Computers and Electronics in Agriculture (COMPUT ELECTRON AGR)

Publisher: Elsevier

Journal description

Computers and Electronics in Agriculture provides international coverage of advances in the application of computer hardware, software and electronic instrumentation and control systems to agriculture, forestry and related industries. The latter include horticulture (in both its food and amenity aspects), forest products, aquaculture, animal/livestock science, veterinary medicine and food processing.The journal publishes original papers, reviews, applications notes and book reviews on topics including computerized decision-support aids (e.g., expert systems and simulation models) pertaining to any aspect of the aforementioned industries; electronic monitoring or control of any aspect of livestock/crop production (e.g. soil and water, environment, growth, health, waste products) and post-harvest operations (such as drying, storage, production assessment, trimming and dissection of plant and animal material). Relevant areas of technology include artificial intelligence, sensors, machine vision, robotics and simulation modelling.

RG Journal Impact: 2.07 *

*This value is calculated using ResearchGate data and is based on average citation counts from work published in this journal. The data used in the calculation may not be exhaustive.

RG Journal impact history

2019Available summer 2020
20182.07
20172.12
20161.98
20152.90
20142.89
20132.56
20122.76
20113.46
20102.82
20092.39
20082.27
20071.96
20061.31
20051.18
20041.57
20031.21
20020.85
20010.85
20000.53

RG Journal impact over time

RG Journal impact
RG Journal impact over timeGraph showing a linear path with a yearly representation of impact points of the journal

Additional details

Cited half-life6.00
Immediacy index0.31
Eigenfactor0.01
Article influence0.52
Websitehttp://www.sciencedirect.com/science/journal/01681699
Website descriptionComputers and Electronics in Agriculture website
Other titlesComputers and electronics in agriculture (Online)
ISSN0168-1699
OCLC38840899
Material typeDocument, Periodical, Internet resource
Document typeInternet Resource, Computer File, Journal / Magazine / Newspaper

Publications in this journal

Of late, a series of methods and tools have evolved in order to assist farmers in making decisions, based on the development of computers. In this paper, an attempt has been made to focus on simulation tools as a means to expand interactivity. The first part deals with the understanding of interactivity. Then the use of simulation as a support for interactivity is developed. In this endeavor, the evolution of understanding of the role played by simulation tools for farm management decision-making has been considered crucial, based on experiments carried out in an interactive manner with both farmers and consultants. Finally, we introduce and discuss numerous potential opportunities provided by the new techniques through automatic machine learning and multi-agent modeling.
A review is presented of several potentially useful applications of artificial neural networks (NN) to greenhouse climate control. Subjects covered are: Quasi-steady-state modelling, reduction (compression) of input and state vectors, NNs used as difference equations and replacing controllers (algorithms or humans) with NNs. In this context the strength of NNs is their flexibility to adapt to non-linear and non-physical data. Their main disadvantage is that their proper training requires large multi-dimensional sets of data to reduce the risk of extrapolation. Therefore, minimizing the dimensionality of the problem (both input and state vectors) becomes of paramount importance. Bottleneck NNs may be used for this purpose.
This paper describes a project to enhance farm level computer use education entitled The Year 2000 Computerized Farm. The farm management information system implemented at the Stiles Foundation Farm is described as well as its effect on farm profits. An evaluation of the short courses taught at the farm provide an insight as to the approach and results of that educational effort. The suggestion is made that other educational institutions could follow a similar approach for staff and user training.
A brief report is given of the field robot contest held in Wageningen, 5–6 June 2003. The experience of the student competitors sheds light on a number of issues that need to be addressed before autonomous vehicles will become a reality.
A preliminary study on the potential application of electronic tracking in poultry in vivo has been conducted. The experimental procedure for this study was based on previous in vitro findings (Fröschle et al., 2009) as part of the same research programme. The study consisted of two phases whereby an initial experiment using inkjet printing of 10 × 10 DataMatrix barcodes onto the beaks of broiler chickens in a live commercial setting has been carried out. Results demonstrated very poor percentage of readability after a short period of time. Barcodes deteriorated very rapidly and this was attributed to the physical effects on the barcodes of the actions of the chickens in a commercial environment, together with the inability of the ink to bond to the hard keratinous surface of the beak. In a subsequent part of the study, a number of commercially available ink types were screened, using a predetermined abrasion testing procedure, for their ability to bond to the beak and provide a readable barcode on the beaks following some predetermined graduated physical abrasion.
Contemporary Precision Livestock Technology in poultry production is very limited and does not meet European standards for traceability and Best Available Technology (BAT), as laid down in EN ISO 2205:2007 standards (2007) and the European Directive 2008/1/EC (2008). A worldwide occurrence of Avian Influenza additionally calls for a fraud-proof tagging device and source verification system for poultry and poultry products in order to complete partially existing documentary trails.During a preliminary laboratory trial, a procedure for the application of miniature linear and two-dimensional Data Matrix (DM) barcodes onto poultry beaks and legs through inkjet printing was set up and assessed. Results regarding the proportion of readability (p%), the standard error in readability (SE) and general statistics on the reading time were calculated. Tests for independence based on Chi-square and Pearson's were performed on the categorical data, to estimate the differences between proportions of readability of reading groups. The resulting data was used to define the optimal position of barcodes as well as the optimal reading mode of the barcode scanner to be used for further trials. As this experiment provided an estimate of readability of barcodes imprinted on chicken beaks and legs, it is intended to serve as a basis for sample size calculation for an ongoing live trial.
A tractor drawbar performance program that predicts the performance of two-wheel-drive (2WD) tractors for haulage as well as field operations for both bias-ply and radial-ply tyres is developed to meet user requirements in educational and research organizations. The program is written in Visual Basic programming language. The program provides an intuitive user interface by linking databases such as tractor specifications, tyre data, implement and trailer specifications and traction equation coefficients to predict the performance of a selected tractor model. The program has been proven to be user friendly and efficient for various field operations under frictional–cohesive soils.
Recent advances in sensor and wireless radio frequency (RF) technologies and their convergence with the Internet offer vast opportunities for development and application of sensor systems for agriculture. The objective was to create regional and on-farm sensor networks that provide remote, real-time monitoring and/or control of important farming operations that add value through improved efficiency and efficacy of targeted management practices. This paper describes hardware and software components of technologies we developed for regional and on-farm sensor networks and their implementation in two agricultural applications in Washington State, an agricultural weather network and an on-farm frost monitoring network. The regional sensor network consists of our AWN200 data logger equipped with a 900 MHz, frequency hopping, spread spectrum (FHSS) radio configured into master–repeater–slave network for broad geographic coverage. A single master is configured with multiple repeaters to provide a RF line-of-sight telemetry backbone network. Independent network backbones from disparate geographic regions are then aggregated in a central database via standard Internet protocols for further processing and dissemination. Software includes firmware to operate the data logger and radio telemetry aspects of the AWN200 in an agricultural weather network application called AgWeatherNet (http://www.weather.wsu.edu). The on-farm sensor network uses our SS100 radio/logger which includes a 900 MHz, FHSS radio, with software designed primarily for mobile, real-time farm operations and management applications. The network is deployed in a star topology in which a strategically placed base radio is responsible for network synchronization, data collection from remote stations within the network, and re-broadcasting collected data to roamer radio units attached to mobile computers and/or directly to the Internet. Client software, AgFrostNet, operating on a computer connected to a roamer, collects, manages, and display data in real-time. This software was designed specifically for air temperature monitoring during frost/freeze protection events. Both the regional AgWeatherNet WSN and the on-farm AgFrostNet networks were successfully implemented in Washington State. Problems encountered were mainly associated with power management under periods of low solar energy and with electrostatic discharge (ESD) damage to gallium-arsenide (GaAs) based transmit–receive switches in the radios during storms, a problem now corrected. Both systems have been made commercially available to growers via a novel arrangement between WSU and a local manufacturer.
A 3D stand generator and visualization system was developed for generating a spatially explicit forest for central Appalachian hardwood forests. Spatial pattern of the stand generator was modeled and validated by characterizing a 75-year old central Appalachian mixed hardwood forest dominated by red oak, chestnut oak, red maple, and yellow poplar. All the trees larger than 12.7 cm diameter at breast height (DBH) were measured for DBH, total height, crown height and crown width along with their locations in thirty 0.162 ha plots. Stand attributes, i.e. species compositions, mean DBH, total height, basal area and volume in the generated stand never exceeded a difference of 10% from the actual stand attributes. The generated stand can thus be used as an alternate to time consuming manual measurement of spatial location of trees for related ecological studies and training purposes and to visualize the same in 3D perspectives. The results also indicated the potential of using this stand generator in simulating stand spatial patterns and generating stands in other regions with some modification in growth functions.
Dairy farmers using automatic milking are able to manage mastitis successfully with the help of mastitis attention lists. These attention lists are generated with mastitis detection models that make use of sensor data obtained throughout each quarter milking. The models tend to be limited to using the maximum or average value of the sensor data pattern, potentially excluding other valuable information. They often put cows on the lists unnecessarily, and their sensitivity for abnormal milk classification is too low for automated separation. Therefore, we analyzed sensor data patterns within quarter milkings in order to identify potentially predictive variables for abnormal milk and clinical mastitis classification. The data used in this study was obtained at a commercial dairy farm in Germany in September 2002, where a German Simmental herd was milked by a Lely Astronaut system. In total, 3232 quarter milkings from 63 cows were analysed; 94 quarter milkings were defined as milk with abnormal homogeneity and 270 as clinical mastitis. A data flow diagram was developed to systematically describe the steps involved in the transformation of within quarter milking measurements into variables that potentially predict abnormal milk and clinical mastitis. Three types of pattern descriptors were used: level, variability, and shape. In addition to using the absolute value of the pattern descriptor, the descriptors were considered relative to their expected value based on pattern descriptor values from previous milkings and from other quarters within the same cow milking. Using this method, potentially predictive variables were computed for electrical conductivity, the colours red, green and blue, a combination of colour sensors, and milk production. The importance of a variable in predicting abnormal milk and clinical mastitis was evaluated by computing correlation coefficients as well as information gain ratios. The most important variables came from the sensors for electrical conductivity, blue and green. Variables describing the variability and shape of the measurement patterns were as important as mean and maximum values, and should be included in future modelling. Also variables that are based on absolute values should be considered for future modelling. Results suggest that clinical mastitis and abnormal milk classification models may include similar predictive variables, but requirements for these models differ resulting in the need for different models. The schematic approach to developing potentially predictive variables will be helpful when exploring the usefulness of new sensors, researching other approaches to estimate expected values, and studying sensor data patterns in general.
Thinning is a silvicultural practice to improve tree growth and health. Thinning from below for the even-aged silviculture and thinning from above for the uneven-aged silviculture are the two mainly applied thinning practices. In forest management simulations, algorithms that describe which individual trees to be removed from a forest have developed in five growth simulators (Söderbergh and Ledermann, 2003). We have developed a shifting algorithm that determines the proportion of trees to be thinned from different diameter classes to complement the individual tree selection algorithms. Sampled (or mapped) tree diameters are grouped into diameter classes. Given the target thinning volume, the algorithm automatically computes the thinning rate in each of the diameter classes using the three-parameter Weibull distribution. The thinning rate is obtained by shifting the location parameter of an estimated Weibull distribution either to the right or to the left for thinnings from below and above, respectively. A modified bisection method is used to search for the new location parameter that yields the desired thinning volume. The proposed algorithm is demonstrated in examples by using experimental forest datasets. A stand-alone program called Weibull_thinning is downloadable at http://www.it.abo.fi/suswood/weibull_thinning/.Research highlights▶ A shifting algorithm to compute thinning rates by using the Weibull distribution for thinnings from below and above is presented. ▶ The shifting algorithm complemented the individual tree selection algorithms in published simulators. ▶ A modified bisection method is used to find the root, i.e., the target thinning volume.
A particle acceleration device for implanting DNA material into plant cells using a timed burst of pressurized helium gas was developed. The device did not require the use of consumable materials (other than helium and microparticles), as used in some similar systems, and was thus easier and less expensive to operate. The system was designed to provide more precise control of the duration of the helium burst and of pressure differentials to ensure more reproducible results. Safety interlock circuitry was incorporated. The device was found to be efficient for delivery of DNA into alfalfa and soybean cell cultures.
A relational database was developed for the agricultural chemical use data collected by the US Department of Agriculture, National Agricultural Statistics Service since 1990. coldfusion Markup Language was used for the client-side interface and server side process programming. The database is accessible from the Web at URL: http://www.pestmanagement.info/nass. Users can obtain information about agricultural chemical use in the database by search of crop, year, region, and active ingredient. Various agricultural chemical usage statistics are provided as Web tables, dynamically generated US maps, charts and graphs, and downloadable Excel files. We used a centralized software architecture in this project, which is suitable for projects with moderate programming complexity. A distributed approach might be more appropriate for the more complex projects. The current database information, spanning 1990–2001, will be augmented in the future, possibly using an automated updating scheme.
This paper seeks to establish the accuracy of an autonomous vehicle working in a field of transplanted cauliflowers. The main sensing systems, odometry and image analysis, are briefly described as is the control system which is based on a fusion of the two data sources using a Kalman filter. Experiments to establish accuracy are described. These were carried out on four plots of cauliflowers with varying degrees of disruption to the visual scene. The RMS error of vehicle lateral position control was 2- mm, while the RMS error of estimated vehicle position was about 10 mm. Little effect of the disruption on position control was observed. It is concluded that these accuracies would be sufficient to control a vehicle and an associated crop treatment device but that improvements to the vehicle controller would make the control of the treatment device easier.
A local position measurement system based on radar technology was set-up in a dairy cow free-stall barn. This system could potentially track up to 16,000 individual objects at a frequency of 300 position estimates/s. We describe the general steps for achieving positioning estimates and the transponder developed to be suitable for dairy cows. Measurements at fixed positions and data of dynamic circular measurements are provided, showing that estimates of the location of a transponder were within ≤0.5 m, regardless of whether it was moving or not. Such accurate position information can be used to track cows and to record their travel paths and their use of different areas of the barn. In addition, we tested the system's suitability for monitoring and quantifying social interactions. Though displacements of one cow by another seemed to result in characteristic patterns of changes in the relative distance between the two cows, most of the displacements did not follow this pattern closely enough to allow the automatic detection of displacements. By contrast, we show that the proximity between two cows recorded automatically with the positioning measurement system correlated well with the proximity recorded by direct observation of the cows, and provided a more detailed and exact record over the same period of time. There were no indications that wearing the transponder restricted the behaviour of the cows. In conclusion, the results of our evaluation suggest that the radar-based position measurement system is a useful tool for simultaneously recording the positions of all animals in large dairy-cow herds with great accuracy.
This paper presents a novel image analysis scheme for accurate detection of fruit blemishes. The detection procedure consists of two steps: initial segmentation and refinement. In the first step, blemishes are coarsely segmented out with a flooding algorithm and in the second step an active contour model, i.e. a snake algorithm, is applied to refine the segmentation so that the localization and size accuracy of detected blemishes is improved. The concept and the formulation of the snake algorithm are briefly introduced and then the refinement procedure is described. The initial tests for sample apple images have shown very promising results.
The study analyses the possibility of improving the automated monitoring of dairy cows by combining the data given by various measurement systems already existing on farms. On a dairy farm where two groups of cows were monitored by different commercial systems, all the measured parameters were collected over 5 months: group A was milked in a traditional parlour equipped with instruments measuring milk production, flow and animal activity; group B was milked by an AMS (automatic milking system) measuring milk production and flow, milk electrical conductivity (per quarter), and animal activity. For each group all the monitoring systems were connected in a network and their data managed by means of a dedicated software. The acquired parameters were first treated to obtain alarms when their standard deviation exceeded a pre-determined threshold. All the animals giving such alarms were then inspected by the farm personnel and the respective normal or not normal (oestrus or pathology) conditions ascertained. Afterwards two models were developed aimed at detecting the animals’ abnormalities: one based on linear discriminant analysis, one based on fuzzy logic. The reliability of these models in detecting the relevant animal conditions was verified by comparing the alarms given by each method with the results of the farm observations. Both models were not very accurate in detecting specific abnormalities, but the model based on fuzzy logic was very effective in detecting general abnormal statuses and was also capable of producing warnings on so far undetected abnormalities in advance.
A comprehensive computerized measurement and data acquisition system was developed to collect dynamic data relating to thermal environment profiles, energy use, operational characteristics, and animal performance of four field research broiler houses (12 × 121 m each). Although the basic components of the system consisted of available industrial electronic and mechanical products, certain design and application features involved were noteworthy and could be of reference value to those who wish to conduct similar field measurements.
In this study an online information and documentation system for the performance data of a forage harvester was developed and tested. A data acquisition system with positioning sensing and a communication module were integrated into the harvester. The data were transferred from the mobile equipment to the co-operative's control centre in two ways: short message service (SMS) and manually. The following online information was recorded: performance data (operation speed, location, harvested yield, …), machine settings (knife drum speed, …) and machine warnings (oil levels, oil pressure, oil temperature, …). Harvester position on the maps was displayed on a monitor installed in the cab. Harvested area was calculated from the field patterns registered by global positioning system (GPS). It was necessary to adapt the existing cartography to the reality of the co-operative's land. In the first design of the mounted prototype the operator's ease of use and the reliability of the system were analyzed. At this stage operation and ergonomic improvements were made. An evaluation was done by comparing the costs of processing the current information with the costs following the implementation of the new system. In a second investigation a first analysis was done of the recorded time to harvest each field and then regression lines were plotted to compare the field capacity value collected by the system with the field size and the crop yield. Correlations between the field capacity of the forage harvester, the area of the plot and the crop yield were found in these first tests.
A microprocessor-based system was constructed to control experimental conditions in the study of the moisture content of agricultural products. The equipment also recorded the condition of the air and the sample weights during the thin-layer drying tests for these products. This paper describes the hardware and software which were developed for use in the study of the properties of parboiled rice. Two samples were studied simultaneously at 13 combinations of relative humidity and temperature. The drying conditions were held constant enough that the variation in conditions in the drying chamber was shown to have no measurable effect on the thin-layer drying data, producing data repeatable to 0.001 moisture content dry basis.
To cope with future developments in glasshouse climate control, a distributed computer system is installed at the GCRS. The hard- and software of the system are described. The system has four types of computers networked together by Ethernet. It controls and collects data from eight glasshouse blocks with over 70 different compartments. The advantages of this system are: reliability, speed, flexibility, easy servicing, user-friendliness and easy expansibility.
This paper presents methodology developed for knowledge acquisition for crop management expert systems. The proposed methodology is described through an extended waterfall model for knowledge acquisition. The way in which the methodology was implemented is presented, and the experience gained is discussed. Although the methodology has evolved through the development of an expert system for cucumber seedling production, it can be used for other crops. A field prototype of this expert system was implemented and is currently being tested in a real environment.
This paper gives a general discussion of knowledge acquisition and formalization using structured induction, and illustrates the application of induction with an example. The example is taken from actual work on a knowledge based system for malting barley crop management, where the ID3 algorithm was used to derive rules and generate a decision tree to make the irrigation decision. The objective of the paper is to give the reader a working understanding of the principles of induction and the mechanics of the ID3 algorithm.
A data acquisition system fast enough to facilitate the recording of the primary phases of chlorophyll-α fluorescence transients has been developed. Based on a microcomputer equipped with an analog to numeric converter, this system permits the acquisition of a data point every 43 ms or 0.13 ms, depending on the program used. In this last case, obtained resolution permits to locate phenomena which occur during the first 400 ms of the measurement on the kinetic curve. An example of usage and details about programs are given.
This article describes the interfacing of National Semiconductor's MM58167 real-time clock/calendar to a 6502 microprocessor-based SYM-1 microcomputer. The functions of the clock, details for interfacing to a microcomputer, programming required, and use of its special features are described.A real-time clock/calendar is an essential part of many microcomputer data acquisition and control systems. It provides a 24-hour clock and an accurate interval timer for data acquisition and control functions. The main advantage of a real-time clock is that it keeps track of true time independent of software execution speeds.The MM58167 clock is a CMOS integrated circuit in a 24-pin, dual-in-line package. It is designed for direct connection to the address and data buses of most common microcomputers. This application involved interfacing the clock with a SYM-1 6502-based microcomputer. The clock has eight counters and corresponding latches that contain months through thousands of seconds. The latches can be used for alarm-type functions. Low power battery backup is available through a special ‘power down’ mode. The clock has two interrupt outputs that can be used for control functions.
Decision support systems (DSSs) can play a powerful role in natural resource management (NRM), by allowing more effective and collective use of information in addressing complex and often poorly structured questions. CSIRO Tropical Agriculture, in Townsville, Australia, is developing a DSS generator that provides a flexible environment for the construction of decision support tools that assist in assessing the implications of proposed policies or management actions. In this context, the POSEIDON system was designed to help resource managers with the problem formulation phase of building a DSS, i.e. identifying specific issues that need to be analysed to provide an answer to a broad NRM question. This is achieved by a form of knowledge acquisition from free text, which performs intelligent analysis of NRM documents. This article describes the design of POSEIDON and its application in NRM problem formulation.
An infrared telemetry and telecontrol system was employed in a project of automatic irrigation scheduling based on soil moisture sensing. It was used to transmit continuous soil moisture potential from a remote field planted with wheat to a base station for analysis. In the base station, where a microcomputer was housed, the field information was processed through water management software developed for this purpose to decide when to start or stop irrigation based on a predetermined threshold for soil water potential. When start or stop irrigation was decided by the computer, a telecontrol signal was sent through the infrared system to the pumping station to deliver water or to stop it.
Recent studies have shown that satellite data can be used in the detection and monitoring of potential outbreak areas of the Australian plague locust. However, the routine monitoring of such areas using Landsat MSS data is precluded by the high cost of the data, although it is still used selectively for forecasting.An alternative approach has been to make use of lower-cost meteorological satellite data with lower spatial resolution, for example that of the NOAA and GMS satellites, which provide an acceptable compromise between frequency of monitoring, relevant data and cost.This paper describes the acquisition of GMS LRFAX and NOAA APT data and other relevant meteorological data at the Australian Plague Locust Commission (APLC) Headquarters in Canberra and the use of the data in the APLC.
A patented gestating sow feeding system for loose housing was developed at the Iowa State University Rhodes Research Farm, Rhodes, IA. The system combined electronic identification of sows and animal weighing with computerized analysis of collected data. Comparison of calculated average daily weight gains with a target average daily gain determined the sows access to one of two possible feed formulations. A computer monitored and controlled the traffic through the system. The system allowed self-feeding of a small group of sows at the same time.
Forest management planning is facing new objectives and diversified data sources. To succeed in the new context, a forest management planning framework should support integration of the new goals, knowledge, and technology as well as embrace multiple scales. The aim of the SIMO framework is to develop a hierarchical, extendable simulation and optimization framework for forest management planning. Current implementation includes a forest growth and yield simulator which is adaptable with respect to the components of a simulation; data, growth and operation models that modify the data, and the control structures between the data and the models. The simulation framework components implemented in XML include the hierarchical structures for data and simulation descriptions, and an extendable model base. To achieve flexibility and reusability, the components are connected through a common ontology, again defined in XML. The article includes two use cases demonstrating the adaptability of the simulation framework, which is available as open source software.
Automated grading of agricultural products suffers from the time varying, error-prone feature space used. Classification errors can be minimized by choosing appropriate class boundaries. However, changes in the statistics of the features in the produce stream cause these optimal boundaries to change. Modern sorting machines use a multitude of features which complicates the optimization of the class boundaries. Automated optimization can be accomplished through identification of distinct, discrete populations within the produce stream, and training of an optimal classifier for each population The adaptive algorithm has been simulated in software and aspects of the algorithm are explored.
Counting the number of flowers in a plant is an example of agricultural quality inspection issues in which a simple 2D image of the product does not suffice. It is essential to see the object under inspection from multiple viewpoints to get a clear estimation of the quality of the product. In order to use multiple viewpoints to obtain a proper quality assessment, a multi-target tracking algorithm that accurately identifies relevant features of the product under inspection is proposed in this paper. The approach is illustrated with an experiment in which the flowers in a number of plants are counted. For the presented method, the plant rotates in front of a camera and a number of consecutive images is taken. The tracking algorithm detects, predicts, and matches the (partially occluded) flowers in the image. The experiments provide a proof of principle of the proposed method. The conclusion of this paper is that the presented multi-target tracking algorithm can be used to solve many similar quality assessment issues for agricultural objects.
Adaptive environmental management (AEM) deals with the complex interactions of social, environmental, and economic systems, and incorporates the knowledge, values and opinions of many stakeholders and experts. AEM has traditionally been centered on a structured series of workshops to define possible management actions and the indicators used to assess the actions, and generally leads to the construction of a model for exploration of the management options in a consensus-building exercise. There is an optimal group size for the workshop process; however this limits the ideal of including all stakeholders in the process. There are also time and cost constraints on the workshop approach. A new approach to the AEM process has been developed based on the concept of a virtual meeting space, in which stakeholders and experts can interact in a distributed system development process over an extended period of time. The AEM system is based on Java applets, which interact over the world wide web. These applets function as graphical knowledge elicitation tools. A stand-alone version run on a laptop computer by an extension specialist permits use in situations where there is no Internet access, or by individuals or groups who do not have the required computer experience.
The identification of a mathematical model capable of describing the behaviour of animals given input such as feed has great potential for behavioural control purposes. Such models will allow to make predictions which are fundamental to any closed loop control such as control of the feeding. This paper investigates the problem of mathematically modelling animal behaviour. An observer Kalman filter identification method was successfully applied to input–output data and two models representing the hypotheses that animals are actively feeding and the hypotheses that animals are inactive were identified. The input and output of each of the identified models were feed dry matter offer and the pitch angle of the neck, respectively. The pitch angle of the neck of the animal was successfully measured and aggregated by a ZigBee-based wireless sensor network. Two fourth-order models describing the dynamics of an animal in the active and inactive behaviour modes showed good performance in terms of prediction error, cross-correlation between the residual and the output as well as cross-correlation between the residual and the input with 99% confidence interval. A multiple-model adaptive estimation approach was applied to determine the likelihood of each of the two models being the correct model for a specific input of dry matter feed. The average classification success rate was 87.2% for the whole experiment.
Two classes of feedback controllers, proportional-integral control and adaptive control, were applied to a counterflow solid particle heat exchange prototype. The primary objective was to optimize process start-up performance of the heat exchanger. The two most significant factors affecting the controllers were: (a) limited input control effort in terms of energy; and (b) deadtime of the process which was a function of the heat exchanger design. The adaptive controller, based on parameter estimation and a digital control law derived using controller synthesis, outperformed the conventional controller during start-up by as much as 11% with respect to a performance measure comprised of both error and energy components. Proper design and implementation of the adaptive controller was crucial for successful regulation.
An irrigation scheduling tool was developed around a previously developed system that adjusts key parameters influencing the water balance components of the PNUTGRO crop model. These parameters were adjusted as the system was used based on soil water sensor responses to drying. An expert system determined which sensor readings were valid before they could be used to adjust parameters. A field test of the irrigation scheduling algorithms indicated that sensors could be relied on less as better predictions of soil water status were made. Comparisons of two very different sensor-based scheduling environments (one for Florida and one for Virginia) indicated potential improvements to the algorithms.
The concept of precision agriculture, based on information technology, is becoming an attractive idea for managing natural resources and realizing modern sustainable agricultural development. It is bringing agriculture into the digital and information age. The practice has smoothly extended into some developing countries. The basic principle of managing soil and crop variability within a field is certainly not new. It was named ‘intensive and meticulous cultivation’ by the Chinese people and has been long regarded as the cream of Chinese conventional agriculture. Toward the new millennium, China is preparing to follow the experience of the developed world and is starting to investigate the new technology. This paper considers the possible adoption of precision agriculture for developing countries and ideas in conducting the practice in China.
A survey conducted among 199 commercial farmers in Natal Province, South Africa, showed that 95 respondents (48%) owned personal computers and were using them as decision-aids in farm management. Computers were rated highly for keeping financial records, for business planning purposes, livestock record-keeping and payroll preparation. Most computer time was spent on keeping financial records (a median of 2.75 hours per week) and maintaining livestock records (a median of 2 hours per week). Most computer owners rated the computer highly in terms of saving time and providing better (up-to-date, more usable, easy to access) information than “hand” records. Time taken for the computer to become useful ranged from immediately to 36 months. Respondents reported use of 43 software packages.The main reasons given by farmers for not owning a personal computer include the cost of a computer system (35%), lack of confidence to operate a computer (30%) and insufficient time to operate a computer (23%).Results of a multivariate logit analysis indicated that farmer's education, gross farm income (size of business), proportion of farmland rented, self-rating of financial management skills, and off-farm employment had a positive impact on computer adoption, while farmer's age and a beef enterprise had a negative effect.
The development of research on cereal aphid damage to winter wheat is described, from early field-cage work on Sitobion avenae through a research simulation model to the development of a computer-based Viewdata advisory system for cereal aphid control. Aphid control decisions in the U.K. have frequently been irrational and uneconomic in the past and appear still to be based on inadequate information. A dynamic advisory package based on the economics of insecticide application and the aphid yield loss/growth stage relationship has been developed for ‘Farmlink’ subscribers on ‘Prestel’, British Telecommunications' Viewdata service.
A patented gestating sow feeding system for loose housing was developed at the Iowa State University Rhodes Research Farm, Rhodes, IA. The system combined electronic identification of sows and animal weighing with computerized analysis of collected data. Comparison of calculated average daily weight gains with a target average daily gain determined the sows access to one of two possible feed formulations. A computer monitored and controlled the traffic through the system. The system allowed self-feeding of a small group of sows at the same time.
Forest management planning is facing new objectives and diversified data sources. To succeed in the new context, a forest management planning framework should support integration of the new goals, knowledge, and technology as well as embrace multiple scales. The aim of the SIMO framework is to develop a hierarchical, extendable simulation and optimization framework for forest management planning. Current implementation includes a forest growth and yield simulator which is adaptable with respect to the components of a simulation; data, growth and operation models that modify the data, and the control structures between the data and the models. The simulation framework components implemented in XML include the hierarchical structures for data and simulation descriptions, and an extendable model base. To achieve flexibility and reusability, the components are connected through a common ontology, again defined in XML. The article includes two use cases demonstrating the adaptability of the simulation framework, which is available as open source software.
Automated grading of agricultural products suffers from the time varying, error-prone feature space used. Classification errors can be minimized by choosing appropriate class boundaries. However, changes in the statistics of the features in the produce stream cause these optimal boundaries to change. Modern sorting machines use a multitude of features which complicates the optimization of the class boundaries. Automated optimization can be accomplished through identification of distinct, discrete populations within the produce stream, and training of an optimal classifier for each population The adaptive algorithm has been simulated in software and aspects of the algorithm are explored.
Two classes of feedback controllers, proportional-integral control and adaptive control, were applied to a counterflow solid particle heat exchange prototype. The primary objective was to optimize process start-up performance of the heat exchanger. The two most significant factors affecting the controllers were: (a) limited input control effort in terms of energy; and (b) deadtime of the process which was a function of the heat exchanger design. The adaptive controller, based on parameter estimation and a digital control law derived using controller synthesis, outperformed the conventional controller during start-up by as much as 11% with respect to a performance measure comprised of both error and energy components. Proper design and implementation of the adaptive controller was crucial for successful regulation.
Adaptive environmental management (AEM) deals with the complex interactions of social, environmental, and economic systems, and incorporates the knowledge, values and opinions of many stakeholders and experts. AEM has traditionally been centered on a structured series of workshops to define possible management actions and the indicators used to assess the actions, and generally leads to the construction of a model for exploration of the management options in a consensus-building exercise. There is an optimal group size for the workshop process; however this limits the ideal of including all stakeholders in the process. There are also time and cost constraints on the workshop approach. A new approach to the AEM process has been developed based on the concept of a virtual meeting space, in which stakeholders and experts can interact in a distributed system development process over an extended period of time. The AEM system is based on Java applets, which interact over the world wide web. These applets function as graphical knowledge elicitation tools. A stand-alone version run on a laptop computer by an extension specialist permits use in situations where there is no Internet access, or by individuals or groups who do not have the required computer experience.
Counting the number of flowers in a plant is an example of agricultural quality inspection issues in which a simple 2D image of the product does not suffice. It is essential to see the object under inspection from multiple viewpoints to get a clear estimation of the quality of the product. In order to use multiple viewpoints to obtain a proper quality assessment, a multi-target tracking algorithm that accurately identifies relevant features of the product under inspection is proposed in this paper. The approach is illustrated with an experiment in which the flowers in a number of plants are counted. For the presented method, the plant rotates in front of a camera and a number of consecutive images is taken. The tracking algorithm detects, predicts, and matches the (partially occluded) flowers in the image. The experiments provide a proof of principle of the proposed method. The conclusion of this paper is that the presented multi-target tracking algorithm can be used to solve many similar quality assessment issues for agricultural objects.
The identification of a mathematical model capable of describing the behaviour of animals given input such as feed has great potential for behavioural control purposes. Such models will allow to make predictions which are fundamental to any closed loop control such as control of the feeding. This paper investigates the problem of mathematically modelling animal behaviour. An observer Kalman filter identification method was successfully applied to input–output data and two models representing the hypotheses that animals are actively feeding and the hypotheses that animals are inactive were identified. The input and output of each of the identified models were feed dry matter offer and the pitch angle of the neck, respectively. The pitch angle of the neck of the animal was successfully measured and aggregated by a ZigBee-based wireless sensor network. Two fourth-order models describing the dynamics of an animal in the active and inactive behaviour modes showed good performance in terms of prediction error, cross-correlation between the residual and the output as well as cross-correlation between the residual and the input with 99% confidence interval. A multiple-model adaptive estimation approach was applied to determine the likelihood of each of the two models being the correct model for a specific input of dry matter feed. The average classification success rate was 87.2% for the whole experiment.
An irrigation scheduling tool was developed around a previously developed system that adjusts key parameters influencing the water balance components of the PNUTGRO crop model. These parameters were adjusted as the system was used based on soil water sensor responses to drying. An expert system determined which sensor readings were valid before they could be used to adjust parameters. A field test of the irrigation scheduling algorithms indicated that sensors could be relied on less as better predictions of soil water status were made. Comparisons of two very different sensor-based scheduling environments (one for Florida and one for Virginia) indicated potential improvements to the algorithms.
A survey conducted among 199 commercial farmers in Natal Province, South Africa, showed that 95 respondents (48%) owned personal computers and were using them as decision-aids in farm management. Computers were rated highly for keeping financial records, for business planning purposes, livestock record-keeping and payroll preparation. Most computer time was spent on keeping financial records (a median of 2.75 hours per week) and maintaining livestock records (a median of 2 hours per week). Most computer owners rated the computer highly in terms of saving time and providing better (up-to-date, more usable, easy to access) information than “hand” records. Time taken for the computer to become useful ranged from immediately to 36 months. Respondents reported use of 43 software packages.The main reasons given by farmers for not owning a personal computer include the cost of a computer system (35%), lack of confidence to operate a computer (30%) and insufficient time to operate a computer (23%).Results of a multivariate logit analysis indicated that farmer's education, gross farm income (size of business), proportion of farmland rented, self-rating of financial management skills, and off-farm employment had a positive impact on computer adoption, while farmer's age and a beef enterprise had a negative effect.
The concept of precision agriculture, based on information technology, is becoming an attractive idea for managing natural resources and realizing modern sustainable agricultural development. It is bringing agriculture into the digital and information age. The practice has smoothly extended into some developing countries. The basic principle of managing soil and crop variability within a field is certainly not new. It was named ‘intensive and meticulous cultivation’ by the Chinese people and has been long regarded as the cream of Chinese conventional agriculture. Toward the new millennium, China is preparing to follow the experience of the developed world and is starting to investigate the new technology. This paper considers the possible adoption of precision agriculture for developing countries and ideas in conducting the practice in China.
The development of research on cereal aphid damage to winter wheat is described, from early field-cage work on Sitobion avenae through a research simulation model to the development of a computer-based Viewdata advisory system for cereal aphid control. Aphid control decisions in the U.K. have frequently been irrational and uneconomic in the past and appear still to be based on inadequate information. A dynamic advisory package based on the economics of insecticide application and the aphid yield loss/growth stage relationship has been developed for ‘Farmlink’ subscribers on ‘Prestel’, British Telecommunications' Viewdata service.

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