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IRRISAT is a satellite-based irrigation advisory service developed in Italy and operational since 2007 in the Campania region (Southern Italy). The service aims at providing farms and managers of water resources with real time information on agricultural water needs. Irrigation needs are estimated using high resolution data from Earth observation satellites and FAO methodology for the calculation of crop water requirements. Data are aggregated at various spatial scales (from field or irrigation unit to district or river basin scale) and temporal scales (real time, historical series).
Nakaseke community radio has for a long time served as a knowledge portal for the rural poor farmers in the impoverished rural district of which over 95% of the community members are purely subsistence farmers.These farmers have for a long time been left out because of lack of vital information on practicing better agricultural methods which has always affected better production.We have achieved this through the use of a community radio station and a web based sms platform (the frontlinesms) to disseminate both audio and text tips on a number of farming issues which in the end have impacted the rural farming community inregaining their potential and much more production has been realized.
In rolling surfaces it is often required for the implantation of crops to be perpendicular to slope, because this procedure is considerably effective to reduce water runoff and soil erosion. The problem that poses in such environment is that level lines across slope are often curve and rarely parallel to each other, contrasting with machinery and crop patterns that are always parallel. This work proposes a method that finds the seed curve for an optimal pattern and models this curve to keep machine steerability. The method finds a hybrid curve from two initial (non parallel) curves using offsets and intersections between these. The hybrid curve can be more similar to one of the two initial curves depending on a weight attributed to its vertices, in order to increase likelihood of the curve to the curve references located in steeper regions. Recursively hybridizing the curves, a final seed curve is obtained which has to be remodeled to achieve a degree of smoothness to avoid parallel tracks to narrow into non-steerable turns. The method was successfully implemented in two stages: for hybridization and steerability; obtaining optimized references for machine traffic.
The application of ICTs is still quite low among the Italian farms; it differs according to the different regions, farms typologies and type of applications. Different studies analyzed the factors influencing the adoption of ICTs in agriculture. Less considered arethe factors influencing the attitude towards the ICTs once they have been adopted (postimplementation stages of a technology adoption). The goal of this paper is to analyze the factors influencing a sustainable adoption of ICTs at the farm, also identifyingpossible intervention strategies for policy makers, farmers’ organizations, extension services and ICTs providers. A Technology Adoption Model (TAM) was applied. A web survey was carried out based on the TAM theoretical approach and the data analyzedusing a Structural Equation Model (SEM) applied to a sample of 766 farmers already using ICTs. The results showed that the Perceived Ease of Use of the ICTs is positively influencing the Behavioral Intention to Use ICTs at the farm; in turn the SEM showedthat the Perceived Ease Of Use is influenced by the Farm Turnover and the farmers’Level Of Education.
CSBP Ltd is the leading fertiliser manufacturer in Western Australia (WA). It is using a computer-aided decision support system (DSS) to assist fertiliser advisory services (“NUlogic®”). Previously a PC-based programme was used by agronomists (users) for the interpretation of soil and plant nutrient analyses and generation of customised fertiliser recommendations. However, the objective for the recent advances in the DSS was to include additional usage for business management and to connect the DSS to farmers and the laboratory conducting the analyses. The DSS is now an online system. Cloud computing stores and automatically backs up large datasets. A smart division of two websites of the same DSS, one “live” stage and one “testing” stage, allows for effective user acceptance testing (UAT) and software training of new advisors without interfering activities on the “live” stage. The underpinning algorithms of agro-economical models are written in a simple programming language, Optimisation Modelling Language (OML). Model updates and improvements in the OML go live after testing and are then instantly available to all users. An analytical testing platform (ATP) uses an application programming interface (API) to connect with the models, other interpretive criteria, comment lists, non-model related inputs, the order of outputs on reports etc, making it cost-effective, flexible and quick for the data analyst(s) to update versions. In addition, the ATP itself connects with the laboratory, farmers and DSS users. Consequently, this DSS allows monitoring of recommendations from DSS users in real time to (1) identify those that require more training and to (2) ensure recommendations comply with Australian standards from the national Fertcare program that audits the quality of advice given to maximise farm productivity, environmental care and food safety. The DSS also logs user’s activities, keeps a record of all current and retired models/model packages with the option of refreshing a retired model/model package, gives full transparency of generated data from recommendation reports for business decisions and offers better software support to users. These advances in the development of the DSS enhance data security, integrity, geo-referencing via mapping capabilities and user-friendliness, offer ease of communication to all users and access to other data storage tools (i.e. farm planning, libraries). Capturing additional data while users are making a fertiliser recommendation is useful to improve market intelligence, forecasting, trend analysis, benchmarking and inventory management. It can be reasoned from a software engineering perspective that this example of a DSS for a fertiliser manufacturer in Western Australia could be easily transferred to other agri-businesses and government agencies world-wide, thereby impacting on the success of businesses and extension services.
The public and private institutions of our country do not have a computer system that allows assessment of the sustainability of the profiles and business plans that arise, provided important today to ensure sustainability. The objective of this project was to evaluate the feasibility of developing and using a computer system with mobile devices, for the formulation and evaluation of production projects under the focus of sustainability and regulations of the National System of Public Investment For obtaining the indicators, employment MESMIS methodology, where it was determined the 20 indicators that were used to build the system. The computer project SYSPROJECT (v.1.0.0), both the mobile and the web have been created with the software development methodology called Rational Unified Process (RUP), object-oriented, using the life cycle evolutionary prototype taking as tools for programming and development to PHP, MySQL, Android, SQLite, eclipse and java. The purpose of this project was to develop a computer integrated both mobile and web, that serves as a tool for management, audit, control, and documentation of business plans and profiles of productive projects.
This paper describes a requirement analysis of a possible “Fourth Party Logistics Pro-viders (4PL)” approach implemented with a 4PL platform in the sector of after-crop logistics. The 4PL approach was analyzed on the basis of a systematic literature review. Subsequently an online survey was created with the consideration of criteria from the Technology-Organization-Environment-Framework. Participants in the survey were freight carriers of the sector. The results of the survey describe the possible functions of a 4PL in the sector as well as approaches for information and communication technolo-gy (ICT) that are currently being applied and will be applied in the future. Moreover the requirements for freight carriers to enter into cooperation and the economic incentives on the part of freight carriers within the scope of 4PL development are presented. Final-ly, future research activities are explained in consideration of possible functions of the 4PL approach in the sector.
STUDIES HAVE SHOWN THAT ETHIOPIAN AGRICULTURAL FACULTIES INTERNET USAGE IN TEACHING AND RESEARCH IS NOT AS TO THE EXPECTATION OF UNIVERSITY TOP MANAGEMENT AND EDUCATION PLANNERS. TO THIS END, THE GENERAL OBJECTIVE OF THE STUDY IS TO INVESTIGATE INTERNET USAGE BEHAVIOR OF AGRICULTURAL FACULTIES IN THEIR ACADEMIC WORKS BASED ON WIDELY USED MODEL IN INFORMATION SYSTEMS: THE TECHNOLOGY ACCEPTANCE MODEL. ACCORDINGLY, THE THEORETICAL FRAMEWORK OF THE STUDY INTEGRATES FOUR EXOGENOUS CONSTRUCTS WHICH ARE PERCEIVED USEFULNESS, PERCEIVED EASE OF USE, FACILITATING CONDITIONS AND SELF EFFICACY. A SURVEY WAS ADMINISTERED TO 193 AGRICULTURAL FACULTIES IN HARAMAYA UNIVERISTY, COLLEGE OF AGRICULTURE AND ENVIRONMENTAL SCIENCES. THE DATA WAS ANALYZED USING STRUCTURAL EQUATION MODELING AND DESCRIPTIVE STATISTICS. THE RESULT OF THE PROPOSED INTERNET USAGE MODEL INDICATED THAT PERCEIVED USEFULNESS (PU) AND FACILITATING CONDITIONS (FC) SIGNIFICANTLY AFFECT INTERNET USAGE OF AGRICULTURAL FACULTIES IN THEIR ACADEMIC WORKS. ON THE OTHER HAND, PERCEIVED EASE OF USE AND SELF EFFICACY DO NOT SIGNIFICANTLY AFFECT INTERNET USAGE OF AGRICULTURAL FACULTIES IN THEIR ACADEMIC WORKS. IN ADDITION, THE MODEL VARIABLES (PU, PEOU, FC, SE) EXPLAINED OVER 59% OF THE VARIANCE IN TEACHING AND 29% VARIANCE IN RESEARCH AND RELATED ACTIVITIES. AS A RESULT, THE STUDY UNDERLINED THE IMPORTANCE OF DESIGNING INTERVENTION IN THE STUDY AREA ON INTERNET TECHNOLOGIES THAT CAN BE USED TO SUPPORT ACADEMIC WORKS. EQUALLY, IMPROVING TECHNICAL, KNOWLEDGE AND PHYSICAL INFRASTRUCTURES IS ESSENTIAL TO ENABLE EFFECTIVE UTILIZATION OF THE INTERNET IN THEIR ACADEMIC WORKS.
The Internet of Things (IOT), the idea of having real-world objects communicating with each other, is changing the way for capturing, organizing and consuming information that comes from the real world, including the agricultural and farming environments. Even if the RFID is a feasible, proven, and cost-savvy technology for items identification, many other data sources or smart sensors could today be integrated to enrich product traceability features. Furthermore, there still is a gap in terms of traceability infrastructures: even if standards for identity exchange mechanism exist, few implementations are known. This paper will describe the “ebbits” event-driven service-oriented middleware, which aims to simplify the development of high value added smart-applications, fostering interoperability with ERP business systems and public authentication systems. The paper highlights the ebbits key architectural features in a concrete life-cycle tracing use-case, exploiting RFID tags and sensors to seamlessly collect data along the whole breeding, slaughtering and distribution chain, giving to farmers, retailers and consumers an integrated products history information.
Management zones partition agricultural fields into sub-units which exhibit homogeneity in yield-defining environmental or plant parameters. Common methods for defining management zones, mainly for field crops, make use of algorithms to partition data observations into clusters based on different similarity methods and often do not account for the spatial neighborhood of the data. Spatial clustering methods, based on spatial statistics, include location of objects and spatial relationships and therefore account for spatial heterogeneity. We present a comprehensive spatial clustering methodology for defining management zones in orchards based on data from individual trees. We have examined the validity of the General G statistic for recognizing global patterns in individual tree data and the Gi* statistic for recognizing local clusters. Results based on case studies on grapefruit in Turkey and plum in Germany demonstrate that point-based spatial-clustering methods and, in particular, the Gi* statistic represent a valid method for delineating management zones in orchards.
Irriframe platform has been developed by Water Boards Italian Association (ANBI) aiming to ensure an efficient use of water resources in the agricultural sector. In the first year and a half of activity 36 water boards all over the country have been involved and 47% of Italian irrigated area has been covered. Daily basis irrigation scheduling has been provided for 3.500 fields through the Web, SMS and Smartphone. Irriframe services in the last year allowed a water saving amount of about 120 million of cubic meters of water in the covered regions. The software has been designed by the Italy based IT company AltaVia srl on the knowledge base provided by the water boards research centre CER. This paper describes the Irriframe services and the main development trends for the near future.
The handheld computer (PDA) is an useful equipment for precision agriculture (PA) in many field operations. But with the growing trend of mobile devices such as smartphones and tablets, PDAs have become a more obsolete option in the technological context. With the idea of creating a new tool for PA based on the speech recognition to replace and/or minimize the use of touchscreen and worksheets in the field, Android was chosen as the operating system for the development of this application. The design was based initially on studies of mobile applications developed for PA through published articles or through monitoring procedures in field data collection. The application resulting from this development is based on three parts: settings, speech data collection and maps. Part of settings allows the user to set some options for operation of the application as: variables to collect, use of GPS, use of speech recognition, file storage folder to ‘txt’ file and registration information, etc. In the data collection the user configures the variables he wants to collect and the application creates a form that is filled through speech recognition automatically. The map is used to help the user navigate the route through the use of Google Maps® base. A ‘txt’ file is created containing data along with geographic coordinates obtained from the onboard GPS of the device and it can be used for creating maps in geographic information systems (GIS).
Positive driving performance and ergonomic effects are ascribed to satellite-based automatic guidance systems. Although the literature had provided some information on working-width utilisation, turning-time requirement and steering accuracy, the relevant studies had mostly been carried out on smaller areas of land under experimental conditions. Little information was found on the nearly-always-mentioned reduction in driver workload. A large-scale field trial under practical conditions was carried out in the Czech Republic for the expanded clarification of the driving-performance and ergonomic effects of automatic guidance systems. Various parameters were recorded for 17 drivers with respect to primary tillage, seedbed preparation and sowing both with and without a guidance system. Working widths were between 5 and 15 m, and field sizes between 1.2 and 15.7 ha. The findings showed that driving speeds, turning times and working-width utilisation were in some cases more advantageous with a guidance system, but did not differ statistically significantly. The variations caused by driver, field shape and field margins had a greater influence than the use of guidance systems. However, two parameters differed significantly. Guidance systems increased average steering accuracy and delivered lower heart rates. The study confirmed that guidance systems can deliver positive driving performance effects and driver relief.
The technology of precision agriculture focuses on the temporal and spatial variability of nutrients in soil quantified their distributions. In this work were collected from soil sampling in a commercial farm with application of swine wastewater to check how are the soil characteristics and their interactions. The evaluations were performed using geostatistics the spatial variability of nutrients and the distribution profiles of 0.00 to 0.20 cm and from 0.20 to 0.40 cm. The study was conducted at Bonsucesso’s Farms, The farm is located in Uberlândia, in the state of Minas Gerais, in Brazil. Fertilization was performed with swine wastewater (ARS) from 6,000 animals in the fattening stage with an average volume of 110 m. per day. Treatments consisted of doses of 8000 m. ha-1 applied over 46 months for Tifton85 (Tifton 1), 5000 m. ha-1 applied at 36 months for Tifton85 (Tifton 2) and 3200 m. ha-1 applied in 26 months in the cultivar MG5. The levels of Ca and Mg indicate that the application of ARS does not elevate the levels of these elements or the extraction of forage is higher than the replacement; The application of ARS does not replace the soil correction, because the base saturation is low and the Ca and Mg has a negative balance; Levels of Phosphorus and Potassium are fully catered with the application of ARS.
Several diseases have affected the maize crop productivity, among them standing out Corn Stunt Spiroplasma (CSS) and Maize Bushy Stunt Phytoplasma (MBSP), which are respectively caused by Spiroplasma kunkelii and by phytoplasma. In Brazil the mollicutes are transmitted to maize plants by the leafhopper Dalbulus maidis which has a remarkable ability to travel long distances if the local climatic conditions are not favourable, e.g., low temperature or high pluviometric precipitation. This work presents a spatial-time deterministic model for analysing the dynamics of the pathosystem “mollicutes – leafhopper – maize” considering a macro region formed by several maize crop fields. From the simulated scenarios we imply that the prediction of the incidence of mollicutes in a maize crop field is only possible when all the other maize crop fields within the travel distance of the leafhopper is taken into consideration.
The major difference between agroforestry and other agricultural production systems is the greater possibility of managing the agroforestry system or its components to facilitate increased rates of nutrient turnover or transfer within different compartments of the system (NAIR, 1993; NAIR et al., 1995). The objective of this study was to estimates of means of leaf area index (LAI) , height and forage production (FP) in the three periods of collectings in a silvopastoral system in the Brazilian Cerrado Biome. The experiment was conducted in a silvopastoral system, located in a farm called Fidalgo in the county of Confins in Minas Gerais, Brasil. The geographic coordinates of the experimental area of this typical Cerrado biome. The experimental area consists of 1.5 hectares. Brachiaria brizantha cv. Marandu productivity was measured quantitatively and qualitatively for three distinctive periods: the beginning of the drought (May 15th, 2009), the middle of drought (July 25th, 2009), period of greatest drought stress, and after the drought (November 23rd, 2009). In the implantation of the experiment was done a cut for standardization of forage at 30 cm above soil. Twelve random points were selected in each system (SPS and pasture), with a total of 24 points. One meter squared collectors made of steel grids were used to prevent animal interference and were placed at each identified location for forage evaluation. Was performed to evaluate bromatologic compositions of dry matter (DM), Leaf area index (LAI). The test was conducted in a completely randomized design, arranged in a split plot, with six repetitions. This study suggests the presence of the tree species Eucalyptus did not interfere in forage dry matter production. Periods of climatic variations observed promoted differentiation in forage production, leaf area and height of the pasture.
The silvopastoral systems have the potential to replace benefits of the current cultivated grassland ecosystems, which mostly consist of monocultures of grasses. The experiment was conducted in a silvopastoral system, located in a farm called Fidalgo in the county of Confins in Minas Gerais, Brazil. The pasture in the SPS and in the adjacent control area, were planted at the same time as the silvopasture establishment. This SPS was established in 1994, without the use of fire. The experimental area consists of 1.5 hectares. Cattle grazing practices depended on forage production during the seasons. The animals grazed for three days followed by a 30-day rest period. In the implantation of the experiment was done a cut for standardization of forage at 30 cm above soil. Twelve random points were selected in each system (SPS and pasture), with a total of 24 points. Conducted the evaluation ADF, NDF, CP and Ca in systems. Observed that there are differences between the seasons of the year and between systems. This study suggests the presence of the tree species Eucalyptus interfere in system only forage. Periods of climatic variations observed promoted differentiation in ADF, NDF, CP, and calcium.
Silvopastoral systems have the potential to replace benefits of the current cultivated grassland ecosystems. The experiment was conducted in a silvopastoral system, located in a farm called Fidalgo in the county of Confins in Minas Gerais, Brazil. The pasture in the SPS and in the adjacent control area, were planted at the same time as the silvopasture establishment. This SPS was established in 1994, without the use of fire. The experimental area consists of 1.5 hectares. Cattle grazing practices depended on forage production during the seasons. The animals grazed for three days followed by a 30-day rest period. In the implantation of the experiment was done a cut for standardization of forage at 30 cm above soil. Twelve random points were selected in each system (SPS and pasture), with a total of 24 points. Conducted the evaluation bromatologic compositions of dry matter (DM), mineral matter (MM), phosphorus (P), and forage composition (lignin). Observed a significant effect on production in forage of lignin (LIG), mineral matter (MM) and phosphorus (P). MM, P and LIG were significantly higher in the SPS (P<0.05). This study suggests the presence of the tree species Eucalyptus did not interfere in Phosphorus Management. Periods of climatic variations observed promoted differentiation in forage production, and absorption of Phosphorus.
In our papers we discuss the issues of collection, processing and visualization of positional data. Gained knowledge and principles have been used for example in game’s spatial activity evaluation in the Doupovske Mountains and the Sumava National Park in the Czech Republic. The database for analyses and processing have been formed by large data set obtained by cooperation with the Military Forests and Estates of the Czech Republic, the Sumava National Park and the Faculty of Forestry and Wood Sciences at the Czech University of Life Sciences in Prague. Analytical and software solution have been developed by the Department of Information Technologies Faculty of Economics and Management at the Czech University of Life Sciences in Prague and is also being administered, managed and run by this IT department
Trichoderma species are known by having the ability to stimulate the growth of crops. The production of a growth promoter from Trichoderma harzianum is a viable alternative for replacing chemicals that represent a high cost in the production of vegetables. In this study it is determined that the application of the electromagnetic field for 30 minutes at 110 mT, produce an increase of 39 % in spore production compared to untreated fungus. It is also proved the possibility of using Trichoderma harzianum as a growth promoter. With the application of the inoculum magnetically treated for 30 minutes at 110 mT to bean seeds, it was obtained an increase of the main root length by 55% and the number of secondary roots by 86% compared to untreated inoculum.
Agriculture in Austria is currently facing many challenges. Innovative products, the increase of efficiency and the careful use of resources are the critical prospective factors for further success. In order to meet these requirements it is more than necessary for Austrian farmers to intensify the usage of modern IT systems.Taking this hypothesis as a basis, the present paper, supported by declarations of farmers, manufacturers of agricultural machines and IT-service providers, describes which systems are currently available on the market and how these modern IT systems can support Austrian farmers in the near future.The conducted market analysis shows that nowadays there are already many IT systems which cover different realms of agriculture. In the future, IT in agriculture will be affected by topics like integration of operating data as well as traceability and sustainability of agricultural products, amongst other things. Based on these subject areas, two possible future scenarios are described which illustrate how IT can be best used in the agriculture of the future.
Irrigation management necessitates better understanding of the water demands of various plants in order to decrease environmental risks and increase water use efficiency. The difficulty in measuring evapotranspiration (ET) from urban landscape plants inhibits the development of sustainable irrigation management strategies. In warm climates, evapotranspiration as the main component of irrigation needs to be quantified accurately. Traditional methods of ET estimation are mostly time-consuming, relatively expensive and lack the coverage required for large areas. Recently, ET estimation has been benefitted from advances in remote sensing (RS) and GIS techniques. Different algorithms and models have been introduced that employ GIS/RS application in order to study various biophysical parameters of vegetation. For instance, the Normalized Difference Vegetation Index (NDVI) is often recommended as a useful indicator to study ET rates. NDVI quantifies the photosynthetic vegetation response to red radiation absorption and near infrared reflectance. This research explores the potential relationship between urban vegetation ET and RS vegetation indices in an urban park; Veale Gardens (VG) within the Adelaide Parklands, Australia. A data set of cloudless WorldView2 imageries of consecutive seasons in 2012 were used to quantify NDVI and NDRE values. ERDAS IMAGINE was employed to image processing, geo-referencing, atmospheric correction and NDVI and NDRE map generation. NDVI and NDRE maps were clipped to the borders of VG and then imported to ArcGIS for zonal statistical analysis. ET rate for VG was estimated using an observational-based approach, namely Water Use Classifications of Landscape Species (WUCOLS). A short description of the WUCLOS method is provided, which is then applied to the study area. In-situ weather and vegetation data were collected and irrigation monitoring data were provided by the local water authority. A panel of horticulturists assessed and rated the most common plant species in the park in terms of drought tolerance. The relationship between RS-based NDVI and ETWUCOLS was investigated. Results showed a strong positive correlation (R2 = 0.95, P < 0.01) between ET of urban landscape vegetation and NDVI. The outcomes indicate that remotely sensed NDVI may be an efficient indicator of the water demand of urban landscape vegetation. In contrast, NDRE is not a suitable indicator of urban vegetation water demand.
Experiments were carried out under field conditions to evaluate the effects of composted tannery sludge (CTS) on soil pH, electric conductivity (EC) and soil organic matter (SOM) content after three years of application. The treatments consisted of five rates: 0 (control), 2.5, 5.0, 10.0 and 20.0 t ha-1. In each year, soil samples were collected 60 day after CTS application. After three years, The CTS increased about 5, 46 and 69% the soil pH, EC and SOM content as compared with the control. Each soil parameter showed linear increases with CTS application. Consecutive applications of crescent rates of CTS promote linear increases in soil pH, electric conductivity and organic matter content.
The aim of this research was to study the feasibility of growing organic vegetables using saline waste from the water treatment station in the community Bom Jesus, in Campo Grande, RN. The research began with the establishment of a community garden according to systematic principles of agricultural sustainability in ecological basis. The participatory planning, in which all activities in the project were planned and performed democratically with the community, was the methodology adopted. Vegetables like coriander, chive, tomato and rocket were grown in the site available for the research, sowing a legumes and grasses mixture to produce plant material, a breeding (elephantgrass), and planting forest and halophyte species (Atriplex nummularia). The appropriate disposal of the saline waste gave a conservative nature to the project and also the possibility of an alternative source of water for agriculture, emphasizing the efficiency of use of water in semiarid regions. It is concluded that there were yield losses in all species grown with water of saline waste – from 25.30% to 26.7% in relation to the conventional irrigation systems (fresh water); but there was biomass. However, the vegetable growth was successful in the community, because it could change the resident's mind about the disposal and reuse of the saline waste.
Japanese farmers are aging and agricultural robots of the cooperative working type, which perform tasks together with humans, are required in particular. Additionally, in the case of the cooperative working type, compatibility with humans is important and the functions that can be controlled intuitively even by new agriculture workers and elderly people are desired. The function is Kansei communication, and we proposed agricultural robots, such as the Kansei Agri-robot ,which is equipped with the function, and the Chinou robot, which extracts tacit knowledge. We have been studying and developing them. In this paper, we built and evaluated an intuitive control part using motion, which is one of the core techniques. We built the system using the Kinect sensor, which can trace the skeleton information of a human. The Kinect sensor is a gaming device for the Xbox 360 and was released by Microsoft Corporation in 2010. It consists of an infrared light for distance sensor, video sensor, distance sensor and multiarray microphone. The target motion control was the “finger pointing” motion to provide the robot a working area or location for movement. As for the development environment, we used Windows 7 as the OS, OpenNI as the library, and NITE as the middleware, and we also used Visual Studio 2010, C++ language, for software development. The results are as follows: First, the skeleton information of a farmer could be extracted from various angles using the Kinect sensor. Next, an algorithm to calculate “finger pointing” points from the information of the joint coordinates of the shoulders, hands, and feet could be built. According to the verification experiment, the accuracy was high when compared to the assumed robot size and working area, and the control of a robot by hand pointing became possible. The estimation errors vary depending on the sensing angle of the robot toward the farmer, and the errors of sensing from behind the farmer were greater than those from other angles. It was also found that the Kinect sensor can be used even in the field in early morning and after late afternoon when the light intensity decreased and under artificial lighting.
Kansei engineering is one field of engineering where the feelings of humans are applied to manufacturing. If Kansei can be extracted, the design, development, and evaluation of various things are possible. This study aims to build an automatic design and evaluation system for agricultural products and landscapes and then utilize the system for the evaluation and improvement of educational effects. In this presentation, we built a low price and near real-time system to extract Kansei information from the facial expressions of users and obtained knowledge about Kansei. Additionally, we created an algorithm to discriminate Kansei. We built a system to obtain facial expression information of a user from a camera image as our experimental equipment. The characteristic values calculated from them were the variation (or the normalized polygon area change ratio) of the four items; the inner ends of the eyebrows, upper parts of the eyes, lower parts of the eyes, and the corners of the mouth. The target Kansei was three items: positive Kansei (liking, fun, and happy) and negative Kansei (unpleasantness and hatred). The results are as follows:First, for the target three Kansei, changes could be captured through the four specified normalized polygon area change rates. As for the positive Kansei, the changes in the corners of the mouth were greater than those of the others in particular. As for the negative Kansei, the changes in the lower parts of the eyes were slightly greater than those of the others and, as for the Kansei of surprise, the changes in the corners of the mouth were slightly greater. The direction of the change showed a tendency where the positive Kansei increased at the corners of the mouth in particular. The negative Kansei showed a strong tendency to decrease at the inner ends of the eyebrows and the lower parts of the eyes in particular. The Kansei of surprise showed a tendency where the normalized polygon area change rates increased as a whole. Next, we selected one subject because the relationship between the facial expressions and Kansei varies among individuals, and then we built an algorithm to discriminate the three Kansei features. As for the Kansei of positive – negative and negative – surprise, it became possible to discriminate at a rate of nearly 100% from the information of the corners of the mouth. It became possible to discriminate the positive-surprise at a rate of about 80% from the information of the upper parts of the eyes. As described above, although it is necessary to prepare the template image of the seven points of the target person and adjust the parameters after measuring the Kansei facial expression in advance, a low price and near real-time computer vision system to extract facial expression Kansei could be built
Recently, climate change has emerged as an issue that affects many aspects of society. Because changes in water resources have a direct impact on the growth of crops and the ecosystem, water management is an increasingly important challenge nationwide in the USA. Output from a soil water balance model can be used as an input to an agricultural productivity model or a vegetation model, which would be used to identify the need for measures to address drought. In this study, a daily soil water model was developed based on a grid analysis of the spatial distribution of water stress. As a test case, the model was applied to Illinois State, USA, where various field observation data as well as digital maps were available to the public. Inputs to the model can be divided largely into soil, climate, and crop data, and their various coordinate systems and spatial resolutions were adjusted to match. Data on soil attributes were obtained from Soil Survey Geographic Database Soil maps by the USDA Natural Resources Conservation Service. Climate data were compiled for 2001–2012 and daily precipitation and reference evapotranspiration from the Penman-Monteith method were spatially interpolated. Several water balance indices were developed to quantify the degree of water stress. The results showed that the water stress conditions in Illinois were bad in 2002, 2005, 2007 and 2011, with the most severe water shortage in 2005. This model could be applied to agricultural water stress evaluation over any scale, from local to global.
This work focuses on the development of a user interface suitable for targeted spraying, using a robot that is teleoperated along the vineyard rows. A prototype of the spraying interface was developed and the usability of three different interaction modes was investigated. Fifty participants were asked to use the three devices to select grape clusters taken from a simulated robot moving along rows in a vineyard. Next, participants completed a questionnaire related to their user experience with the system. This paper presents the results of the statistical analysis of the log files and questionnaire responses to compare the three devices.
Agri-Food business requires access to increasingly accurate, detailed, and up-to-date information and data. Worldwide, agriculture lacks the coherence and coordination for exchanging these data. Many data are captured in existing information systems, but for developers of new services it is often difficult to use the data of these systems in order to make them interoperable. This paper describes a reference framework for interoperability that was developed in the agriXchange project. Use cases play a key role in interactive development of the framework. The framework’s functions are introduced by a kind of a work flow process using reference information models. The aXTool supports the implementation of the framework in the agriXchange platform, which is supported by a web portal and community of practice. The aXTool systematically supports developers and other users to share and re-use knowledge and concrete components concerning data exchange in agriculture.
In remote sensing, many spectral indices such as NDVI (Normalized Difference Vegetation Index) or NDWI (Normalized Difference Water Index) have been developed for plant management in agriculture. However an essential problem exists that the remote sensing indices are not based theoretically on the spectral properties of the molecules of photosynthetic pigment, nutrient or water in plant. This article presents that spectral properties of the pigments and water were analyzed with a molecular orbital method derived from quantum chemistry and related to remote sensing indices. The electromagnetic wave absorption spectrum calculations for a single molecule of chlorophyll a, lutein and water were carried out with semi-empirical molecular orbital method software. The chlorophyll a is main photosynthetic pigments in plants and lutein is one of carotenoids served as sub material of the pigments.Water molecule is the solvent in pant cells. Chlorophyll a showed two main absorption bands in 360 nm and 600 nm, and lutein in 410 nm. The molecules showed their main absorption bands moved low in a region of 50 nm to 100 nm approximately in comparison with the actual bands in vitro measured by a spectrometer. This difference was thought due to a solvent effect. Both molecules are actually surrounded with water, protein and other molecules. The NDVI uses reflectance from a red absorption band around 660 nm and a nearinfrared around 860 nm, suggesting that the NDVI dependents strongly on the spectral properties of chlorophyll a.Water molecule showed the three main absorption bands in k1=3,850 cm-1 (2,600 nm), k2=1,750 cm-1 (5,700 nm), k3=4,000 cm-1 (2,500 nm), ranging in infrared and caused from the oscillations among the three atoms of H2O. Those fundamental absorption bands created two characteristic compound absorption bands at red color region around 600 nm and at infrared around 900 nm. For examples, k1+3k3 =15,850 cm-1 (630 nm) and 2k1+k3=11,700 cm-1 (850 nm). The NDWI is defined as the reflectance ratio of (860 nm - 1,240 nm) / (860 nm + 1,240 nm), implying a relationship with the characteristic compound absorption band in 850 nm of water molecule.
Pcdairy Enterprise is a package of computer programs for formulating and analyzing rations for dairy cows. It consists of three programs: PCDAIRY ration formulator, SHIELD ration composition evaluator, and CTR ration timing evaluator. The user start with formulating a least cost ration in PCDAIRY and then proceeds to evaluate the composition of this least cost ration in SHIELD, and then proceeds to evaluate the timing of feeding of different components of this least cost ration in CTR. This paper describes these three programs (PCDAIRY, SHIELD, CTR) and the interface between them.
The purpose of Agricultural Machinery certification is to provide good information to user and to promote for export of Agricultural machines and to develop and distribute of good agricultural machines. We have 5 types of Agricultural machinery certification i.e. general certification on performance, safety and technology roadmap, safety management including safety device check for traveling type agricultural machinery, and certification on machinery used in APC(Agricultural Products Processing Center), RPC(Rice Processing Complex), greenhouse etc. and certification in agricultural machinery emissions.We have developed the Agricultural Machinery Certification Management System (AMMS) during 5 months and field department members have been used since 1th Jan. 2012. The Main functions of this system are requests, accepting and testing of agricultural machinery certification, issue a report for those agricultural machines. Also, we made a process and a standard by all step, and build a database by input theirs result each steps. So, it is possible to analysis and management every each step. The System can provide many types of statistics. Furthermore the system’s efficiency and reliability are getting increased by auto-issue a report. We have certified about agricultural machines 937 times on the AMMS in last year. It means that one person have certified for 67 times agricultural machines. And, this system is linked to E-approval system, so user is very easy to use.
Spotting risks in the food chain is a daily challenge faced by growers, importers, producers, retailers, laboratories and regulators. It is a task made all the more difficult by having to wade through endless reports, often in foreign languages, and trying to compare the results of this search cross-country just to find the bits that might apply to you. The regulatory framework concerning the occurrence of pesticide residues (MRLs) is changing. The standardization of the MRLs for EU members helps but the problem with registered versus expired agrochemicals remains (last use/expiry date). For some active ingredients (ai) no MRL exists but there are still agrochemicals with this ai in use. Homologa™ is set to change all that by providing agronomic information including the current pesticide product approval status of over five dozen countries together with the associated MRLs to support the development of business strategies and to ensure compliance within the prevailing regulatory frameworks. It facilitates the access to regulatory data and hence saves important resources to its subscribers. There are numerous examples in which Homologa has been used to resolve critical problems. Subscribers can search online for expired and registered crop protection products as in several countries in a single report allowing side-by-side comparisons. There is also the possibility to receive alert e-mails when registrations or MRLs change. In addition, the new version of Homologa™ provides access to product label information for many countries and companies. The database can communicate with other user platforms using a WebService. The Homologa™ Team and it's global collaborators constantly update the database. Today the mark of 7 000 000 lines of registration data is passed and will continue to increase further.
A review of the recent literature on determinants and factors that influence intention to adopt and adoption of Precision Agriculture technologies was performed. The analysis covers both ex-ante and ex-post approaches to behavior modeling. Results suggest that some constructs are relevant both ex-ante and ex-post, while others are presented differently in the two situations. A discussion of adoption as a process, and, the need to include the consideration of this process in the analysis of new technologies is also provided.
Residual Biomasses from agriculture and forestry activities are among the most promising renewable energy sources. To face the growing need of such resources for the energy producing industry the delivery of residual biomass fuels must be effectively enhanced compared to the current state. By help of the simulation software “Vensim DSS” ® (Ventana Systems Inc.) we developed a set of equations representing one biomass harvesting and supplying chain. The considered system, which has the Time step of one day and covers a time span of three years, is composed by three sub models which are related to: a) energy plant dimensioning; b) supply transport cost estimation; c) harvesting and conditioning operations cost estimation. Model output underwent to univariate and multivariate sensitivity analysis to check its behavior at changing of parameters’ values. Model behavior turns out to be quite robust at varying of the input parameters for all the considered variables: evaluation of behavior pattern measures showed that with reference to €/MWh primary energy equilibrium level is quickly achieved meaning that negative feedback loops become soon dominant in the system.
This paper identifies gaps in standardization of agri-food logistics. Out of the European FP7 SmartAgriFood project a framework for classifying existing standards within the agri-food supply chain is introduced. Furthermore the characteristics to which a semantic standard should adhere are investigated. The standards classified as semantic out of the framework are assessed along these properties. The resulting conclusion is that the standards that are already present in the chain are more focused on syntax and lack semantic properties.
Research over the years has shown that it is possible to set production targets for pomefruit orchards. Based on tree density, targets can be set for yield levels and fruit size, that translate into the optimal crop load (fruit number per tree). When this is achieved via thinning, the question remains open: how to make sure that growth of the fruit is progressing correctly? Precision fruit growing research answers this, by making it possible to evaluate the management carried out by the grower, and to assess whether or not it is in line to achieve the desired quality and yields targets.
The data acquisition and process control is one of the main problems faced by engineers and researchers responsible for automation and analysis equipment and agricultural processes in real time. For a decision about the characteristics of the process are carried out with a greater chance of success, it is important to know and monitor the parameters related to its performance. Thus, the aim of this work was to develop a computer program in order to register and display real time information about the process and the dynamics of weight loss product. The system was implemented using the LabVIEW software. Developed Virtual Instruments (VI) for the following types of sensors: load cell, PT 100, Transducer of electrical, air humidity and frequency inverters. Obtained the application DRYING OF GRAPES for monitoring and controlling the process of partial dehydration of grapes developed, which was observed during the tests, ease of operation of the system, allowing the rapid acquisition of data, and the ability to combine the system implemented to meet the demands of several studies, and can be used in different types of agricultural products.
There are many examples of tools to support decision making; one such tool is the SIINSAT-V1 system, which we present in this paper. SIINSAT is the Spanish acronym for "Sistema de Información para el Inventario de Imágenes Satelitales”, an inventory information system to support the selection of satellite imagery for agricultural applications. SIINSAT-V1 supports queries about satellite images of different satellite sensors. The image information is contained in a database appropriately designed and structured. This software system provides historical imagery information available for a specific area of the Mexican Republic of particular interest to decision makers and academia interested in agricultural information. For each image the information includes: sensor information, date of the scene, resolutions, bands and a JPEG preview file to visually present the percentage of cloud cover of the optical images. The system searches satellite imagery information as requested by the user. The search terms include month and year, geographic and geopolitical area; the query result is displayed in a table of key existing images, resolutions, etc. Also displayed is an image which allows the user to appreciate the percentage of cloud cover and decide whether to use it and download it or not. The current version 1 of SIINSAT runs like a web application and is currently being evaluated by typical users. To facilitate access to SIINSAT-V1 for all interested persons, version 2 (V2) will be enhanced with a redesign of forms and it will be standardized so that it will run on any platform.
On a global scale, environmental challenges are forcing local communities to re-think ways of interacting with the environment. Environmental problems present themselves in various forms and call for a profound change in the way we perceive the environment around us. To tackle them, new ways of approaching them have to be deployed, gathering around the same table, environmental experts, citizens, scientists of the environmental field as well as others from various background such as information science or economics. Green Ideas events provide the process with which these people will be able to meet in a lively setting that fosters creativity and innovation. This paper will outline the process on which Green Ideas is based and analyze the basic requirements for carrying out similar events that address carefully selected and articulated “design goals”, related to green topics. The paper will also showcase results from the successful completion of previous Green Ideas events and discuss ways in which these ideas can be transferred from design to implementation in real-life settings. The main contribution of this paper is the presentation of a tested methodology that can help in addressing a series of different problems in any field, customized to fit environmental cases.
Optimizing production systems in agriculture and farming environments can nowadays be helped by advancements developed in other domains. In the field of precision live-stock farming, solutions enriched with ICT, robotics and automation components are increasingly used to improve processes’ efficiency and flexibility. This paper proposes a pervasive ICT system to monitor and record eating behavior of fattening pigs, leverag-ing on HF RFID ear tags identifiers (to detect animal eating while the head is on the trough) and on Camera Vision Systems (to cross-validate RFID reading). In addition a Synergistic Control algorithm is applied due to analyze information, extract feeding behaviors and detect eventual issues. Finally, these information are made available on the network, to the end-user, through the Virtus Middleware: it is an Internet of Things (IoT) system enabling seamless data integration and event sharing, able to manage het-erogeneous information sources and geographically-distributed, large-scale deploy-ments.
The use of learning analytics is constantly increasing during the last years in the context of the evaluation of a wide variety of learning-related services, such as the learning portals. Especially in the case of multilingual learning portals, learning analytics may act as indicators that provide insight on the use of the multilingual aspects of the portal, such as the multilingual user interface, the use of translated metadata records and classification systems used for the classification of the resources as well as the engagement of the users in the portal by metadata translated in their own language. This paper provides the preliminary results of an analysis (Protonotarios et al., 2013) which aimed to identify the use of the Organic.Edunet Web portal by users coming from developing countries. The analysis was based mainly on the log files of the portal and the correlation of this information with related information coming from other sources. Based on the outcomes of this analysis, a number of requirements are defined in order to be used as a basis for further work related to multilingualism in the specific portal.
Agriculture is an important sector where majority of the rural population in developing countries like India depend on for their food and survival. Due to dwindling natural resources for agricultural production, the farming sector is now faced with a challenge. The ever increasing demand for agricultural products due to the increasing population, especially in India, offers opportunities for farmers to opt for sustainable agriculture and improve their livelihood. Recent advances in Information and Communication technology (ICT) has brought about a change even among the farming population. The prevailing ICT provides ample opportunities for skill up gradation among rural population, especially farmers in agriculture and to overcome community based development issues, through value addition in agri produce supply chain and also enhances the entrepreneurial behavior in the rural population. Many a times availability of information on time is the problem faced by farmers in India, especially agro input like seed, varieties, farm equipments, fertilizers due to wide spread customer base and multi product and multi-tier distribution system .This can be overcome by the Market led agriculture and market intelligence which is the solution to the problem and is absolutely necessary considering the present trends. Keeping these factors in mind as the need of the farmers, innovative ICT application could be seen today to disseminate the agricultural and related information on the various electronic media. The information seekers today are relying on speedy ICT tools such as computer, Internet, Mobiles etc. In the South Indian state of Karnataka, a number of initiatives for the benefit of farmers have been launched by the government and private companies to cater to the requirement of the farming community. To cite some of the successful cases- the ‘Bhoomi’ project of Karnataka government, where land records can be accessed in almost every village. ‘Krishi darshana’ programme on government T.V channels and also “Anna data” programme by a private T.V. channel. An Expert Centre of the University of Agricultural Sciences (UAS) Bangalore also provides the Teleconferencing facility, apart from forecast of Weather, Pest and Disease through mobile updates. The Government owned ‘Kissan Call Centre’ (KCC) working with a toll free number provides service to the farming population by answering queries over phone lines. These are the advancements in the field of agriculture through ICT application where in farmers are reaping the benefit of agriculture related information, learning skill oriented operations and adopting modern agricultural methods leading to sustainable agriculture
Geospatial information is becoming available increasingly in digital representations and can be created and consumed with the help of various different devices and services. Due to the increasing application of precision farming techniques the importance of spatial information and their implementation has become a key issue in operation planning and application in agriculture. Within the ICT-agri funded project GeoWebAgri present precision farming workflows for geo-data handling and data exchange have been analysed. User groups in the precision farming domain, consisting of heterogeneous users like farmers and many others, have identified the benefits of the idea of precision agriculture. Nevertheless the current usage of those techniques is still inhibited by nonflexible, restricted and hard to use systems. Identified by a survey, the concept of a Spatial Data Infrastructure for Precision Farming applications (SDI-PF) was developed to particularly overcome the problems of geodata handling, because present Farm Management Information Systems (FMIS) and precision farming tools fulfil the needs only partly. The information-intensive, location-related tasks of precision farming were analysed and decomposed. Following the concept of Model Driven Architecture (MDA) a conceptual model was developed using the Profile for GML application schema of the Unified Modelling Language (UML). The derived physical models can be used to exchange PF data in an infrastructure, based on a server-client communication, driven by web-services and the standards from the Open Geospatial Consortium (OGC) and International Standardization Organization (ISO). The approach was tested by modelling an exemplary application of precision weed control and made a positive outlook for the integration of tailored services into existing task controlling, as well as maintaining interoperability with ICT-infrastructures of close-by domains
Experiments to measure and quantify airborne spores of Sclerotinia sclerotiorum in oilseed rape fields was undertaken in a specially sown field at Rothamsted Research (Hertfordshire, UK). Airborne ascospore concentrations were estimated by quantifying the DNA of Sclerotinia sclerotiorum present on daily samples (waxed tapes) retrieved from Hirst-type spore trapping devices. The corresponding weather data was taken from a climate station in the field and another 1 kilometre away. This data was used to test an existing model of disease incidence and can be used to inform growers of the right time to spray their crops. Inoculum, sclerotia of Sclerotinia sclerotiorum were deliberately planted in a ring at the centre of the field-site the previous autumn. In the early spring, the trapping devices were placed in the centre of the ring and operated continuously to provide a record of spore presence. Air samples were sent to a laboratory in Rothamsted Research for DNA extraction and qPCR measurement. In parallel, the measured weather data and also information about the Rothamsted field was used to predict the likelihood of spore release according to the “Raiso-Sclero” model. The qPCR readings of spore presence were successfully recorded and inputted into the various models. The Raiso-Sclero model was successful at identifying the important periods of spore release however it provides a substantial number of false positives. The model gives growers valuable information on when disease incidence is likely to occur and can lead to more efficient crop spraying regimes.
We present the model of a new information system for agribusiness management that supports Direct Costing and Activity Based Costing analyses. It has three main elements of novelty in comparison with existing systems. First, it collects real cost data making use of specific technological solutions. Second, it adopts Direct Costing and Activity Based Costing approaches to elaborate cost data. Third, it presents a structured section of reports, including what-if analyses, to support farm management decisions. We designed the model evaluating user needs through different round of interviews. The model aims at identifying the information requirements for the introduction of structured cost management approaches in Farm Management Information System development and depicts a viable design of the system supported by a working prototype and a set of reports for farm decision makers.
Effect of soil salinity on the photosynthesis and growth of paddy rice was investigated with a measurement of chlorophyll fluorescence. A nursery rice of 61 days after seeding was transplanted in the 1/5,000 a pot of 3.8 L in volume. The pot was filled with soil of 3.0 L. Before the transplantation, the soil was prepared with spraying the NaCl water adjusted to the four concentrate conditions of 0 ppm as control, 1,000 ppm, 2,000 ppm and 4,000 ppm. The saline concentration means a mass ratio of NaCl to dry soil. To each saline condition, six pots were examined. Growth parameters (height and stem length) were measured weekly after transplantation. Photosynthetic parameters (Fv/Fm, Fv’/Fm’,ΦⅡ, ETR, qP, NPQ) were also measured weekly with a chlorophyll fluorescence measurement tool. After harvesting, yield parameters (grain numbers, weight and density; root, stem and leaf dry weight) were measured. At the ripening stage of 150 days after seeding, the plant height reached maximum in every pot and was 70 cm (100%) in the control, 58 cm (83%) in 1,000 ppm, 50 cm (71%) in 2,000 ppm and 45 cm (64%) in 4,000 ppm. The plant height decreased strongly with an increase of saline concentration. Photosynthetic parameters except NPQ were decreased with an increase of saline concentration. NPQ (Non-photochemical quenching) means heat dissipation in PS (Photosystem) Ⅱ. Fm (the maximum chlorophyll fluorescence in the dark) and ΦⅡ(the effective quantum yield of PSⅡ) are related to the activity of the manganese cluster located at the end of PSⅡ. Decrease of Fm and ΦⅡ means that the manganese cluster reduces to electrolyze water into H+ and O2. In conclusion, we can explain the salt damage in plant as follows. An excessive salt brings water deficit in the photosynthesis in leaves by the water potential reduction in roots. The water deficit reduces the photosynthetic activity. Then photon energy is excessive and dissipated in heat. Thus excessive salt leads photosynthetic damage and brings yield loss. Keywords: Chlorophyll fluorescence, chlorophyll intensity, paddy rice, photosynthetic activity, salt stress, Japan
Recently, the scaled farm management has been made by the crop cooperative cultivated group and the agricultural product shipping group of local as well as cultivated acreage expansion. It has increased the need for farm management software so due large scale farming. We has been disseminated the PC-based farm management software from 10 years ago, but it has not been activated because farmer don't like to record and do not feel the need about farm management. Recently the dissemination of smart phones and smart devices tab is increasing rapidly. we propose ways of using activated farm management software using a variety functions of smart devices. This application was developed to run on iOS and Android smart devices. It consists the four menu that is farm daily record, household ledger, the latest news and Configuration management. farm daily record has the function of input, modify, and retrieve the contents of farm work by crops. The household ledger has the management functions of household income and expenditure, and settlement of accounts.
The new information and communication technologies (ICT) have become an essential part of business. Because of this, we have developed a lot of scientific research on adoption issues and benefits of using ICT in all types of businesses. In agriculture and agribusiness are no exception. However, there is little research conducted in developing countries and virtually no studies of this type for countries in Latin America. This paper presents the results of an exploratory research developed in a group of technicians and producers MasAgro program in the state of Chiapas by the Secretary of State SAGARPA, Mexico. The study examined the factors of value creation in the ICT decision-making according to the perception of the program directors. The survey used was applied to 90 producers representing corn producers in the region. The instrument designed to obtain information was a questionnaire with a total of 60 questions, the questionnaire is divided into four sections, the first of which collects the information about the interviewee and performance. The next section asks about the use of ICT, the third section aims to analyze the perception of the companies surveyed in relation to ICT, and the last part is dedicated to analyze the factors that influenced the adoption of these technologies. The results show that the degree of adoption of ICT presents technical and program producers in the state of Chiapas is still basic, since the use that is given to the use of Internet is not going beyond the banking, the consultation climate and information searches. This research contributes to knowledge in this area helping the understanding of the different facets of ICT adoption in rural enterprises in developing countries. Proposing a second phase to the adoption of the proposed model which depends on the initial level of use of ICT in the study group as well as the technical characteristics and producers, and the process of promoting innovation for use. The adoption shows differences in knowledge management to define the model of use for the development of their daily activities, aimed at harnessing the potential based on the current situation of ICT, which will make up an integrated system for decision-making in real time. The most influential factors in the adoption of innovations are the characteristics and level of knowledge of ICT, where the digitization of information is based on the use of computer technology, and implementing the widespread use of ICT in transactions economic and trade MasAgro program in the state of Chiapas, México.
In the last years we have seen a growing complexity and an unusual dynamic in the markets for food commodities, now comparable to those of more sophisticated financial systems. Productions are strongly affected by these imbalances, and classical models of demand and supply are no longer able to describe evolutions and developments for these markets. A food commodity is the result of a complex series of production and transformation processes, which determine price and availability. This study aims to a complete mapping of the major food commodities of animal origin, milk and meat chain. The main objectives of this presentation cover many of the issues that the governance and the players of food industry, from producers to processors, have to face without appropriate tools for qualitative and quantitative assessments.
This paper reports the result of test on a prototype of a simple device using ICT technology to monitor pests in vineyards and orchards using a trap with specific pheromones lure. The device acquires set of images of the surface of the trap at fixed time intervals and record the environmental temperature and humidity. The data and the captured images are stored on a server that offer a free file hosting and sharing service, making possible the remote access to the information.The system is based on an industrial IP camera with wide-angle lens appropriate to the capture field dimensions (260x200 mm) and a LED illuminator that ensure a correct and uniform illumination. Illuminator and environmental sensor (temperature and humidity) are governed by an I/O card which can be programmed according to the needs. The entire system is controlled by a dedicated software running on a embedded mini-ITX PC. The software is designed to fully automate the acquisition of images and environmental parameters. The recorded files are stored on a local disk and are automatically synchronized with a free file hosting service that makes them available on the internet. In this way, authorized users, can access to images from any device with internet connectivity (e.g. smartphone, tablet, pc). The system is completely autonomous with power supplied by a solar panel and allows a complete remote visual check
vite.net® is an interactive, web-based DSS for sustainable vineyard management which was developed in such a way to overcome all the limitations (both technical and of low acceptance by end-users) met by the DSSs for crop management developed up to now. vite.net® is targeted to the vineyard manager (i.e., the person who makes decisions or provides consultancy about the vineyard management) and includes several components such as decision supports for canopy management and for disease and pest control, indicators of the eco-toxicological impact of the plant protection products, alerts on potential abiotic stresses (cold temperature damage and water stress), and estimates of the pending yield. Thanks to its holistic vision of the vineyard management problems, the accessibility and versatility of the service as well as the intuitive and interactive nature of the web-portal, vite.net® is a unique tool in the current panorama of DSS for grape production.
SmartDDS is a three-year-study, financed by the German Ministry of Agriculture. Our ambition is to develop an app for mobile devices that can identify plant diseases by analysing digital images at minimal computational costs. The first aim is to identify fungal leaf spots on sugar beet which are hard to differ like Cercospora beticola, Ramularia betae and Phoma betae. First tests showed promising results with a recognition accuracy of more than 97 %.
The canopy area of a tree characterizes its assimilation area, and hence its water and nutrient requirement. The primary aim of the ‘3D Mosaic’ international research project is to improve water and fertilizer management in orchards. To achieve this, canopy are-as should allow for better, tree-based water and fertilizer management. The aim of this study was to further develop methods for measurement of the canopy area. In a plum orchard in Potsdam (DE) with 180 trees, two different methods were applied to measure the canopy area. The first consisted of a plane-laser (LiDAR) mounted on a frame which was driven through the orchard by a tractor. The second method was based on near-infrared (NIR) imaging with standard cameras. The near-infrared images allowed efficient image segmentation to aid in determining the leaf area, which was calculated via an average pixel area. Consequently, both the LiDAR and NIR methods express a relative rather than an absolute measurement of the canopy area. The comparison with the real leaf area showed that the two methods can be well calibrated. Both methods performed well over the two-year period. The measured canopy areas in 2011 and 2012 correlated with 0.91 and 0.88, respectively. The differences are explained by the fact that the laser changed position from one measured laser plane to the next, and the cam-era took only one image per tree, from a single position. Owing to the different perspec-tives from where the measurements were taken, protruding branches and leaves result in different shading effects, creating the above-mentioned variation. Both methods are suitable for accurately measuring canopy size. Calibration of the rela-tive measurement with the real leaf areas allows the leaf area to be calculated. Whereas the laser has the advantage of enabling easier data treatment, the camera system is much less expensive than the laser. Both methods would readily lend themselves to full auto-mation, which opens up interesting opportunities for future tree-specific orchard man-agement.
A computational model for electromagnetic wave propagation through tree orchards is presented. Branches are modeled geometrically as tapered cylinders and trees are defined as collections of branches; each branch has its own starting point and orientation, expressed as three Euler angles. Tree canopies are modeled as dielectric spheres of appropriate dimensions. To simulate a tree row, copies of a cherry tree model are positioned on top of a rectangular, lossy dielectric slab that simulates the ground. The complete scattering model, considering soil and trees, enhanced by periodicity conditions corresponding to the array, was illuminated using a commercial computational software tool, which can simulate wave propagation. The simulated signal attenuation results are compared to radio path loss measurements taken in a cherry orchard, using the nodes of a wireless sensor network (WSN). The overall behavior of the predictions and measurements resemble each other; however the solver computes the maximum power that can be captured by the receiver antenna, and hence the predicted power is an upper bound of the apparently received power.
This study was carried out to evaluate the effect of water type on the performance of reverse osmosis system which was used for water desalination. Two type of water included well water (9.6 ds.m-1) and drainage water (4.25 ds.m-1) were used in this experiment. The feed flow rate was fixed at 4.8 m3/h and operating pressure was fixed at 13 bars. Productivity, Recovery ratio, specific energy and electrical conductivity and cucumber yields were measured in this experiment. Complete randomize block design (CRBD) with three replicates was used. Least significant differences (LSD) were used to compare the means of treatments at 0.05 probabilities. It was found that the use of drainage water ( EC = 4.25 ds.m-1) led to obtain higher productivity ( 3.04 m3 / h ) , higher recovery ratio (63.91% ) and higher rejection ratio ( 97.42 % ) and led to obtain lower specific energy ( 2.56 kW/m3) and lower electrical conductivity ( 0.109 ds.m-1 ) . There is no significant difference on productivity between plants which were irrigated by using desalinated water while the plants which were irrigated by using saline water ( well or drainage water ) were affected. Increasing in cucumber yield which irrigated by desalination water comparing with well and drainage water significantly.
In Japan, the percentage of contract culture in the vegetable productions has been increasing recently, and many producers are required for precise supply of the vegetable products just like industrial products. However, it is difficult to forecast accurately the vegetable production in open culture which is easily influenced by weather condition. Therefore, a vegetable production forecasting application based on the lettuce growth simulation model was developed to make accurate production forecasting and just-in-time shipments of the vegetable products possible.This application was developed as a Microsoft Excel file. It can acquire specific meteorological data from the online meteorological database (AMeDAS) and run a program of the lettuce growth simulation model. It calculates the harvest date and the yield amount in each planting field, and it estimates the amount of weekly vegetable production for the producer. By using outdoor time-lapse cameras in the planting fields, the growth simulation results can be corrected by the vegetation cover ratio of the plant image data. This application was applied to the local lettuce production on a trial basis. We confirmed that it could estimate the harvest date in each planting field with 80 to 90% accuracy.
That work aimed at the geoprocessing application in the hidrologic analysis and environmental of the Stream Duas Aguas watershed - Botucatu (SP) through the Geographical Information System - Selva, seeking to the preservation, rationalization of his use and environmental recovery. The watershed presents an area of 4007.19ha and it is located among the parallel ones 22o 43' 49" to 22o 49' 29" of latitude S and 48o 17' 53" to 48o 22' 03" of longitude W Gr. The results showed that the low value of the drainage density, they facilitate the infiltration of the water in the soil, reducing the superficial drainage and the erosion risk and of the environmental degradation, as well as the low value of the form factor (0.58) aided by the circular index (0.52) it indicates that the watershed tends to be more prolonged with smaller susceptible to the occurrence of inundations more accentuated, and consequently a tendency of smaller risk of the silting of the courses of water and of the environmental degradation of the drainage net.
The present work sought to the geotecnology use in the mapping of soil use in areas of APP's, allowing their delimitations and diagnosis of possible humane interventions. The watershed with 4286.15ha, locates among the geographical coordinates 22o 31' 52" to 22o 38' 20" of latitude S and 48o 33' 40" to 48o 38' 47" of longitude WGr. The used cartographic bases were the letter planialtimetric for the georreferencing of the image of satellite of 2011. SIG-IDRISI Selva was used in the supervised classification and the determination of the areas of the thematic map. The soil use showed that the culture of the sugar-cane occupies most of the area (81%), showing with that the predominance of the agricultural occupation in the area. The image and the use of SIG important tools were shown, supplying reliable results in a small interval of time. The obtained data will aid in the futures plannings of recovery of the area, because they made possible the verification that the area is not being preserved environmentally, link fact of presenting only 12.54% of forests, and the minimum demanded by the legislation of the Brazilian Forest Code effective is of 20%.
knowledge protected agricultural in soil sterilization area and determining the relation between the level of knowledge of vegetables farmers protection agricultural and each of independent factors , age ,agricultural experience , briefing of information sources ,participation in agricultural cycles ,number of green houses .In addition on diagnosis the important soil sterilization for vegetables crop .Protected agricultural in increasing production .The middle provinces were chosen to conduct this research, the ratio of %50 was taken from the following provinces(Baghdad , Babylon , Dayla , Karbala and Nagif ) stratified proportion random sample was chosen from each province with %11 from vegetable farmers ; the sample value reach (65) farmers . the measurement included (21)items to measure the level knowledge of vegetables farmers. The test included three areas , soil sun sterilization , soil evaporation sterilization ,and soil sterilization comical ; the research show of The research was amide , cognitive the level of vegetables farmers that was low knowledge level for vegetables farmers in soil sterilization area and that was relation between knowledge level of farmers with all independent variables , there search recommended that it is very important to increase the knowledge of vegetables farmers during participation in extension training specialist in soil sterilization area in addition to using extension activities that relation in soil sterilization .
This paper describes a novel monitoring system designed for orchid greenhouses. The proposed system provides important information on environment parameters related to orchid growth, such as temperature, humidity, and illumination. Based on wireless sensor networks (WSNs) the proposed system can monitor orchid greenhouses with high continuity and high frequency. With these benefits, the proposed system can discover the unbalance in temperature and humidity in a greenhouse. Through this system, orchid will grow in a well-controlled environment and the quality of orchid will increase. A dynamic routing and localization algorithm is also implemented in this system to manage a large amount of mobile sensor nodes to increase system robustness and scalability, and the lifetime of the proposed system is extended.
At the parcel scale, crop models such as STICS are powerful tools to study the effects of variable inputs such as management practices (e.g. nitrogen (N) fertilization). In combination with a weather generator, we propose a general methodology that allows studying the yield variability linked to climate uncertainty, in order to assess the best practices in applying fertilizers. Our study highlights that, using the usual practice of Belgian farmers, namely applying three doses of 60kgN/ha, the yield’s distribution presents the highest degree of asymmetry. This implies the highest probability to achieve yields superior to the mean. The computed return time of expected yield shows that 9 years out of 10, a grain yield of 7.26 tons.ha-1 could at least be achieved.
A practical bottleneck for efficient use of irrigation water is the proper use of irrigation controllers. These devices undertake the automated execution of irrigation schedules but need to be programmed periodically to adapt to weather conditions and crop development. In this context, the Irrigation Expert Simulator (IES) is a web-platform for training farmers and technicians in using irrigation controllers and promoting the adoption of good irrigation practices. With this tool, they can define very particular irrigation scenarios, propose irrigation strategies for them and see how their proposals compare with those of an expert. The tool is backed by an expert system that uses a collection of irrigation examples to provide recommendations and simulations of how a given irrigation regime would perform. The tool will be accessible from RuralCat (www.ruralcat.net), the portal for the agricultural sector in Catalonia.
Decreasing the variation of environmental parameters is a very important task for an automated plant factory. An uneven temperature distribution may hinder the growth of plants. Fans are usually added to reduce temperature variation. In traditional, devices in a plant factory are manually activated after sensors detect unusual readings. This method is time consuming and labor intensive. In recent years, wireless sensor networks (WSNs) have been applied to environmental monitoring. In this paper, we propose an automated fan system controlled by sensor nodes in a WSN. Sensor nodes can not only be used to measure the actual condition of a plant growing area, but also be connected with other devices in the plant factory. Compared to using a number of fans, the use of a servo motor is more effective, because it can push air flow into larger areas. The system proposed in this paper includes two parts: a fan and a servo motor. A sensor node is also employed in this proposed system to turn on the fan by using its microcontroller unit (MCU) chip to generate pulse-width modulation (PWM). When unusual readings are detected by the sensor node in the proposed system, this sensor node will generate proper PWM to make the servo motor turn to a right direction and then activate the fan. By using this proposed automated fan system, the variation of temperature is significantly reduced. The experimental results also indicate that plants can grow up much better in this well controlled environment.
Precision Agriculture techniques have been studied for Brazilian citrus to improve input use efficiency. Yet no study has approached the impact of variable rate application on energy efficiency and sustainability in these systems. This study aimed to understand how energy is used spatially in a citrus orchard and how variable rate fertilization influences energy efficiency. Two orange plot orchards were submitted to variable and fixed rate fertilization treatments in alternating rows. Georeferenced yield data was collected during two seasons to evaluate yield response to variable and fixed rate applications. Energy assessment was combined with Geographic Information System (GIS) to determine site specific energy indicators throughout the orchards. Energy and yield maps were analyzed to infer about energy efficiency and sustainability. Maps of nutrient energy embodiment reveled that energy performance varied spatially due to yield variation. Energy embodiment was higher in the fixed rate treatment, since it generally used higher quantity of fertilizer without raising fruit yield. Variable rate technology showed more efficient regarding energy use.
The wine industry is an important sector of the Italian economy, and is fed by environment primary inputs and contribute to energy resources demand. At the same time, the wine sector is one of the best identified components of Italian rural environment and agricultural landscape. The Italian Ministry for Environment, Land and sea launched in July 2011 a National pilot project to estimate the wine-sector sustainability performance, in collaboration with three research Centers of the University of Turin, Piacenza and Perugia. In this framework, to assess the sustainability of agronomic management of the vineyard an ICT tool that measures the environmental impact of pests, fertilization and soil management has been developed. Concerning the disease management, the tool uses a calculation procedure to assess the potential environmental risk of pesticides at the farm level. About fertilizers, the tool calculates the risk of damaging effects of the distribution of nitrogen, phosphorus and potassium as a function of the soil characteristics and needs of the vineyard and evaluates the effect of cultivation on the evolution of organic matter, based on the ratio between the quantity entered in the ground with fertilizers, cover crops and crop residues and the recommended levels. The use of agricultural machineries causes the compaction of soil and influences the activity of plants and of soil’s microflora. For this assessment, in the model are considered the values of rainfall, the percentage of surface covered by cover crops and vines, the machinery used and the number of steps per year. The water runoff is also evaluated, according to the type of soil, the agronomic management, the slope and the rainfall. The final evaluation relates the indicators calculated in different forms; for providing an overall judgment fuzzy logic is used. According to the traditional definition of sustainability which has environmental, economic, and social dimensions, socio-economic aspects have to be introduced in the sustainability assessment. For this reason a tool box kit, called “territory”, of qualitative indicators has been developed to include in the sustainability evaluation all aspects that make wine production one of the best identified component of Italian “culture” of rural environment and agricultural landscape management and protection, associated to food safety and consumer’s health. The tool box kit investigates the winegrowing farms on strategies, policies and measures adopted in the management of biodiversity, landscape, social aspects (field, winery and office workers, local community, consumers, suppliers) and economic aspects (territory and community investment). All the selected Indicators have been developed through multi-stakeholder processes, and those designated as “Core” are generally applicable Indicators and are assumed to be relevant for most of the national winegrowing farms. All farms have to pay off the “core” indicators to participate at the National project. The two indicators will be included, along with tools for the calculation of Carbon and Water footprint in a suite of assessment that will be available to all companies who wish to assess their own sustainability performance, on the website www.viticolturasostenibile.org.
To efficiently monitor large-scale greenhouses, gateways in monitoring systems are designed to manage sensor nodes in different subareas of a sensing field in order to acquire real-time sensing data. It is a challenge to maintain the whole monitoring system in the large-scale greenhouse. Electronic monitoring devices deployed in a greenhouse may fail due to a lack of energy. This paper proposes an automatic data backup mechanism for WSN gateways to recover the monitoring data of sensor nodes in the subareas where their gateways fail. Gateways with an automatic data backup mechanism will start a monitoring procedure in every new round based on a fixed schedule to exchange their working status packets. As a result, the lost monitoring data of sensor nodes caused by a failed gateway can automatically be restored, and the data completeness can be effectively improved and eventually extending the lifetime of large-scale monitoring WSN.
In recent years, precision agriculture (PA) has become an important issue in agriculture. Wireless sensor networks (WSNs) might be a great tool to monitor plant growth in greenhouses, because they can provide spatiotemporal sensing data converted from real world physical/analog signals with high-resolution. In Taiwan, there are many small contracting greenhouse producers who operate their businesses independently. Through the combination of WSNs and cloud computing, sensing data can be automatically recorded in an agricultural cloud. This new service aims to accumulate current and historical data to keep track of plant growth, helping farmers making more informed decisions. Farmers who use the service can benefit from detailed data on factors related to plant growth, such as soil moisture, leaf temperature, leaf width/length, temperature, and humidity. Cloud computing is an appropriate choice because it uses powerful computing servers and distributed resources shared by each measurement site to provide a smart service with useful information. Cloud computing applied to greenhouse monitoring will improve the efficiency of agricultural production and help conventional agriculture move toward PA. Researchers can also further analyze diverse data collected from different sites to provide important information/suggestions to farmers through such a cloud-based monitoring system. To promote the concept of PA, we propose a greenhouse monitoring system with an agriculture cloud. The proposed system collects environmental data from a greenhouse, and the data is stored in a database. A cloud computing service is provided to analyze the data. The proposed system is also able to send an alarm to users.
In this study, Geographic Information Systems techniques were applied to identify suitable area of land in Ibarapa Central Local Government Area in Oyo state, Nigeria for cassava cultivation and optimum production. Data acquisition include; geological map, use map and soil type map of Oyo state, and topography map of the study area for the purpose of identifying and classifying soil type, nutrients and moisture content, and also selecting slope and relief to reduce soil erosion that washed away top soil. The acquired data were converted into digital format for the purpose of georeferencing in GIS environment using ARCGIS 9.3. The database was created for different entities and their attributes, on this spatial analyzes were carried out that determine suitable soil SITE for cassava production. The result showed that Idere and part of Igbo-Ora is suitable for the cultivation and production of cassava.
Some factors, such as temperature and humidity, may have a large impact on crop growth. Recently, plant factory has become a new cultivation technique in agriculture, and all environmental parameters in plant factory are controlled thereby the crops can be stably supplied. However, uneven temperature distribution can be still found in plant factories, so additional sensor techniques, including wireless sensor networks should be employed to monitor the environment in plant factories. A large number of sensors densely deployed in a closed space may increase the chance of packet collision, causing data loss. With incomplete data, the variation in temperature may not be detected. In order to solve the problem of data loss, this study proposes a multi-channel mechanism to avoid the packet collision in a plant factory.
Agricultural production dominate occupation of most Nigerians and small holders farmers remain the bulk supplyers of food and fibre for her growing populace. Information and communication technology (ICT) in sustainable agriculture in Nigeria has a high potentials like any other part of the World. Agricultural Transformation Agenda (ATA) could be facilitated with mechanization and ICT package in agricultural production in Nigeria. ICT adoption level, challenges of e-agriculture in Nigeria and the ICT potentials were reviewed. Some of the phases of agricultural development were presented as sample modules with the view to demonstrate the practicability of ICT application in Nigeria agriculture. A public private partnership tractorization scheme (PPPTS) operation network and Input distribution network were showcased in the paper. Practical steps for e-agriculture in Nigeria and recommendations on pathway to successful ICT for sustainable agriculture in Nigeria were made and which will enhance the challenges of making agriculture profitable to the country poor farmers.
Hyperspectral Imaging (HSI), also known as “Chemical Imaging” or “Spectroscopic Imaging”, is a powerful technique combining traditional imaging processing and spectroscopic analysis to attain as well spatial as spectral information of an object simultaneously. Caused by improvements in spectrograph technology, new developments in detector designs, reduced costs and better handling of the hard- and software this technique has become increasingly applied in agricultural processes. Thus the count of HSI implementations in agro-food science increases rapidly over the last ten years. The most applied processes of HSI are in field of the food production chain under indoor conditions - determining to quality control of vegetable, fruit, grain, meat and poultry products. In this paper the authors applied a near infrared HSI system for cleaning control of sugar beet directly on a harvesting machine on the field. This is a complete new challenge cause measuring under field conditions during the harvesting process. In this article the potential of this application of HSI for quality monitoring of the sugar beet harvesting process is presented and analyzed
Harvest in hop production takes place in late summer. The hop wines together with the supporting wire cut or pulled from the overhead cables of the trellis system, loaded on to a trailer and transported to a static picking machine. Harvesting on the traditional picking machines implies manual putting of each individual vine into a clamp which pulls the vines into the picking machine. This work is very labour-intensive, with a high risk of injury and considering the ergonomics unfavourable. The Bavarian State Research Center for Agriculture and the company Fuß started 2011 a cooperation project in which a novel prototype of a system for automatic picking based on the preliminary work of the company was developed and tested. Main idea is to replace the manual placement of the vines into the clamps with fully automated feeding of the picking machine. The first prototype of the system consists of a conveyer, a cutting subsystem including a pre-picking unit and transport conveyer with a pre-separator for cones for transporting the cut hop vines into the picking machine for further processing. In this paper the concept, methods which were used during the development and preliminary test results of the system will be described and presented.
The recently developed multidisciplinary methodology is based on our Direct Computer Mapping based simulator, combined with a Multi-objective Genetic Algorithm. This paper focuses on the conceptual framework of this dynamic simulation based tool, through the example of Lake Balaton and its Southern catchment basin. The objective is to manage sustainable and reasonable land use by the investigation of various scenarios, considering the preferences of various interest groups. The coherence of the model is given by the dynamic network of water flows and reservoirs. The completeness is solved by the complete and disjoint covering of the whole area by modeled patches, corresponding to the typical parts of natural and human built environment, associated with typical partial interests. The complexity of the large scale and long term process is managed by evaluating detailed models only for one representative patch from each class, while the calculation and assessment of the similar patches is solved by simple multiplication rules. Automatic and impersonal development of scenarios is realized by a multi-objective evaluation feedback over the possibility space of the human controlled characteristics, supporting the computational analysis of the conflict between the interests. First experiences proved that the developed multiscale methodology is flexible enough for the continuous development of the multidisciplinary models, which can support the multicriteria decision making for the agricultural and natural resource management.
Precision Fruticulture addresses site or tree adapted crop management. As a prerequisite, spatially organized data are needed that might include orchard topography and information on the plant water status. In the present study, the influences of terrain elevation, soil electric conductivity, and apparent plant water status on yield parameters were studied in plum trees (Prunus domestica 'Tophit plus'/Wavit).
It is important to know the origin of the wood chip and to verify the whole transport chain, from the forest to the processing plant. This can be done using electronic customized devices to monitor the entire process: these technologies, already used in other fields, are based on the transmission of GPS data via GPRS-UMTS-HSDPA connection. In the wood chip supply chain application they must be adapted to the context, properly tailored to interface with the electronics onboard the machine and to generate usable arrays of data, including performance and quality. In this work the entire chain is controlled by means of a novel electronic architecture onboard the machine, interfaced with a communication system connected to a central server acting as a supervisor. All the machines are equipped with a GPS receiver, a data communication module and a CAN (SAE J1939) interface: machines data are sent to a central server, through an internet connection, and collected in a database ready for web services. A communication protocol has been designed to optimize data transfer and to minimize the cost. To increase the product value, an automated integral sensor (capacitive type) for wood chip humidity determination was implemented. With the fleet management system installed on the machine, cruise controls data (using a GPS system) are acquired, other than all the machine states (through CAN line inside the machine) and wood humidity. The data base (MySQL standard) permits, moreover, to the system administrator and to the user to manage all these information. Another important result is the web access that permits to monitor the fleet situation (route, engine status, time of journey, climatic conditions) at any moment with a screenshot. The capacitive sensor for humidity measurements gives good results, especially in the case of chips with dimensions comprised between 34 and 64 mm and an initial humidity (on wet basis) of 45%.
The influence of vibration forces and cushioning materials on the quality and dynamic behavior of fresh apple fruits was investigated. Fruits were exposed to random excitation( is excited by combination of single- sinusoidal signal and a broad band stochastic single and compared to pure stochastic excitation) by using robust techniques EFDD enhanced frequency domain to harmonic excitation. Six vibration modes were identified in the frequency range of (0- 1.6 KHz) by two techniques FDD & EFDD. The paper- wrap and foam-net cushioning materials interaction is also studied. Damage identification technique has been applied to determine the integrity of the structure. Increasing vibration frequencies within the range encountered during transport caused an increase in damage percent from apple fruit and a decrease in shelf life. Damping ratios were greater at package with foam-net cushioning materials comparing package with paper- wrap and package without cushioning materials. Results from test showed the range of resonance frequency of apple fruit is important when transporting without cushioning material, a higher starting resonance is an indication of a stiffer apple bottom, the cushioning material moves resonance frequency compared without cushioning material. And Packaging fruit by cushioning material may move the natural frequencies of the fruit out range of that the transport vehicle resulting in reduced resonant vibration and vibration bruising for fruit.
Wheat is a strategic crop which is considered to be one of the most important agricultural products. Harvest Loss is a type of loss that decreases final production performance. Combine harvester loss is divided to several losses; natural loss, header loss, threshing loss, separation loss and quality loss. The major loss is attributed to header loss. Combine harvester header loss is the consequence of cutter bar strokes, height of the reel, reel peripheral speed, travel speed, width of harvest, height of cutting, crop moisture, height and density of crop, feed rate of the crop and etc. Mathematical modeling of the combine harvester is the initial step to retrofit the performance of the combine harvester. Dimensional analysis is a method that uses effective variables and forms several dimensionless equations to evaluate the issue. The variables are changed to dimensionless equations and this reduces the number of variables. Accordingly, the numbers of required experiments to determine relationship between variables are decreased. This research has developed a model using combination of theoretical combination method (dimensional analysis) and practical phase (field experiments). This method uses most of the elements that have effect on loss. There were π-terms developed out of the effective elements, and the experiments were designed based on these pi-terms. Complete randomized block design was used in practical experiments. All the experiments were done in Pars-Abad with CLAAS combine harvester. Increasing travel speed in a defined range decreased header loss. Height of cut should be optimized because of some reciprocating reasons. The obtained data in analysis stage, verified the model with relatively high (76%) correlation coefficient
To perform climate change impacts studies on the crop irrigation requirements is necessary to use climate change scenarios data produced by regional climate models, which are distributed in space and have long data series (e.g. 30 years) relative to several climatic variables. It is also necessary to take into account observed meteorological data recorded in weather stations networks, to characterize the baseline scenario and to correct the bias of the climate models data. Thus, to handle large amounts of spatial distributed data it is necessary to create a geospatial database to properly manage such volumes of data. For this purpose, georeferenced data relative to soils, crops and climate (observed climate data from weather stations and climate change scenarios) must be integrated into a GIS database. On this study a GIS application, namely GISClimReg, was developed in order to: i) perform spatial analysis on climate change scenarios data; ii) produce automatically digital maps of the most relevant climatic variables; iii) integrate the irrigation simulation models with the GIS database allowing the quantification of crop water requirements at a regional scale. The regional climate models considered on this study were: the HadRM3P (scenarios A2 and B2) with a spatial resolution of 50 km, the HIRHAMh (scenario A2) with a resolution of 25 km and the HIRHAMhh (scenario A2) with a spatial resolution of 12 km. The climate models data correspond to the 2071-2100 period and were obtained from the PRUDENCE project. These data sets were complemented with observed meteorological information from SAGRA weather stations network, located in the Alentejo region (south of Portugal). GISClimReg is able to operate over several files containing meteorological data (including the RCM models output and the weather stations data) and to automate spatial interpolation of meteorological variables. Interpolated grids resulting from that interpolation can be converted into a regularly spaced grid of 10 km resolution, creating a kind of virtual meteorological network, were the soil water balance model can run to calculate the crop water requirements for the several climate change scenarios considered. As a result, the crop water requirements maps produced for the study region enable the assessment of the climate change impacts over the crop irrigation requirements at a regional level.
AgroClimate is a web-based system developed to help the agricultural industry in the southeastern USA to reduce risks associated with climate variability. It includes climate related information and dynamic application tools that interact with a climate and crop database system. Information available includes seasonal climate monitoring and forecasts combined with risk management tools for a range of crops, forestry, pasture, and livestock. More recently it has been expanded to include decision-aids based on real time weather monitoring and short-term weather forecast. This expansion prompted the development and adaptation of existing tools to mobile phones. Decisions targeted for mobile phone applications are related to application of fungicides in high value crops such as strawberry and citrus, irrigation scheduling, and tracking of growing degreedays and accumulation of chill hours.
Precision Agriculture (PA) Information Systems improve farm management helping to make the best decisions based on all available information, keeping, controlling, and optimizing resources, returns, and preserving the environment. These systems need to archive, retrieve, and process large amounts of data from many different farms for future analyses. It has to be done without neglecting aspects of entity-relationship model (ER model) at the same time describing all crop cycle’s stages. With minor changes in the database schema, the performance of geospatial queries can be improved by refactoring tasks in the literature related to Agile Software Development. A refactoring represents structural, architectural, integrity or data quality change that preserves the system functionalities. As a case study, a PA Information Portal System database that dynamically generates models based on input data was created to represent the relations of input data generated for a Spatial Data Infrastructure used in a PA. In this context, we redesigned this database introducing refactoring techniques in order to improve PA queries performance.
Agri-Food Supply Chain Networks (AFSCNs) must increase production while reducing environmental impact. In these networks farms, as the main producing actor, adapt their production processes to meet these demands (e.g. by precision agriculture, precision livestock farming and precision horticulture). This leads to a more information-intensive agriculture that needs to be supported by state-of-the-art (software) tools. Currently, the available state-of-the-art tools, used for arable farming, cannot be integrated sufficiently, hindering adoption. Problems, related to integration and adoption, are identified and different projects are developing improved (software) tools that aim at enabling enterprise integration and business to business collaboration in AFSCNs. In these projects ad-hoc frameworks are used to develop these (software) tools. However, these frameworks are not aligned, which can result in (software) tools that are still not sufficiently integrated. This paper proposes to design a generic integration framework that can facilitate the design of project-specific frameworks in order to improve the integrating capabilities of state-of-the-art (software) tools. A structure of an integration framework is presented that is based on specific frameworks developed in three software development projects, which are selected as case studies. This structure can be used to design a generic integration framework. Such a generic framework supports the creation of specific frameworks.
The dehydration of grapes to make wine, in controlled environment and with variance in temperature and humidity, began to be studied with greater emphasis recently for some grape varieties, due to the proven effects of the highest concentration of phenolic compounds and decreased the amount of water in the wort. Physiological standpoint of increasing the phenolic compounds is beneficial due to its antioxidant and anti inflammatory, and make an important role in the quality of wines. Postharvest dehydration in order to adequate levels of sugar, resulting in constant changes after harvest, note a positive development in the wine and grape flavor. The aim of this study was to evaluate postharvest changes in grapes after partial dehydration in a controlled environment. The grapes used were the kind of Shiraz, grown in the city of São João da Boa Vista, São Paulo, the drying process was adapted into a cold chamber for the drying process and a forced air tunnel to form a fixed bed flow of air perpendicular. To obtain the desired temperature is installed a set of finned RTDs nominal power of 2400 W, a system controlled by PWM (pulse width modulation). Treatments consisted of a control (initial condition) and the combination of dehydration temperature (37.1 C) and air velocity (1.79 ms-1). To analyze the final quality of the analyzed concentration of soluble solids (Brix) and concentration of phenolic compounds (gallic acid mg per 100 g of must). Statistical analysis was performed by applying an ANOVA followed by Tukey's test for comparison of means. The treatment cause a significant increase in the concentration of phenolic compounds, which indicates the effectiveness of the method and since the concentration of polyphenols is an indicator of quality wines and to produce this compound also has a great importance to health. The soluble solids were not different after dehydration (increase of 0.20 ° Brix), this may be due to the late harvest product causing potential is reached sugars. It can be concluded that there were physical and chemical changes in the product subjected to dehydration and they showed their beneficial from the point of view of winemaking
Information resources representation and retrieval through meta knowledge is addressed in this paper. We present our work towards information resources characterization and associated software retrieval related to forest and forestry. One aim is the enhancement of the resource descriptors by allowing users to help define new search terms. This approach will contribute to the knowledge engineers’ understanding of how users desire to search information based on concepts relevant to them.
The Geographic information systems (GIS) has function to support in making decision and define the location and area of land as an effort to develop specific bioenergy biofuel from palm oil plants and diversification of agriculture to support food security. The Plantation area of palm oil and paddy fields are inversely decreased in national and local level. The interpretation of design in using land has been change with natural resources that include natural resources forestry and natural resources for land plantations, rice fields and other different use in community. The capacity in one area is a component to supportanalysis of natural resources. The arearesources were calculated due to degradation of land resources into description useof the land. Result of the study reveals an analysis of food-carrying capacity of land in each region has surplus food consists of Indragiri Hilir, RokanHulu, adequatefood consists Indragiri Hulu, Pelalawan, RokanHilir, scarcefood consists KuantanSingingi, Siak, Kampar, Bengkalis, Meranti, Pekanbaru, Dumai based on extensive comparison plantations producing bioenergy and land use in agricultural production of food. The capacity conditions of land for bioenergy developed surplus energy consists of Indragiri Hilir, Pelalawan, Siak, Kampar, Rokan Hulu, adequateenergy condition consists of Kuantan Singingi, Indragiri Hulu, Bengkalis, Rokan Hilir and scarceenergy conditions consisted of Meranti Islands, Pekanbaru and Dumai.
Since the introduction of the Veris Mobile Sensor Platform (MSP) pH Manager it has become possible to sample fields for soil pH with a sampling density of more than 15 samples ha-1. With this, the density of information increases greatly and small-scale pH heterogeneities can be recorded that remained undiscovered in conventional sampling methods. The optimal distribution of lime leads less to a saving of fertiliser but instead to the expectation of positive agronomic effects, such as an increase in yield. In three fields a comparison was made between high resolution and conventional soil sampling. In this the expected agronomic effects were simulated from results from other trials for a rotation period of six years. The economic evaluation of the comparison shows that a potential of ca. 20 € ha-1 y-1 remains through the much higher density of information using the Veris-MSP.
Sustainable use of irrigation requires delivering the optimum amount of water according to weather conditions and the status of trees and soil. Diverse existing technologies can be used in this topic but practical application in commercial orchards is limited by the lack of an integrated system. Within this context, EFFIDRIP provides a tool kit for cost-effective services in automated supervision and control of localized irrigation. The central part is a web-based application that monitors the crop through a wireless sensor network, uses meteorological data, and adjusts the forthcoming irrigation schedules without the need of user intervention. Compared to existing decision support systems, EFFIDRIP takes the next steps in automating irrigation control. First, it integrates commercial equipment deployed in the field, i.e. soil or plant sensors and irrigation controllers, to a higher level system. Second, it makes autonomous operative decisions and communicates machine-to-machine with the diverse components based on information and communication technologies. The system is being evaluated at three test sites (Portugal, Greece, Spain) in terms of improving water and fertilizer use efficiencies without impairing yield. Labour effort and the capacity to detect and cope with incidences are also analysed.
The Province of Bolzano (Italian alpine area) has a density of people and animals comparable to other regions of Northern Italy. Anyhow, due to the special nature of its mountainous lands, there are potentially-critical situations to be monitored: (i) the anthropic and animal pressure is considerable on valleys, where the population concentrates; (ii) there are few lands for spreading animal slurry according to environmentally-sustainable strategies (i.e., limiting N-rate). Therefore, an integrated system for monitoring the N-rates spread on the territory is proposed. Analogous systems were recently experienced in other Italian regions where specific research projects proposed solutions to monitor the production and distribution of slurry from intensive breeding and to automatically compile field-activity registers, in accordance with current regulations. The system presented here also foresees tools for managing grazing systems through virtual fences (GNSS-equipped collars).
The TRAKTnet.one project of the Free University of Bolzano aims to identify and develop new solutions to remotely monitor the efficiency of farm-tractors engines included in a local voluntary network all along their lifespan. The knowledge of tractors’ efficiency can give important information concerning machines’ consumption, emissions and need for servicing, thus contributing to a more environmentally-sustainable agriculture. Engines will be monitored by measuring rpms, exhaust gases’ temperature and oxygen content (as indexes indirectly estimating consumption and efficiency) and then analysing and inferring the data through procedures, which algorithms will be an integral part of the project’s results. This implies the existence of a service centre controlling all farm machines and managing a Farm-Information-Systems network through simple logical connections according to a client-server approach. The final outcome of the project is expected to be an automatic system, based on an inference software-engine able to correctly interpreting the sensors outputs. The advantage of this proposal is to exploit a farm monitoring network, previously designed for managing the information related to the automatic compilation of records in the country, by simply equipping data loggers with two additional sensors.
A new methodology for monitoring the performance of forest chain was here proposed and described. The target of this methodology is to develop a system to analyse operational time monitoring. The aim of this study is to propose an innovative and standardized approach of Precision Forestry in the use of GNSS for performance and productivity relief. GNSS is used as an integrated tool for measuring the efficiency of the forest mechanisation chain. So far, these surveys have been carried out through the application of GNSS only for logging operations. The validation data has been done through the comparison with a clock time relief. The preliminary overview about the application of this approach on harvesting operations has permitted to assess a good feasibility of the use of GNSS in the relief of operative times in high mechanised forest chain. Results showed an easy and completely identification of the different operative cycles and elementary operations phases, with a maximum difference between the two methodologies of 11.49%.
A reference model is proposed for management zone delineation. The results showed that although there are differences in the steps used by each author, some are recurrent. Yet, steps not considered can have a strong impact on the maps obtained. This study is also useful as a reference document for standardization in management zone delineation, and can be used as a guide to choose the right tools, right data and methods, allowing the optimization of the management zone delineation and improving the quality of the maps obtained. The use of Business Process Model and Notation (BPMN) showed to be adequate to represent the steps, their flows and the decisions to be made along the process.
The objective was to assess the chemical composition of biogas obtained in batch biodigesters from manure of broilers fed a diet with probiotic and exogenous enzymes. In a completely randomized design, the study included 4 treatments with manure from broilers (Cobb®), ages between 43 and 48 days, raised in cages, and fed different diets: a negative control (NC, control diet without feed additives); probiotic (PRO, the NC diet + 500 ppm of a product containing Bacillus subtilis); exogenous enzymes blend (ENZ, the NC diet + 20 ppm phytase+200 ppm protease+200 ppm xylanase); and a treatment combining both feed additives in the NC diet (P+E). Each treatment had 4 replicates in the batch biodigester. The manure was collected, identified and prepared (4% total solids). The volume per batch was the same (1.8 kg) for all biodigesters, with manure (0.301 kg) + water (1.499 kg). The vertical displacement of the gasometers was measured daily and the values were multiplied by their internal transversal section (0.00785 m2) to determine the biogas volume accumulated in 142 days. The gasometers were reset after each reading using the discharge valve. The biogas volume was corrected for 1 atm and 20°C. The biogas composition analyses were performed every week to determine the amounts of methane (CH4) and carbon dioxide (CO2), using a Finnigan GC-2001 gas chromatograph equipped with Porapak Q and Molecular Sieve columns, as well as a thermal conductivity detector. The results were given as cubic meters (m3) and percentage of CH4, CO2 and other gases that were produced. The data underwent variance analysis employing the General Linear Model procedure using the SAS® software. The data underwent variance analysis employing the General Linear Model procedure using the SAS® software. Averages were then compared by the Tukey test with a significance level of 5%. It was found that there was no statistical difference (P<0.05) between the treatments as to the production of CH4, CO2 and other gases. The treatments with additives (PRO, ENZ and E+P) resulted in a gas production (CH4, CO2 and others) that was statistically similar to that of birds fed the NC diet. The poultry manure produced an excellent amount of CH4 in relation to the other gases (NC-80.04; PRO-80.79; ENZ-81.30; P+E-79.29). It can be concluded that additives included in the diets for birds do not interfere with CH4 production, a gas essential for clean energy production.
Agricultural Crop Field Modelling is a technique that uses georeferenced data points of soil information analysis or spectral remote sensing imagery raster layers to obtain models to: identify spatial differences in the regions; maximize the production, minimize the nutrient reposition; and find the desired characteristics in terrain based on class of production selected. Concepts related to Object Based Image Analysis were adopted to generate a meaningful Management Zone delineation aim the construction of models based on a multi source georeferenced data fusion, building a concrete relationship among different input of information layers employed using the Multiresolution region-based segmentation algorithm.
Farmers need problem identifying alerts delivered timely and personalised. Using smartphones as platform (35% of Danish farmers use a smartphone) utilising micro blogging tools, Twitter and Vine are able to fulfil this need. Advisers in the Danish agricultural extension systems are instructed and encouraged to start using Twitter and Vine. To lower the entrance barrier, they are offered a common account, so they can start tweeting without the hassle of creating their own account. Work was done to find appropriate hashtags and to emphasise the importance of using these so targeted and personalised tweets can be embedded on websites. Preliminary results indicate that we will see a steep increase in uptake of this new way of disseminating alerts.
To ensure successful spatially differentiated fertilization, it is necessary to find a section of the field where the crop differs in appearance from that with optimal characteristics, determine the nutrient whose deficiency impaired the quality of plants in that section, evaluate the expedience of additional fertilization and calculate the amount of fertilizers needed in every individual section. Most publications on this subject are devoted to revealing crops with nitrogen deficiency while very few of them consider optical symptoms of other nutrients shortage. The aim of the present work was to study specific and nonspecific changes in optical properties and the possibility of their employment for detecting plants suffering from nitrogen, phosphorus or potassium deficiency. It was found that unbalanced mineral nutrition not only increases leaf reflectance but also induces changes in the structure of reflected radiation spectra. Appearance maximum and minimum values in reflectance spectra derivatives observed in conditions of N, P and K deficiency indicates nonspecific response of plants to nutrient shortage. As has been shown, specific changes also take place under the deficiency of each of the nutrients against a background of nonspecific ones.
This paper describes the objectives and final results of the STRATOS project (System for TRAcTOrs’ autonomous OperationS), within the framework of ICT-AGRI ERA-NET (Coordination of European Research within ICT and Robotics in Agriculture and related Environmental Issues). The main objective of the STRATOS project was the development of an open ICT hardware-software infrastructure enabling the acquisition of geo-referenced information on soil and terrain parameters. In more detail, STRATOS project target was to develop and demonstrate new functions enabled by ISOBUS technology (ISO 11783) that support a substantial improvement of the quality of the farming jobs. In particular the idea is to develop a technology based on ISOBUS compliant, wireless self-powered sensor network for the real time measurement of soil and harvester conditions. In this way, Task Controller (an ICT component defined by ISOBUS specification which supervises actively the farming job performed by the tractor) can optimize the whole tractor and implement operational modes to improve the farming job quality and safety of the overall systems. The project lasted from 1st April, 2011 to31st March, 2013, and this paper reports about the project achievements
This paper conducts a socio-economic evaluation of climate risks on crop production in Hungary, using panel data models. The country has a special location in the Carpathian basin. The spatial distribution of the precipitation is highly varied, from humid conditions in the western part to semiarid conditions over the eastern regions. Under the current conditions crop systems are mainly rainfed and water licenses are completely underexploited. The potential future climatic conditions were examined based on the RegCM3 model with A1B scenario, and compared to last ten years (2002-2011), which was a warm period. Results show, that in the near future (2021-2050) most of the crops examined could have the same or better climatic conditions, while at the end of the century (2071-2100) lower yields are expected.
Although standardisation of data exchange formats and protocols in agriculture has made considerable progress during the last few years, achieving interoperability for information integration in IT systems in the agrifood sector is still seen as a challenge. Traditional ways of agreeing on interfaces by long and elaborate discussions in standardisation committees probably will not be able to cope anymore with demands from a more and more networked world and faster changes to requirements in the future. Novel ways are needed to enable at least to a certain degree automatic interface negotiations. Semantic technologies are one of the building blocks within such a framework. The authors present methods used, potential benefits in facilitating interoperability and experiences gained in implementing a semantic layer on top of the agroXML standard.
Farmer in modern society is facing with a lot of paperwork that is extending their work and reduced efficiency. In addition to that, they often lack in a comprehensive view over farm which leads to smaller decision-making capability By developing a comprehensive software solution that offers automatic accounting, animal traceability, FADN and VAT reporting, we are trying to offer a comprehensive overview of the farm where farmer could only focus on farm relevant information and at the same time prepare a relevant information for accountant in the background. This could improve their efficiency and give better results without large investments.
Shape and further geometric characteristics of agricultural parcels are main factors with respect to machinability, working time requirement, and arising costs for cultivating agricultural acreages. Due to missing comprehensive statistical information on existing agricultural field structures regarding shape and ergonomically relevant geometric prop-erties, most ergonomic simulations are based on simplified assumptions and therefore admit only limited information about real conditions. In this context this research pro-ject focuses on the development of methods for a comprehensive classification, charac-terization, and statistical description of ergonomically relevant geometrical properties of existing agricultural parcels on a large scale. Results gained provide basic information for continuative research in the fields of ergonomic simulations and agricultural engi-neering.
The main objective of the study was to determine the actual precision of the AutoTrac Guidance System according to different correction signals proposed in Belgium by John Deere: StarFire 1 (SF1), StarFire 2 (SF2) and RTK. The second objective was to observe the evolution of this precision in function of the return time between two passes in the field. Finally, the study aimed at fixing the limits of use of each correction signal. A theoretical case (specific tool especially designed for the trials) and a practical case (precision seeder for sugar beet) were studied on a tractor John Deere 6830 fully equipped. The observed precision of the correction signals was equal or better than the one announced by the manufacturer
The Youth Mediated Communication (YMC) model is an idea to transfer knowledge to illiterate parents through their children educated at school. In this study, the model was applied to extend agricultural knowledge in rural Asia where farmers tend to use too much chemicals because of their poor knowledge. And such excess use of chemicals is now terrifying the sustainability of agriculture and even their life there. The model was combined with an idea of youth sensors that children work as field sensors, measuring meteorological conditions as well as crop conditions. A Q&A software package was implemented for the children to interact with remote experts through the Internet. The children transfer the queries given by their parents to the expert using the software and receive the answers from the experts. Then, they explain their parents about the answers. The field data collected by the children were used by the experts to provide advices to each of the farmers. We had a test bed in a village in the heart of Mekong Delta in Vietnam and trials were carried out for two cropping seasons from 2011 to 2013 where 29 and 15 families participated in the first trial and the second trials respectively. We concluded the mechanism functioned well in terms of providing illiterate farmers proper knowledge though we still need additional trials to accumulate data for the evaluation of its effectiveness. The youth sensors were very helpful for the experts to understand the truth in the fields of each farmer and to provide optimal advices. The data can be also used as the ground truth to calibrate the satellite based estimation and down-scaling meteorological data.
A daily climate dataset was developed (1961–2100) for scenarios SRES A1B and A2 using a statistical downscaling model and data that included the CGCM3 model outputs, NCEP reanalysis data, and SDP observation data. The climate data obtained were used as inputs for a crop yield model in order to estimate the present (2007–2011) and future (2071–2100) rice yield, transpiration, and irrigation requirements of a paddy field in Matsuyama city, Ehime prefecture, and to also assess the climate change impact on its rice yield and water balance. The results show that the yield increased by over 30% in both scenarios under high CO2 concentrations, while the transpiration rate from the rice plants decreased by 12%. The future irrigation water requirement increased by 28% for A1B and by 36% for A2, indicating a need to significantly increase water intake from rivers.
The purpose of this study was to evaluate climate change vulnerability over the agricultural infrastructure in terms of flood and drought using principal component analysis. Vulnerability was assessed using vulnerability resilience index (VRI), which combines climate exposure, sensitivity, and adaptive capacity. Ten flood proxy variables and six drought proxy variables for the vulnerability assessment were selected by opinions of researchers and experts. The statistical data on 16 proxy variables for the local governments were collected. To identify major variables and to explain the trend in whole data set, principal component analysis (PCA) was conducted. The result of PCA showed that the first 3 principal components explained approximately 83% and 89% of the total variance for the flood and drought, respectively. VRI assessment for the local governments based on the PCA results indicated that provinces where having the relatively large cultivation areas were categorized as vulnerable to climate change.
ArcGIS software was used for individualization of landform morphographic heterogeneity in five (5) different mountainous broadleaf forest areas from Basilicata region, located in South Italy. Regional hydrogeological risk was based on defence plan for hydrogeological risk (Watershed Authority of Basilicata Region). It was considered as good prediction feature of landform morphographic heterogeneity for timber harvesting operations and new forest road construction for timber extraction. Orographic characteristics, such as slope, watershed systems features, and other natural obstacles were considered. The regional law and forest management plans as constraints for timber extraction were also considered. The analysis allowed identifying forest areas with high landform morphographic heterogeneity, and orographic or watershed restrictions to be considered in the planning and timber extraction optimization. This methodological approach should be tested in other mountainous forest regions subjected to slope instability.
In the Interreg IV, EU project 'The healthy greenhouse' a new integral crop protection system is developed. Part of the project is the development of autonomous robots for monitoring individual plants. One of the sensors for monitoring is an applicationspecific multispectral camera for detection of fungal diseases. In this paper the development of this camera is described, starting from a laboratory based hyperspectral system. Using feature selection the number of bands is reduced to eight. Results from the analysis of the reduced images show that 90% of the pixels are properly classified. These bands will be validated in a fast filter wheel multispectral system in the greenhouse. Final goal of the project is real-time multispectral camera using micro patterned coatings on individual pixels.
Overexploitation of scarce water resources for irrigation agriculture is a key problem impeding a sustainable development in the extremely arid Tarim Basin in China's Xinjiang province. Therefore the SuMaRiO (Sustainable Management of River Oases along the Tarim River) project develops a Decision Support System (DSS) for integrated land and water resource management. To ensure credibility, relevance and acceptance of the DSS an inter- and transdisciplinary research approach is applied that includes local stakeholders’ knowledge, perception, and preferences from the beginning of the project. The DSS-sub-models which are linked within the DSS include hydrological models (WASA, SWIM, and MIKE BASIN), quantifying discharge and irrigation water availability, bio-geophysical models (EPIC, APSIM), determining crop yields and actual crop water use, and farm optimization models (Linear programming), deciding farmers’ current and future cropping pattern. Furthermore the response of riparian forests along the river, on changes in groundwater level and flooding events is determined by self-developed empirical models. The actual land and water management measures that can be simulated through the DSS comprise improvement of water transmission and storage infrastructure, restriction of agricultural land expansion, improvement of agricultural extension service, subsidization of advanced irrigation technology and others. Specific ecosystem service (ESS) indicators enable the DSS-user to judge the impact of potential water and land resource management measures under a range of future climate and consecutive river discharge scenarios. Socio-economic scenarios define future developments of agricultural input and output prices, which directly enter the farm optimization model. The ESS indicators are then determined for every sub-region annually until 2030 and include among others the status of natural riparian ecosystems, farmers’ income, production amount of food, feed and fiber, as well as ground and surface water status.
A research project, “Climatic Changes and the Evaluation of Their Effects on Agriculture in the Asian Monsoon Region (CAAM)” is progressing. The purposes of this project are to improve the reliability of climate prediction, and to develop the necessary information platform to design adaptation and mitigation strategies in agriculture against the predicted climatic changes in the Asia monsoon region. Sixty percent or more of the world’s population lives in the Asia monsoon region, and the effects of the predicted climate changes on the region are expected to be quite serious, since most of the countries in the region are agrarian. Our team’s central goal is to elucidate the effects of climatic changes on major crops in the Asian monsoon region by constructing an evaluation system using meteorological data and crop models. In particular, we take charge of development of a system that can simulate the cultivation under various conditions (e.g., cultivar, weather, and management).We first surveyed the major crop models in Thailand to decide which crop model to adopt for the system. We found that the Decision Support System for Agrotechnology Transfer (DSSAT) was applied to several crops in Thailand. Next, we developed a prototype system to optimize the double cropping of rice and cassava in Thailand. This system was implemented using the Java Agricultural Model Framework (JAMF), and includes rice and cassava module of the DSSAT. As the input data for the system, solar radiation, air temperature and precipitation of 0.05 degree grid data in northeastern Thailand were prepared. This data was generated from actual data using a space interpolation method developed by Japan’s National Institute for Agro-Environmental Sciences. Each crop model was executed 365 times while the transplanting date was moved by one day each time, and the maximum yield of each crop was saved in XML files and displayed on Google Earth. The results of this system cannot be discussed yet because there are no local field data to compare and to verify the results. The comparison and verification between the results and the observation data are tasks for the coming years. The field data will be prepared by the cooperating institutes.
We developed a quantitative color appearance evaluation method of crops and agricultural products using a digital camera. By analyzing the relationship between the color appearances of the images of a standard color chart with the plain Red, Green, and Blue color sections taken under the various natural lighting conditions and the illuminating spectral information, the photosensitive characteristics of the digital camera were experimentally studied. In addition, the color parameters of the Red, Green, and Blue sections on the virtual standard color chart calculated using the two parameters of a power function with the natural lighting spectral information consistently agreed with those of the standard image taken in the standard color acquisition system. Furthermore, the color calibration for the tomato fruit images taken under the natural lighting using the evaluated color parameters of the virtual color chart was performed. The developed color calibration method showed very successful results as well as the conventional calibration results. Consequently, these results suggested that the surface color images of the agricultural products which have the dynamic color distribution and the complicated geometrical structure could be evaluated based on the irradiance information of the natural lighting.
One of the main challenges for today‟s agriculture is to increase drastically the production while at the same time being more sustainable. Innovation is seen in Europe as the key solution and ICT have a great potential to boost innovation in agriculture. As the complexity of the innovation process still remains difficult to manage, an experimental Public-Private Partnerships Action of the ICT AGRI Era-net was launched and is presented in this paper. This one-year action aimed to gather together all the players involved at the European level for crop protection and to boost concrete innovation in ICT to reduce the use of pesticides, especially around a unified platform of information and services. The main conclusions of this study, especially on the method tested, are presented in this paper and some recommendations are made for next innovation management actions.
The Agricultural Research Council – Research Centre for Agrobiology and Pedology (CRA-ABP), has for many years developed soil survey, mapping, and informatization methodologies. Several thousands of soil observations have been stored on a Ms Access database. Climatic variables relevant for soil evaluation and management were also collected and stored. This Information System was the starting point to develop a web- GIS application for online Italian soil data consultation. This paper outlines the design and development of a prototype web-GIS for use in the fields of agriculture, agroindustry, food, fishery and forestry.
The no-tillage system (NTS) represents an important technological advance in agriculture generating economic and environmental benefits. However, there is a new orientation of academic interest in issues related to the environment and sustainable development in several areas regarding the NTS. Our aim was thus to perform an overview analysis of academic publications about this system and their focuses. The method adopted was a bibliometric survey at the Web of Science database. The 500 most cited articles on the Web of Science database published between 2006 and 2011 were chosen and lexical and multiple correspondence analyses with the most frequent words in title, abstract and keyword fields were made. The results suggest that there is a strong emphasis on no-tillage publications on environmental issues, such as carbon sequestration and greenhouse gas emissions.
Within the knowledge-based bio-economy, information sharing is an important issue. In agri-food business, this is a complex issue because many aspects and dimensions play a role. An installed base of information systems lack standardisation, which hampers efficient exchange of information. The objective of this paper is to presented a Strategic Research Agenda (SRA) of AgriXchange project, which reflects the business demands for utilisation of ICT and exchange of agriculture data, information and knowledge supported by current standardisation, but also by future research in ICT for agri-food industry. It reflects the needs of the agriculture business. The focus of the SRA is on identifying major ICT challenges related to the utilization of ICT and data, information, knowledge and standards in agriculture and agri-food industry sector. The agenda defines not only the necessary ICT standards, but also in a broader view the Research and Technology Development (RTD) areas which will be selected as key priorities in order to achieve the challenges identified.
Recent advances in information, control, and communication technologies greatly influence the progress in modern Agriculture. In particular, in the last decade, wireless sensor networks technology has dramatically changed the ways of measurement, communication and control in precision farming. Moreover, the evolution in the microelectronics allows for easy smart sensors and actuators implementation. Reliable, low energy low cost and easy to deploy wireless sensor networks is a challenge for precision farming towards sustainability. In addition, methods for unification of sensors and actuators interfacing and handling can lift off the development of ICT applications in sustainable precision farming. In this paper, the architecture of a wireless sensor network relying on the DASH7 protocol that uses the 433MHz frequency is proposed, together with the design of a node device compatible with the smart transducers according to IEEE 1451 standard as a means of unification of the physical layer of interfacing with sensors and actuators.
The sunlight-based plant factory supported by the Ministry of Agriculture, Forestry and Fisheries (MAFF), which has a potential to achieve long-term stable tomato production under global climate change, is not yet able to produce tomatoes with the quality meeting the consumer’s preference. Furthermore, even though the sunlight-based factories use less electricity than other factories, they still require a lot of energy to keep optimizing the growing environments. To solve these problems, we started creating a next-generation technology for plant factory system by utilizing the information and communication technology (ICT). The proposed system can manage the product quality demand as a dependent variable, make it possible to reduce electric power consumed to maintain the temperature, and make a stable production of a certain level of quality, which can be determined by counting the consumer’s preference backward. We have successfully created the scheduling software used in the system.
Massive mobile technology growth during the last few years has brought GIS technologies into another dimension. It is a big challenge for standard GIS technologies. New areas of applications are revealed for wide community of users. The INSPIRE and mobile mapping apps infrastructures differ in many things such as philosophy, application area and technical solution. It is also vital for the successful implementation of INSPIRE. Currently, there exist two worlds: 1) top down managed world of INSPIRE (GMES, GEOSS and similar initiatives) represented by SDI experts and 2) world of smartphones, tablets, world of ordinary people and also world of thousands micro SMEs developing applications. There are two important issues. On the one hand, Europe and EU invest hundreds of millions of euros in building the INSPIRE infrastructure. On the other hand, most of European SMEs and citizens use for their applications Google maps. National and regional SDIs offer such information which is not available on Google. The idea of INSPIRE in pocket is to build a bridge between these two worlds. First real step towards INSPIRE in Pocket is HS-CAT. HS-CAT is application for searching, browsing and displaying metadata records.
There is a wealth of institutions and projects that offer access to good educational resources related to food safety and food standards, ranging from training opportunities and courses to open educational resources, and from targeted/needed skills and competences to certification opportunities and courses. Still, these resources cannot be easily discovered, especially on a global scale. As in other areas of agricultural education, there is a need to pool together the variety of resources on food safety and standards in a baseline infrastructure that will enhance their findability and discoverability. This paper introduces an approach that can help address this challenge: taking advantage of current advances in e-learning technologies and standards in order to set up a learning infrastructure for food safety that will be open and scalable.
Agricultural sciences are one of the largest and most significant examples of Big Data research communities. The development of this research field brings about demands for larger, more powerful and trustable computing infrastructures to support the work of agricultural scientists. On the other hand, Cloud and Grid technologies have emerged in the last decade as a way to integrate large-scale data infrastructures. In the present work, we describe a federation of large computation and storage infrastructures developed within the agINFRA project, and the interfaces to use them. The new data infrastructure and its interfaces allow different user profiles to access and take advantage of applications and services to manage, process, navigate, and visualize trustable information on agricultural science topics.
The environmental concern and the oil price rising stimulate the implementation of policies to replace the fossil energy source. In this context, biofuels emerge as the most feasible alternative to attend this new demand. However, the potential impact of the biofuels production on the demand for agricultural products raises the question about the competition biofuels versus food. The investment analysis of projects and policies are complex, thus requiring tools to support the decision-making. The purpose of this paper is to evaluate the applicability and usability of a decision support system for the investment analysis on biodiesel projects, developed under an agreement signed by UFV (Federal University of Viçosa/Brazil) and FAO/RLC (Foods and Agriculture Organization - Regional Office for Latin America and the Caribbean). The normative ISO 25000 series (Software Product Quality Requirements and Evaluation) was the framework chose to evaluate the quality aspects. Additionally, the ISO 9241 (Ergonomics of Human System Interaction) was selected to evaluate the effectiveness, efficiency and satisfaction of the software by the user. The questionnaire applied on the evaluation consisted on quality attributes related to the normative ISO 25020/07 (Measurement Reference Model and Guide) and ISO 9241. The results obtained were treated descriptively and confirmed the software usability, especially related to efficiency and effectiveness.
In this paper we describe the ongoing move of the AGRIS repository toward a decentralized approach based on Linked Open Data (LOD) (Bizer, et al., 2008). This move has progressively required modifications and enhancements to data, models and workflows. The growing demand for freely accessible data has brought a rise in data distributed using LOD, which combines Resource Description Framework (RDF) (McBride, 2004a) and RDF Schema (McBride, 2004b) with vocabularies such as Dublin Core (DC) (Miles, et al., 2009) and Simple Knowledge Organisation System, together with interfaces such as SPARQL query language for RDF (Prud'hommeaux, et al., 2008). While LOD implementations are by now a well-established pattern, the impacts that such approaches have on underlying business processes is less well understood. The openness of the LOD paradigm can expose flaws in information management workflows. Poor metadata, lack of metrics, vague provenance; all can contribute to the inability of an LOD-enabled system to satisfy the demands of the Semantic Web.
In the short and medium term, biofuels are the most viable alternative to reduce theenvironmental impact of fossil fuels. The recent controversy over the competitionbetween biofuels and food production increases the complexity of investment decisionsin the biodiesel production chain. In this context, decision support tools are highlyrelevant. The purpose of this article is to describe the BiodieselFAO using the UnifiedModeling Language (UML). An integrated analysis considering both agricultural andindustrial sectors was identified as a key requirement to the system. Therefore, farmersand industry are the main actors in the use case diagram. As the raw material representsaround 70% of the industrial cost of biodiesel production, the price negotiation of rawmaterial (oilseeds) is the central use case. Configuration, agriculture, industry, resultsand scenarios are the modules, which encompass the functionalities derived from theUML diagrams. The Food and Agriculture Organization of the United Nations (FAO)has made the BiodieselFAO available, free of charge, to around 180 professionals from17 Latin American countries. Additionally, the developing team has supported the usageof the BiodieselFAO in several biodiesel investment analyses throughout LatinAmerica. The system was also useful in the design and analysis of policy related tobiodiesel industry in Brazil
Netnography is the conduct of ethnography on the internet, within social networks and communities. Ethnography is a qualitative research method for understanding and analyzing cultural phenomena in its most naturally occurring setting. Netnography employs similar concepts. However it differs as a market research technique which makes use of a participative and an observational approach to the study of online communities. Netnography is primarily used to study Social Media. This is any form of online publication or presence that allows end users to engage in multi-directional conversations. By allowing users to create and share their own content, it gives a direct link into the relationships and interactions among the users themselves and their subject matter. The purpose of this study is to use a netnographic approach to social networking amongst young professionals in agriculture (YPs). Specifically the study examines the level of usefulness of social networking in terms of an information source, a networking movement and a support system for young professionals in agriculture. The study directly examines interaction among the online community of YPs that are involved with the #cooltofarm hashtag topic of the social media site Twitter. In order to evaluate the usefulness of social networking, the methodology of the study involved the application of the Netnography Process. The method provided a system of meanings within the target group. The process consisted of five steps: 1) Planning a Research Focus; 2) Community Identification and Selection; 3) Engagement, Immersion and Data Collection; 4) Analysis and Interpretation; and 5) Presentation of findings and feedback. Engagement and Immersion began with a period of observation of the YPs community followed by an entree into the commune to participate and ethically gather information. This led to data collection of which three types were recorded; a) Archived (data collected without the researchers involvement); b) Elicited (data co-created by researchers and community members) and; c) Field Notes (observational and reflective data). A Coding process was executed to ensure consistency in the data. Preliminary results have indicated that social networking works well for YPs as a networking tool and a source of agri information. Further data collection and analysis is necessary to illustrate key findings and to meet a set of ten evaluation criteria that assess the standard or quality of netnographic research.
Different indices and complex indexes can be used for ICT-level comparisons between countries. But just simple indicators or absolute indices are available for analyzing smaller territorial units within a country. By contrast, a multi-dimensional regional analysis allows evaluate of a given region in several ways, recognizing its strengths and weaknesses and development potential. The main aim of our research is to evaluate the availability and usage of broadband network infrastructure and the subscriber services in regional level, because the implementation of certain projects concerns principally the smaller areas directly. We used regression analysis for find out that weather there is any relation among the ICT and socio-economic indicators, regardless of the causal link between them. In the case of Hungary we present the development over time and regional differences of different indicators, which are related to the usage and availability of broadband networks. We tried to examine which factors have contributed to the change of these indicators, and to determine that the results obtained have contributed for the development of a region, what are the direct or external effects. The units of the analysis are the NUTS-2 regions of EU, but those member states, where any of chosen indicators wasn’t available; their regions have not been included in the present analysis.
A multi-distance continuous wave optical sensor for nondestructive monitoring of fruit quality in the visible and near infrared spectral range has been developed. The sensor has been characterized in terms of sensitivity to changes in the optical properties by means of measurements on solid tissue phantoms. A state-of-the-art technique for characterization of diffusive media, time-resolved reflectance spectroscopy, has been used to assess the optical properties (absorption and reduced scattering coefficients) of the phantoms so as to provide a calibration for the new sensor. Measurements have been also performed on fresh apple to test the correlation between the readings of the two sensors.
This paper describes the construction of a fuzzy inference system (FIS) based on rules to assess the sustainability of farms in the Pantanal. Sustainability of biomes is founded on three dimensions: environmental, social and economical. This paper presents a fuzzy approach to integrate sustainability indicators to quantify and simplify phenomena that are accessible to all users and assist decision makers for understanding of complex systems. This work also describes two tools to support the construction of fuzzy systems, called FuzzyGen and WebFuzzy. They were developed by Embrapa Agricultural Informatics and Embrapa Pantanal. The use of sustainability indicators is an efficient strategy to evaluate and formulate development policies. The monitoring of real production systems of beef cattle in the Pantanal was the basis for the definition of variables to represent the performance of the activity. The validation was performed from scenario simulation in a fuzzy inference system (FIS). Scenarios were constructed to critical evaluation of producers until convergence analysis results from the experience of producers
Emerging technologies enhancing implementation of more advanced software were analyzed and applied to upgrade the standalone DSS Ziarbit, developed by the authors in past years, to a form of a Web-based decision support system embedded in Semantic Web frameworks. The system was developed to support design and management of cereal grain drying, handling and storage facilities. New technologies were used for problem domain analysis, UML diagramming, knowledge representation and Semantic Web implementation, and recent Microsoft programming environments were applied (.NET 4.5, ASP .NET 4.5, C++/CLI and C# available in Microsoft Visual Studio 2012, and Windows Phone SDK 8). In order to ensure interoperability, a concept of Internet-based Knowledge Center (IKC) was introduced and the new system was developed within the IKC framework.
In the frame of Borlaug Global Rust Initiative (BGRI), a web-based data management system - the Wheat Rust Toolbox - was developed to support surveillance, monitoring and early warning of new aggressive wheat rusts on a global scale. On-line data entry permits quality controlled and standardized data to be entered into the system. Once validated and approved, data are published and automatically disseminated via a series of interactive graphical and mapping web tools. The wheat rust single tools are embedded and integrated with other information in the Global Rust Reference Centre (GRRC) hosted by Aarhus University and in RustTracker – a global wheat rust monitoring system hosted by CIMMYT. The targeted countries for RustTracker are Central and West Asia and Africa. The backbone of the system is a Host-pathogen Microsoft SQL Database and Web system, combining host and pathogen data in a flexible way. After login to the toolbox a user management system controls the access rights to user-group specified tools and features. To stimulate partners to supply new data, dedicated login protected tools that analyse and summarise the raw data on country level, are available for data owners. The importance and distribution of new aggressive wheat rust in a global context are available for the wheat growing community in interactive maps, graphs and tables. The target for information is the farming community, breeders as well as scientist working on wheat rust and other crop disease. To reach the target user groups, dedicated tools and results are embedded in external web pages i.e. the RustTracker (http://rusttracker.cimmyt.org/) and the web site for the Global Rust Reference Centre (http://www.wheatrust.org). The wheat rust toolbox integrates and analyses more and more data from new tools related to phenotyping and genotyping of the pathogen and for the characterisation of host resistance. The challenge is to understand the interaction between the host and the pathogen, and to be able to monitor and predict the evolution and spread of new aggressive races. In Europe farmers can apply agrochemicals when new aggressive pathogens attack the crops. In the developing countries the majority of farmers must heavily rely on resistant cultivars.
Handling spatial data from sensors, farm management information systems (FMIS), local legislation, weather and many other data sources is becoming an increasingly challenging task for managers and stakeholders of arable farming. The amount of data, sources and on line services, heterogeneous group of data processers, and the complexity of agricultural practices calls for novel and common spatial data infrastructure. Automated process data acquisition and control is a reality in industry for online management of the production line. For farm machinery the use of sensor data and job files is restricted by hardware and software compatibility, different data formats, the lack of common concepts for interpretation of data, and the amount of data itself. This paper demonstrates an implementation of standard web feature services (WFS) defined by the ISO 19100 series, initiated by the open geospatial consortium (OGC) and ISO/TC211. Data are recorded by a novel web client based electronic control unit (ECU) and data is exchanged online with a web server offering WFS. The features in this study refer to field operations management data. Data are organized and stored on the server. It is demonstrated that data can easily be requested for further processing and use via the WFS.
The federal advisory services in Germany are legally obligated to provide a warning service for farmers. This is to alert in time about possible dangers to crops so that appropriate control measures can be taken. Recommendations are largely based on representative field observations of the first occurrence and the development of plant pests and diseases. For more than ten years, these monitoring data can be entered into and viewed online in the German advisory portal www.isip.de. Now mobile web pages have been developed to permit the input of data at the location of assessment. As a special feature, these web pages are fully functional even when offline, because the network coverage in the rural areas of Germany cannot be considered comprehensive.
In recent years new technologies to support agriculture are becoming more accessible. Wireless Sensor Networks (WSN) are networks of sensors located within the cultivated area able to measure, collect, process and sometimes share in real time many micrometeorological parameters. In the last years it has become possible to combine high spatial resolution images, quick turnaround times and low operational costs in order to generate useful remote sensing products for vegetation monitoring. Remote sensing platforms based on unmanned aerial vehicles (UAVs) represent a tool for this purpose, providing low-cost approaches to meet the critical requirements of spatial, spectral, and temporal resolutions needed. In the present work a low cost and open source agro-meteorological monitoring system in vineyard was designed and developed, and its placement and topology was optimized using a set of UAV-taken multispectral images.
The objective was to assess the accumulated volume and potential of biogas production in batch biodigesters from total and volatile solids added and reduced in manure of broilers that were fed a diet with probiotic and exogenous enzymes. In a completely randomized design, the study with the manure from broilers included 4 treatments (Cobb®), ages between 43 and 48 days, raised in cages, and fed different diets: a negative control (NC, a control diet without feed additives); probiotic (PRO, the NC diet + 500 ppm of a product containing Bacillus subtilis); exogenous enzyme blend (ENZ, the NC diet + 20 ppm of phytase, 200 ppm of protease and 200 ppm of xylanase); and a treatment combining both feed additives in the NC diet (P+E). Each treatment had 4 replicates in the batch biodigester. The manure was collected, identified and prepared (4% total solids). The volume per batch was the same (1.8 kg) for all biodigesters, with manure (0.301 kg) + water (1.499 kg). The vertical displacement of the gasometers was measured daily and the values were multiplied by their internal transversal section (0.00785 m2) to determine the biogas volume accumulated in 142 days. The gasometers were reset after each reading using the discharge valve. The biogas volume was corrected for 1 atm and 20°C. The potential of biogas production was calculated using the accumulated biogas volume and amount of total and volatile solids added and reduced in the biodigesters during the anaerobic biodigestion. The values were expressed as m3 biogas /kg total and volatile solids added and reduced. The data underwent variance analysis employing the General Linear Model procedure using the SAS® software. Averages were then compared based on Tukey test with a significance level of 5%. Analyses of the total accumulated biogas volume during 142 days showed that there was no statistical difference (P<0.05) between the treatments. However, when the potential of biogas production was evaluated, a statistical difference (P<0.05) was found for all evaluated characteristics. When treated in the batch biodigester, manure from the birds fed the P+E diet had a higher potential for biogas production per kg of total and volatile solids added and reduced, being different from those solids added to the NC treatment. In relation to the reduced solids, it was different from the ENZ and NC treatments. The use of P+E increases the potential for biogas production.
The objective was to quantify total and thermotolerant coliforms in affluents and effluents from the manure of broilers that were fed a diet with probiotic and exogenous enzymes, treated in batch biodigesters. Samples of manure were collected from broilers (Cobb®), ages between 43 and 48 days, raised in cages, and fed different diets: negative control (NC, a control diet without feed additives); probiotic (PRO, the NC diet + 500 ppm of a product containing Bacillus subtilis); exogenous enzymes blend (ENZ, the NC diet + 20 ppm phytase+200 ppm protease+200 ppm xylanase); and a treatment combining both feed additives in the NC diet (P+E). The manure samples were identified according to the diet and prepared (4% total solids). The volume per batch was the same (1.8 kg) for all biodigesters, with manure (0.301 kg) + water (1.499 kg). Samples were collected from the affluent at the beginning of the trial and from the effluent after 142 days of treatment. Coliforms were determined using the Most Probable Number (MPN) of Total (35°C) and Thermotolerant (44°C) Coliforms. Results were expressed as MPN/100 ml affluent and effluent and efficiency percentage of treatment in the batch biodigesters. Total (NC- 14x10Ñ; PRO- 7,8x10Ñ; ENZ- 4,5x10Å; P+E- 14x10Ñ) and thermotolerant coliforms (NC- 11x10Ñ; PRO-7,8x10Ñ; ENZ- 4,5x10Å; P+E- 14x10Ñ) were present in the affluent samples from all treatments. The ENZ treatment had the lowest amount of coliforms in the affluent and coliforms were absent in the effluents from all treatments. It was found that the microbiological treatment in batch biodigesters had 100% efficiency when the affluent and effluent samples are compared. It can be concluded that adding enzymes to poultry diet reduces the organisms present in broiler manure affluent. The same observation was made in batch biodigesters, with 100% efficiency in all treatments.
The purpose of this study is to assess the temporal distribution of climate and hydrologic attributes measured in a field-scale watershed in Treynor, IA. ARIMA models have been applied in 36 years of measured data and from final models long term change were identified at runoff and gully sediment time series. During wet-season (summer) temperature and precipitation slightly increased at this site from 1965-1999, whereas sediment yield decreased 0.48 ton per decade in summer and 0.26 ton in spring season.
Soil compaction in agricultural fields, especially in the subsoil, is an increasing problem caused by traffic with heavy machinery, and the damage has proven nearly persistent. Decision support for sustainable traffic is urgently needed. The Terranimo model (www.soilcompaction.eu) simulates the stress distribution in the contact area and down into the soil as inflicted by a tyre with a certain wheel load and inflation pressure. Evaluation of the compaction risk is achieved by comparison to soil strength also estimated by the model. The model needs information on machinery, site characteristics, soil texture and soil water content. The machinery data can be selected from a database, where data on machine are stored by country and where tyre data are stored in general tables. The user can supply input on soil texture and soil water both manually and by automatic methods, which can utilise country-specific soil and weather databases. State-of-the-art models are implemented for simulation of stress distribution in the contact area and the vertical stress in the soil profile. Only the vertical stress component is dealt with in this first version of Terranimo. Soil strength is calculated from soil clay content and soil matric potential by equations derived from new data on soil precompression stress. Model outputs are presented as charts. Contact stress is shown in a 3D surface or contour plot. Soil stress in the soil profile is shown as contour plots with stress isobars. The present version of the Terranimo tool is considered valuable for farmers, contractors and agricultural consultants to show the effects of machines and soil characteristics on stress propagation and soil strength and to evaluate soil compaction risk. The tool is prepared for worldwide extension depending on the availability and the possibility to access national soil and weather databases.
The market of the agricultural machineries has been recently modified due to globalisation, with an increasing of the competiveness and machinery reliability, and a reduction of cost production and development time. To perform this and, in particular to increase the reliability of the tractor, a tractor design correspondent to the real use on the machines is necessary. For these reasons the analysis of the tractor mission profile is one of the main objectives of tractor manufacturers. The mission profile of the tractor has usually been estimated through the use of questionnaires submitted to consumers followed by the monitoring of some detailed parameters using transducers specifically fitted on the tractor. This procedure is time-consuming and not totally reliable due to the trustworthiness in the questionnaire compilation. In all the high power tractors numerous transducers are fitted to monitor some parameters to optimise the operation of the machine. All of these transducers are connected to an electronic central unit or with the tractor CAN-Bus. In this context, a system able to monitor the operation and use parameters of the machine capitalising the existing transducers could represent the optimal solution for monitoring a high number of tractors, distributed in different regions. The high number of signals are in any case difficult to be memorised without a high quantity of memory. The goal of the paper is to define a methodology to memorise the operation parameters useful to define the mission profile of a tractor using a small memory. A tractor of a nominal power of 170 kW was selected and a system able to measure the signals acquired by the transducers fitted on the tractor was connected to the CAN Bus of the tractor. To reduce the memory requested to store the signals, all the signals were converted on matrices, with a similarly procedure used in the analysis of the strain gauge signals. In this way it is possible to count the number of occurrences for each event as the number of hours of tractor use, the number of hours for each gear use, etc. After a detailed analysis of the parameters measured on the tractor, the useful parameters were defined and acquired during 1000 hours of tractor use in different working conditions. The method defined in the paper has allowed to store the defined time of about 1000 hours into 100 kB, instead of 24 GB required to memorise all the parameters acquired by the transducers. The analysis of the parameters stored in the memory has allowed a detailed analysis of the operational parameters of the tractor in different applications. These parameters could be used by the engineers to design tractors with a higher quality and reliability and also to define predictive maintenance criteria and reduce the unexpected tractor failures.
Damage evaluation of an agricultural pipeline system is normally used by non-destructive testing, such as elastic wave method. For effective maintenance and management of pipeline system, it is necessary to evaluate not only the degree of damage but also the water-flow conditions using ICT techniques. In this study, acoustic emission (AE) method was applied to be detecting flow conditions in service open type water pipeline system. The purpose of this research is development of detection method for water flow conditions in pipeline system based on ICT technique.
Amber33 rice cultivar was used to evaluate the effects of milling duration of wetting brown rice on broken rice (BR) and temperature of milled rice. Brown rice at initial temperatures was = and an amount of water from ( 0 % ,1%,2% and 3%) was added to the brown rice whose moisture content 13.6% before milling and milled for duration ( 0 ,15, 30, 45, and 60 ) sec in a satake grain mill laboratory . There relationship between duration of milling and broken rice was appositive . it is showed that broken rice increases 2.5 % - 25.5% when increasing duration from ( 0 - 60 ) sec with wetting from( 0 % - 3% ) but this study showed that the water added for brown rice helped to reduce rice temperature in comparison with not wetted . However, when, increasing wetting effect positively on the performance of whitening machine because it make the removal of brown layer easy and duration of milling less
The presented in work model to identification of mechanical damages of corn kernels basis on the digital images. Produced model operate support by two technologies: computer image analysis and artificial neural networks. First technology analyses corn kernels images and saves gain this way information to the learning files. The artificial neural networks conduct the process of damages identification basis on produced learning files. Analysis of sensibility produced neural model showed on key part information about color of corn kernel in process identification. Information about shape of corn kernels have smaller significance. Base on mentioned analysis was decided to check influence of colors compression on working quality of neural identification model. Applied method of average information of color value in one teaching example. Also executed division to percentage participation color three basic colors according to the RBG model in one teaching example. So processed learning files were presented again to the artificial neural network. The results of working neural identification model, learning on modified teaching files, appeared significantly worse from trained on learning files including the full information about color. First method of compression showed larger error of model working than second method, with proportional part of basic colors. Obtained confirmation the key meaning information about corn kernels color in process of damages identification.
In the past 50 years climate has changed rapidly, include warming of the world’s ocean. In Vietnam, sea level monitoring data in marine-coastal stations show trend changes in average sea levels are not the same through coastal areas. Most of these stations tend to increasing, however, a few stations did not clearly reflect this trend. Changing tendency average of sea level along the coast Vietnam is about 2.8mm per years. In this research, we focus on the changing of temperature, rainfall, tropical hurricane, flood and drought in coastal areas of Vietnam. These factors are reasons for rising sea level. Sea level rising in coastal Vietnam affect to human life, social-economic development activities, especially agricultural production. Therefore, the research and forecast sea level rise and identify risk areas for future is essential
Computer-based analysis of heat and water transport in agro-food and forest products is difficult due to material complexity of the products, lack of reliable data on product material properties, and imperfections of software. Therefore an information system was developed to enhance estimation of values of material properties, and to improve quality of computer analysis of thermo-mechanical behavior of agro-food and forest products. It was based on original algorithms of image analysis and 3D finite element mesh generation, geometry modeling and inverse coefficient problem solving. Original authors’ software modules were improved and integrated to support the overall analysis. The resulting information system was able to enhance identification and analysis of geometric and physical properties of selected agro-food products subjected to thermo-mechanical processing, and accuracy of the analysis of heat and water transport in the products examined was significantly improved.
We carried out the conversion, rounding and placing into table with Microsoft Visual C# 2010 developing system. We saved the figures received when running the program into an Excel worksheet in order to make further data processing easier. The next step to save these data into a database. A stable relational database is needed which will handle data and also provide data for the query system. Since I aimed to apply standard solutions, I needed an SQL-based system and finally chose the MySQL database server, because it is free of charge, portable, compact and fast in case of bigger record numbers. We studied the environmental pollutant affect of the molybdenum by elements load experiment in Nagyhörcsök Experimental Station. We analyzed the contact between the uptake of molybdenum and other micro-elements and its effect on plant organs (loaf, seed) using by different statistical methods. The aim of investigations to search for answers on how to arable crops respond to a possible soil contamination. It is also important to determine the extent of mobilized elements from the soil into the plants, which type of effect on them, and how leach the harmful substances into deeper layers (groundwater).
In this study, development of a planning support system (PSS) was studied as a tool to support the planners for analyzing and choosing the best policy instruments in order to adapt to climate change. In order to carry out this study, different methods for regenerating the time series of climatic variables were assessed and finally, a comprehensive weather generator model was developed which was capable in regeneration of statistical characteristics and also spatial correlation between neighboring stations. After downscaling the monthly outputs of GCM models using the Inverse Distance Weighting (IDW) method, the developed weather generator model was used to generate daily time series for the base and climate change scenarios. In order to simulate the Taleghan reservoir daily inflow using the data fusion method, the outputs of the best Artificial Neural Networks and Hammerstein-Wiener models were used and the reservoir daily inflow was simulated under climate change scenarios. The results confirmed the decrease of mean daily inflow in almost all the months. PSS biophysical input coefficients were estimated using the DSSAT crop simulation models under all climate scenarios for 24 land units. The potential production of all studied crops could vary between 86% and 122% of the potential productions in the base scenario. Also, it was revealed that the net irrigation requirement of the crops will decrease by 12% on average. The main goal of the PSS was to maximize the total net income of the entire area. Analyzing the management scenarios using the planning model showed that the best option for climate change adaptation will be the combination of all the instruments in one management scenario. Also, it was concluded that the reduction of interest rate and using two different water prices for surface and pressurized irrigation systems could be the best management scenarios after the combination scenario.
The number of educational institutions, companies and other users applying knowledge repositories has grown significantly in the last decade, therefore they have become as important means and resources as other informational systems of the institutions. However, there are several conditions and components to implement and use these systems successfully. Based on opportunities of knowledge service system we have created a 4-level model. This model shows and expresses the plenitude of the application of knowledge service, has become an integer, and uses all the benefits of this process for the recovery of University of Debrecen service system.
Advances in the Information and Communication Technology (ICT) and availability of fine resolution remote sensing spatial data provides an opportunity to identify previously unknown and potentially useful patterns from the huge datasets. Application of geospatial data mining techniques has been used in various agricultural contexts such as drought management, vegetable quality classification, pest management and several other agriculture related areas. The recent development and implementation of watershed programs in rainfed regions of India has highlighted strategies that can be used to conserve water for irrigation of crops. Due to aberrant rainfall conditions in the rainfed regions and enormous changes in the landuse, the impact of the watershed development has greatly influenced the local hydrology. Any understanding of the impact of watershed development cannot be made through an examination of a individual watershed, but through the examination of all surrounding watersheds. This can be achieved using geospatial datasets and available novel data mining algorithms. For example, these techniques could provide an assessment of the effectiveness of watershed development using different land use patterns, cropping intensity, water availability, aquifer re-charge and positioning of different watersheds structures in a catchment. This paper attempts to explore the application of geospatial data mining techniques to watershed data sets. An evaluation and quantification of hydrological impacts of watershed development under varying climate and management scenarios using advanced techniques of geo-spatial data mining could be one means to improve the understanding of these impacts. This paper reports on the development of a robust data matrix of various parameters that affect the watershed and the application of various data mining algorithms. It is concluded that there is no single technique that can be used to assess the impact of watershed development.
This paper describes a device developed to aid farmers shooting images in fields for the monitoring of crops without any button manipulation. The device, referred to as the Hand Framing Camera, allows users to quickly switch between shooting and field work because with this device, it is not necessary to take off gloves or get the camera out of a bag or pocket. Users can take pictures by forming the shape of a picture frame around the target with their hands. The result of a field test suggested that users could easily and quickly take pictures of plants while they were at work in the field.
The unstoppable evolution in diversity and capacity of information and communication technologies at our disposal, in particular the growing features of collection and data storage, communication facilities and associated action, which can be integrated in mobile and collaborative solutions, created a window of opportunity to innovate and create decision support systems that allow us to put on the field at the disposal of farmers and agricultural technicians sophisticated information systems that support decision making by providing updated information, at the right time and in the most appropriate format. The delivery of information to the end use is nowadays receiving increased attention and to deal with this challenges one of the possible approaches is to launch Business Intelligence (BI) platforms. The present work addresses the last step of these BI platforms, the user interface challenge and proposes for the agricultural field the usage of smartphones and augmented reality as an effective mechanism to deliver in the field and in a transparent way information for decision making. With that purpose we present a augmented reality prototype to deliver information for decision support in a greenhouse using a BI approach and a smartphone Layar augmented reality interface.
European wine industry is a strategic economic sector that is nowadays facing a growing competition in the international market at the same time it as to deal with predictable lower support from the CAP. Taking into consideration that the use of ICT can support the development of new tools and devices that can reduce costs and increase final product quality/quantity an international consortium that comprises 3 technical companies and 3 winegrowers together with 3 research groups setup the EU Project PREMIVM. In this work will present the PREMIVM decision support system that was developed including the field device for data collection - WINEPEN, the web information management system for data storage, processing and information visualization, and the smartphone interface for information delivery. ..
Intensive agriculture and livestock breeding represent critical factors in the environment, particularly in the Lombardy region where nitrate vulnerable zones represent 62% of Utilised Agricultural Area (UAA). The problem of reduction of nitrogen losses as leaching of nitrates into groundwater and ammonia emissions into atmosphere can be only addressed through a critical and scientific analysis of animal manure entire production chain. As consequence, the ValorE Decision Support System (DSS-Valorisation of Effluents) has been developed to run simulation both at farm and territorial scale. ValorE allows to define, simulation scenarios on the basis of different manure management options and evaluate these by synthetic indices which take into account environmental, economic, technical, multifunctional and normative aspects. The application of the DSS in a sample of selected farms highlighted its potentiality as a tool to support stockholders' decisions and how an intervention planned at district level could be a useful solution to improve livestock manure management.
This paper presents the eFoodChain project, its objectives and main achievements so far. The overall goal of the eFoodChain project is to contribute to the improvement in the competitiveness and efficiency of the agro food industry in Europe by stimulating an innovative and seamless use of ICT along its value chain. SMEs, that represent more than 99% of companies and generate approximately half of the industry turnover, are the focus of this action, as the objective is to facilitate their participation in the global digital food value network and enable them to become international business partners. We present the first results of the project, starting with an analysis of the current European landscape in electronic message exchange in the agro food value chain, the eFoodChain proposed approach to improve its efficiency and promote the inclusion of SMEs, and discuss the pilot scenarios that will be implemented to demonstrate this approach.
Agricultural research for development, largely aimed at fulfilling agricultural technological needs of developing countries, has primarily been carried out by national public funded Institutions and international research systems funded by foreign donors such as that of the Consultative Group on International Agricultural Research (CGIAR). These institutions generate public goods. The use of new Information and Communication Technologies (ICTs), especially the Internet, Cellular telephony and FM radio, is bringing about the possibility of new partnerships in information generation and use between the agricultural community, the public and private sectors (C-P-P partnerships). The generation of data and information in pluralistic extension systems now being advocated and promoted the world over inherently recognizes that farmers and agribusiness entrepreneurs are also generators of agricultural data and information and not only users. The corporate private sector in many developing countries provide not only the “bus” or channels through the Internet and Cellular Telephony needed to communicate but also the applications to make use of data and information. The public sector’s role still remains to be generator and manager of organized agricultural data and information. However these roles are fast changing. The current user communities and individuals, with farmer and civil society organizations in the lead, are organizing themselves through participatory efforts to generate data and information related to agriculture and natural resource use. This local data and information of natural resources such as soils and water, agricultural biodiversity, disease and pests etc and used through GIS systems is proving to be far more accurate, relevant and current than that acquired through conventional approaches such as surveys. The private sector has seen the potential of agricultural knowledge services and has initiated businesses that generate value added services such as for advising farmers through call centers, assessing risk for financial and insurance service providers, forecasts on markets in addition to being channel providers and generating applications. The public sector in developing countries, however, still finds it difficult to link up with the private sector and use the community sector to leverage its data and information management, especially in generating accurate local data, in disseminating information, new skills, knowledge and technology and in acting as a “Trust” organization in validating the relevance and accuracy of agricultural information. This paper discusses with examples, in the context of emerging information and communications technologies, the rapidly changing roles of the public, private and community sectors in information management for agricultural research for development, the constraints faced by each sector in working in partnerships as also how public-private-community partnership can rapidly enlarge further the effective management and use of agricultural information for development. It also discusses the Global Forum on Agricultural Research’s efforts in advocating and building effective C-P-P partnerships.
The sequence of working the parallel lines in agricultural field area coverage operations can be optimized to minimize the total non-productive time. The amount of savings achieved in using the optimized sequence, denoted the B-pattern, compared to the conventional sequence varies considerably depending on the operation’s features. This work presents a method for estimating the savings of using B-patterns and is applied on a specific problem instance consisting of a specific tractor, implement and field, based on a recording of a “conventional” operation. The savings assessment method consists of fitting a turn model using data from the recording, generating the Traveling Salesman Problem (TSP) cost matrix with turn model, solving the TSP and finally using parts of the recording to estimate the savings. The specific problem instance was a harrow operation with an estimated savings of 3.3% in total operation time.
The purpose of this research was to determine the impact Planting winter morphological, phenological, agronomic and physiological parameters taken from the local and the global collection accessions of lentil (Lens culinaris Medikus) to identify and sample the recommended cold-resistant varieties for cultivation in cold regions of Iran mountainous conditions and the definition of phenophases, where its impact is more pronounced, affecting crop yields. Thirty lentil genotypes accessions of Mashhad Lentil Collection (MLC) were evaluated at Chenaran, Iran with three planting dates [Oct., Nov. (fall) and Mar. (spring) during 2009-011 growing seasons]. For all experimental year as a control has been chosen local (Iranian) cultivar «Ziba». According to the fall plantings data, the length of growth duration of samples in fall plantings were 2.3 times higher than spring planting, and also in the first planting that was 5, 25 and 255 percent more than 2nd and 3rd planting dates, respectively. The height of fall plants were more than spring plants and in the first year fall planting genotypes were about 38% taller than the same planting. The number of pod per plant in fall planting was 2 times higher than spring planting. More than 22% of accessions had 125 pods per plant in 1st and 2nd planting in this years. In the 2009-11 growing seasons the yield of lentil genotypes in fall planting were more than 4 and about 2 times of spring planting, respectively. It seems that the improvement of seed yield in the fall planting were due to suitable winter survival of plants fallowed by better usage of rainfall and escaping from drought and heat stress of the end of spring. Results showed that there were some cold tolerant accessions in MLC and it is possible to provide cold tolerant cultivars for fall planting in Chenaran conditions.
The application of plant protection product has an important role in agricultural production processes. With current pesticides management, a huge amount of them are applied to worldwide orchards. In precision spraying, spray application efficiency depends on the pesticide application method, the phytosanitary product as well as the leaf surface properties. For environmental and economic reasons, the global trend is to reduce the pesticide application rate of the few approved active substances. Under these constraints, one of the challenges is to improve the efficiency of pesticide application. Different parameters can influence the pesticide application such as nozzle types, liquid viscosity and leaf surface. In this paper, we focus on the vine leaf surface properties determination and the discrimination between two kinds of vine leaves (Pinot and Chardonnay) for different stages of development by following their roughness growth. This discrimination allows studying the impact of the product behavior, and allows to adjust the product viscosity and spraying parameters according to the roughness and the stage of vine leaf development. In this context, we propose to explore the performance of combination of Generalized Fourier Descriptor with Kernel Discriminant Analysis method using neural network. The results show that sufficient information can be obtained with this combination to characterize vine leaves.
In Italy, the establishment of the National Service for Voluntary Certification of plant propagating material has allowed the introduction of certified plants into the market, which were produced by using propagating materials verified in terms of varietal trueness-to-type and phytosanitary condition. The control of productions and activities carried out in the centres established by the National Service for Voluntary Certification could allow the identification of both possible sources of disease risk and the destination of the propagating materials. In previous studies a methodology was proposed and applied to carry out the requirements analysis and specification for the development of an integrated computerbased information system for certified citrus-plant traceability. This study proposes a methodology for the implementation of the database prototype required for the execution of the previously designed functionalities of the information system. The use of PostgreSQL, a free and open source object-relational database management system, allowed the implementation of the entity-relation scheme containing the information related to the managed propagating materials and the process activities defined by the certification program. The proposed methodology was applied to the case study of the Italian citrus-plant nursery chain. Specific information derived from plants and centres of the National Service for Voluntary Certification were included in the database along with the geolocation of both certified citrus plants produced in the nurseries and planted in the field and citrus mother plants. Geographic data acquired by using a GPS system were combined with other information concerning plant health condition and treatments with the aim to find out possible relations between the citrus-plant health status and the territory. The system implemented in this study allows the definition and utilization of ‘track and trace’ procedures of propagation materials and plants present in the certified Italian citrus-plant nursery chain, as well as the evaluation and prevention of the diffusion of the Citrus Tristeza Virus which causes one of the most damaging diseases in citrus orchards.
In order to eliminate diseases in agriculture and viticulture, the currently used solution requires massive use of phytosanitary products, dangerous for the environment and the operators. To respond to agronomic challenges, this study seeks to examine the feasibility of early detection of the presence of disease in plants by using imaging techniques based on specific images: acquisition based on thermal effects and image processing based on texture-color techniques.
The durability of agricultural infrastructures could decrease drastically due to earthquakes, in particular, seismic wave-motions. The degree of damage in service structures is, in most cases, evaluated from mechanical properties. For effective damage estimation, it is necessary to be monitoring of mechanical properties using ICT techniques. By the authors, quantitative damage evaluation of structural materials is proposed by applying acoustic emission (AE) method and damage mechanics. The procedure is named “DeCAT” (Damage Estimation of Concrete by Acoustic Emission Technique). In this study, damege estimation of deteriorated irrigation infrastructure is conducted by DeCAT system. The monitoring structure has been subjected to the influence of the Great East Japan Earthquake, two years ago.
Storing grain in hermetic plastic bags (silobags) is a frequent storage alternative for farmers, grain elevators and the grain processing industry in Argentina. During the last 5 years, about 40% of the grain production in Argentina was stored in silobags, and this technology is being adopted in several countries around the world. The silobags can store about 200 tones of grain, and it can be placed in the same production field, in a case of a farm, or in a field specially dedicated right next to the elevator. In Argentina, some farmers own their own silobag equipment, and for them is critical to know what is the real cost of bagging the grain in comparison with sending the grain to the elevator. On the other hand, other farmers use custom operation. For silobag contractors is also critical to know the real cost of the service, so they can charge a profitable rate. The main goals of this work were: 1) to present a web based application for computing the cost of storing grain in silobags, 2) to show the use of the application for determining the cost of storing grain in silobags for a typical system configuration in Argentina. The cost per tone decreases as the number of silobags increases, from 5.9 US$/tone for 15 bags per year to 5.03 US$/tone for 503 bags per year. The cost did not changed substantially as the number of bags increased due to the high proportion of variable costs. For a medium size operation (126 bags per year), the bags accounts for 59% of the total cost, labor 13% and fuel 24%, meaning that the variable costs accounts for 96% of the total costs, while the ownership costs represents only 4% (maintenance 1%, interest 1% and amortization 2%).
Detecting and collecting data from field are repetitive and time-consuming tasks. Agricultural robots would help the automation of these tasks such as gathering data from the field and transferring it to a DSS. One of the core elements of ICT – AGRI Robofarm project is to design one prototype autonomous robotic platform (RoboTurk) which will carry on several sensors and it will be able to perform agricultural tasks. In this paper a novel mobile robot will be demonstrated. The designed vehicle can be operated in open and closed field conditions and can carry several sensors such as hyper spectral camera for detecting field phenomena. In the future it will be able to have installed some implements, as: a spray system for variable spraying, a lifting platform to perform seeding, etc. The autonomous navigation, is been achieved with the use of a laser scanner and a RTK-GPS system.
Information and Communication Technology (ICT) is a generic technology due to its potential of value creation across a wide range of industries and applications. It has yielded benefits for a wide range of sectors of the economy and/or society. Agriculture is a strategic sector of producing food and fibre to supply basic human requirements. Its strategic importance has been increasing due to raise in world population and environmental constraints. Therefore, the survival and growth of agricultural production could be managed through the effective use ICT. This article aims to reveal the current status of ICT in Turkey by evaluating data published by the Turkish Statistical Institute (TUIK). In addition, the author argued challenges and prospects of ICT use in agriculture.
The needs to increase the efficiency in agricultural production, and the latest technological developments in ICT, have led to the creation of the first autonomous agricultural robots for open fields. Additionally, the rapidly growing technology of mobile internet communication and its capabilities have given the possibility for remotely internet connection of the autonomous vehicles. The aim of this study was to design and develop a web-based farm management information system (FMIS), capable of controlling agricultural robots and for analyzing their data in real time remotely with the use of a web browser. The FMIS was built in C#, and the first tests were held to two low cost fully autonomous vehicles designed to perform specific tasks within field operations. This research was funded from the ICT-Agri project “RoboFarm: Integrated robotic and software platform as a support system for farm level business decisions”.
Silobags technology is extensively used in many countries for storing dry grains. In the last years, 35 to 40 million tons of grains were stored with this technology in Argentina. Many farming operations have silobags scattered through different regions, separated several kilometers apart that create difficulties for a physical examination of the bags and the quality of the grain. A technology was developed in which each silobag is tagged with a RFID card. A portable CO2 meter with a RF reader is used. The meter is first activated with the RFID of the bag, and a number of measurements of CO2 are made along the 60 m of the bags. A service was implemented to perform the monitoring of the bags every two to four weeks. The information is transferred to a server via GPRS technology and analyzed. The owner of the bags can log-in in a web site and check the storage risk of the bags being monitored with this technology, regardless the location of the bag. In addition to that, if a bag reaches a critical CO2 value, an alarm is sent to the owner via e-mail, fax, or smt. This technology is currently used in more than 10000 bags in Argentina and neighbor countries
On the basis of research being carried out to investigate the potential of biomass and bio-waste for energy production in Europe and in India, more technical, economic and financial information has become available to experts in recent years; however, up-to-date information on biomass and biowaste is still not accessible to end-users. In the frame of the EU-SAHYOG Project, we collected the most up-to-date data on biomass production and availability from three major sectors: forestry, agriculture and wastes in Europe and India. Analysis of availability of the potential biomass and biowaste feedstock for sustainable conversion to bio-energy and bio-materials was performed at state level through an intensive consultation of existing databases and reports in both countries. The paper will provide a general overview on the biomass resources present at state level in the European Union and in India. An accurate analysis of the results SAHYOG inventories, will finally outline the EU and Indian priorities in biomass utilization and technology implementation
In this paper we present an account of the publication of a suite of datasets, LEAPS, that collectively enable the evaluation of potential algal biomass production sites in North West Europe (NWE). LEAPS forms the basis of a prototype Web application that enables stakeholders in the algal biomass domain to interactively explore via various facets, potential algal production sites and sources of their consumables across NWE.
No two farms are the same with respect to management structure, equipment, farm plan, etc. Farm information management systems (FMIS) of the future need to accommodate the differences and be holistic in nature as well as cost effective. Fortunately, many technologies are available to address these concerns, but they need to be integrated into workable systems which are intuitive as well as reliable. This manuscript covers some elements of developing autogenic systems (automatically generating data) which use always-on public cloud storage servers and highly capable mobile devices in concert with current agricultural equipment sensors and technologies. This type of system can provide nearly continuous and seamless synchrony and data sharing among devices for functionality and should improve data mining possibilities in the future.
Renewable energy sources are assessed thoroughly the last decade in order to be used instead of fossil fuels. One energy source, scientifically interesting, is biomass energy. This type of energy can be extracted of many biomass sources as some types of waste, wood residues from forestry, energy crops, etc. There are many interesting energy crops used for biomass production as biofuels (pellets, chips, biodiesel, etc.). Every energy crop in order to grow up for a given period needs some energy consumption which, in parallel means that provokes some CO2 emissions during the field operational management. These two factors are very important for evaluation of the sustainability of energy crops. In this paper, switchgrass is examined as a potential energy crop for biomass production. The field tested regards a 1 ha area, placed in a 1 km distance from the bioenergy facilities. The switchgrass crop, as a perennial crop, is tested for a 10 years period. Especially, in this paper energy consumption during the whole tested period of growth of switchgrass is examined, in order to be evaluated the sustainability of the crop. Energy consumption regards every energy input (direct or indirect) that is inserted during field operations management or from agrochemical material, fuels and other sources. In parallel, the CO2 emissions due to the field operational management and materials are assessed for the switchgrass crop.