Agriculture

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Agriculture is a vast industry that includes plant and animal production, comprehensive support and infrastructure systems, and food and fiber processing. Key application areas of computers in agriculture include record keeping, decision-making, control, and research. The diversity of agricultural enterprises and associated products requires a variety of computer hardware and software solutions, from specialized software packages to computerized components for traditional machinery and equipment. A particular challenge to designers and manufacturers of computerized agricultural machinery is to make computers, analog/digital (A/D and D/A) converters, terminals, and connections unaffected by environmental conditions. Agricultural equipment experiences extremes of dust, rain and high humidity, vibration, and temperatures.

Recordkeeping is vital in any business. Agricultural enterprises use computers for common financial and business tasks such as inventory, payroll, accounting, and taxes. Because there are many differences between agricultural businesses and other businesses (with regard to tax structure, labor management, insurance, and inventory, for example), software packages have been tailored specifically for agriculture. Spreadsheet and database templates are common, but specific application programs also exist.

Livestock and crop production farms have unique needs for records. For example, crop production fields have numerous descriptors and variables that should be recorded (e.g., soil type, drainage, slope, pH, nutrient status); databases have been developed to deal with this information. Precision agriculture (sometimes called site-specific farming) requires such data to be recorded not only for fields, but for locations within fields. Because they provide a combination of database and drawing functions, Geographic Information Systems (GIS) are needed to handle the large amount of data. Global Positioning Systems (GPSs) work with computerized machinery in the field to correlate crop and soil conditions with exact locations on the Earth's surface. Because soil and crop conditions can vary tremendously within fields, this capability can improve the environmental friendliness of farming and improve profitability.

Similarly, livestock farms track individual animals, storing and evaluating information such as age, growth rate, milk production, health records, offspring productivity, and reproductive cycle status. Unlike with large corporations that employ computer scientists, farmers generally do not have or cannot hire the expertise to customize relevant software; therefore, there is a market for software products suitable for those who are mostly novice computer users.

Computers can be used to assist agricultural decision-making through such tools and techniques as optimization, simulation, fuzzy logic, expert systems, and computer aided drafting (CAD). A common problem to be solved on crop farms is the selection of the optimal field machinery set. Equipment that is too large will result in poor use of capital and labor; equipment that is too small may result in poor timing of operations and consequential loss of crop value. The equipment must function as an interdependent set; operations must flow in a sequential and timely manner. Simulations can model farm and machine events over time to predict what would happen if particular machinery sets were chosen. Important factors include weather, soil type, and desired field operations. Optimization techniques such as linear or non-linear programming that minimize cost subject to reasonable constraints (e.g., labor availability, frost dates) can help improve profitability.

Increasing regulations require that nutrient management plans be developed, implemented, and monitored. While much of this is recordkeeping in nature, decision tools are used to project future impact and profits, given past performance and conditions. Integrated pest management (IPM) also takes a holistic view of production and optimizes the timing and rates of chemical application (if necessary) or the use of alternative measures. IPMrequires projection of consequences with various strategies so that the optimum strategy can be implemented. IPM models include simulation of pest population dynamics and rule-based expert systems techniques.

In poultry and livestock production, a major cost of production is feed, often exceeding 35 percent of gross receipts. Minimizing feed cost is a classic linear or non-linear optimization problem. Optimization methods can help determine the least costly ingredient package in a diet subject to constraints including energy, protein, intake limitations, minerals, and fiber requirements.

Landscape design and construction, which is also an agriculture-related enterprise, can benefit from computer aided drafting and drawing packages that help designers generate and illustrate concepts to clients. By providing projection of individual plant growth, good packages can show how plants on a site will look years after installation.

Control of machinery by computers can provide consistency and reliability unmatched with human operation. Controller area networks (CANs) are common on tractors and self-propelled equipment; these CANs reduce wiring complexity and allow one or more on-board chips to control machine functions such as engine controls, transmission, and hydraulic power output. CANs use serial communications like other networks, but they havea specific data structure to facilitate interchange among vendors of CAN compatible devices and diagnosis of problems.

Computers are used increasingly to control seeding or chemical application rate automatically in fields. This requires GIS and GPS data input, computer algorithms to generate control signals (rule or formula based), and relays and amplifier cards to power mechanisms that perform the desired functions.

Support industries for inputs to production agriculture include manufacturing and delivery of machinery, feed, and fertilizer. After the farm production of raw products, there is food and fiber manufacturing. Programmable logic controllers (PLCs) are used in all of these agricultural industries, as well as on farms. PLCs can perform intelligent on/off and proportional control on machines that meter, grind, weigh, blend, cut, and weld.

Research in agriculture requires some uses of computers not used in other aspects of agricultural work. Very sophisticated simulation models address issues such as crop growth, animal nutrition, water flow in soil, thermal and physical behavior of agricultural products, machinery performance, and integrated farm systems.

As with most areas of research, good agricultural research requires computers for statistical analysis of data, generation of mathematical models, and control of research devices. Instrumentation to measure temperature, flow, pressure, electrical conductivity, and strain also requires computers or data loggers.

Dennis R. Buckmaster

Biology; Geographic Information Systems; Molecular Biology; Weather Forecasting.

National Research Council. Precision Agriculture in the 21st Century: Geospatial and Information Technologies in Crop Management. Washington, DC: National Academy Press, 1998. Also available at <http://www.nap.edu/catalog/5491 .html>.

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Production Agriculture 3, no. 2 (1990): 212-219.

Zazueta, Fedro S., and Jiannong Xin, eds. Computers in Agriculture. St. Joseph, MI: American Society of Agricultural Engineers, 1998. Also available at <http://wcca.ifas.ufl.edu/ E;.

Agricultural Software Page. Agri-Publications, Inc. <http://www.agdownload.com E;

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