Computer Technology in Agriculture

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2.1 Computer Technology in Agriculture

Agriculture, in 21st century has gone far away from just about crop production or livestock farming and allied activities. Ecological factors which adversely affect to the environment have to be considered in current agricultural procedures. Therefore eco-friendly sustainable agriculture is currently the spotlight in all over the world, and the application of Computer Technology in Agriculture (CTA) has become more and more important in order to rescue the environment. Enhancing the Agricultural Information Technology (AIT) has been the major target of many developed and developing countries in recent times in order to achieve the concept of low costs and high income by scientifically managing the farming activities.

Internet and related applications (web based) play a leading role in agriculture in terms of providing information to farmers and other people who involved in agricultural business (Arumapperuma, 2008). Several kinds of agricultural forums and knowledge based learning repositories on the Internet provide variety of information of all kinds of agricultural topics (Edge et al., 2011). Some examples can be found in the web as ICT in Agriculture (, NAFIS (, AgNIC (, KAiNet (, AGIS (, GIEWS Food Price Data and Analysis Tool (, FarmerNet (, GAIN ( Farmers can connect with experts through these services and solve their problems and exchange knowledge in several ways. Computer technology has directly been used as management software especially in livestock farming sector and crop production sector as well with running under database management systems (DBMS). These kinds of comprehensive management software normally provide services for record keeping, simulation models (e.g. weather forecasting, pest insect outbreak) and estimation of profit and productivity. Applications of computer technology in agriculture include simulation models and decision-support systems for agricultural production. Technologies such as Geographic Information System (GIS), Remote Sensing (RS) and Global Positioning System (GPS) also play a leading role in farmland assessment which uses to extract information like soil conditions, weather conditions, etc. Technologies such as GPS can also be used for irrigation monitoring, field mapping, soil sampling, machinery guiding and crop scouting. Another emerging field in computer technology in agriculture is automated farm machinery. Controlling of farm machinery has obtained a higher position in terms of consistency and reliability because of their autonomous computerized systems. Crop seeding and fertilizer application, robotic harvesters, automated feeding systems and computerized milking machines are already being used. Various researches conducted by different scientists in different countries on application of computer technology in agriculture can be found in Li and Zhao (2008, 2009 and 2010).

2.1.1 E-Agriculture

E-Agriculture is a recent emerging field of agricultural information technology which aimed on innovative applications of information and communication technologies (ICTs) in agriculture for eco-friendly sustainable agricultural development with special focus on rural areas. Agriculture related technological fields such as agricultural informatics and agricultural development and business are also included in E-Agriculture (Mangstl, 2008). This concept was populated with the dissemination of results from a global survey carried out by the Food and Agriculture Organization of the United Nations (FAO) in 2006. World Summit on the Information Society (WSIS) held in 2003 and 2005 has declared e-Agriculture concept considering in their action lines as a major priority for the sustainable agriculture and rural development (World Summit on the Information Society, 2003a, 2003b). Action line C7 of WSIS outcome document explains this as to ensure the systematic dissemination of information using ICTs on agriculture, animal husbandry, fisheries, forestry and food, in order to provide ready access to comprehensive, up-to-date and detailed knowledge and information, particularly in rural areas (WSIS Plan of Action, 2003). The total responsibility of organizing activities related to the action line C7 under ICT applications is being assigned to FAO of United Nations.

2.1.2 Agricultural Modeling and Simulation

Balancing agricultural processes in a sustainable way has increasingly been a great challenge. Although modelling agricultural systems has been dominated among agriculturists, environmentalists and technical specialists, concepts to address the wide range of issues arising in agriculture are still scarce. Complex agricultural systems can be simplified dividing into many organizational levels. It could be from the individual components within a single plant or an animal to large scale crop or livestock farms or a whole agricultural region. However the core of an agricultural system is concerned with plants and therefore the basic level that is of main interest to the agricultural scientists who are dealing with the modelling is the plant. Models of agricultural systems generally are mathematical equations which could be represented the reactions occurring within the plant and the interactions between the plant and the environment. Hence, within the plant the scientists still need focusing on other factors to integrate with from a spectrum of disciplines such as biology, physics, chemistry, economics and mathematics and to specify interactions of different nature such as physical (weather, light and soil moisture), chemical (CO2 concentration and nutrients) and biological (pests, diseases, weeds and other plants in the community) (Cheeroo-Nayamuth, 1999; Stockle 1989). Agricultural models are built for specific purposes and they are not universal unlikely other fields such as physics and engineering. Since the core of an agricultural system is concerned with plants, crop models have been dominated in agricultural systems modelling. Most of the crop models are built specifically to simulate a particular crop and then forecast the potential of the harvestable yield (Cheeroo-Nayamuth, 1999). Since the weather data are major input or influencing factor for crop growth simulation, weather forecasting models also play an important role in agricultural systems modelling and have most likely been developed simultaneously with crop models. However, models with different levels of complexity have been developed depending on the amount of knowledge base data existing in a particular field. Several crop models have been developed by various scientists and the most referred are namely, DSSAT (Jones et al., 2003), CERES (Jones and Kiniry, 1986), EPIC (Williams et al., 1984), SUCROS (Spitters et al., 1997) APSIM (McCown et al., 1996) and AquaCrop (Steduto et al , 2009).

2.2 Wheat

2.2.1 Introduction

Wheat (Triticum spp) is the most widely grown cereal crop in the world. It is counted among the “big three” cereal crops with over 674 million tonnes (Mt) of annual production, and it is the third largest cereal crop production in the world, after maize and rice (Table 2.2). For example, in 2012, the total world production was about 674.9 Mt compared with rice (718 Mt) and maize (875 Mt) (FAOSTAT, 2013). Wheat has been successful in terms of its adaptability and high yield. Because wheat is a hardy crop that can grow in a wide variety of environmental conditions in different geographical locations than any other commercial food. Wheat is cultivated in large-scale and can be harvested using mechanical combine harvesters. Long-term storage could also be ensured if the water content is kept below 15% dry weight and pest is effectively controlled (Shewry, 2009). According to the FAO statistical yearbook, about 65% of the wheat crop is used for food, it is currently second to rice as the main human food crop, and 17% for animal feed. Another 12% is used in industrial applications with special focus on biofuels. World trade in wheat is obtained a higher position since wheat is the leading vegetable protein source in human food. Wheat is also having higher protein content when compared to other major cereal crops such as maize and rice, and provides more nourishment for humans. Wheat grain is easily converted into flour for making edible foods such as bread, noodle, biscuit, cookie, cake and pasta. Wheat flour is also used to make beer and other alcoholic beverages.

According to FAO statistics, in 2012, China is the leading wheat producer in the world with 120.6 Mt while India (94.9 Mt) and USA (61.8 Mt) were second and third producers respectively (Table 2.1). Within China, wheat is the second most significant grain crop in terms of human food after rice. In China, wheat is grown in most parts of the country especially in the North. Wei and Fen River valleys on the Loess plateau are most popular wheat lands in China in addition to the lands in Sichuan, Hubei and Jiangsu provinces.

Table 2.1 Top 10 wheat producing countries in the world (FAOSTAT, 2013)



Production (Mt)








United States of America






Russian Federation

















Table 2.2 Top 5 cereal production in the world (FAOSTAT, 2013)



Production (Mt)
















2.2.2 Insect Pests of Wheat

Wheat is attacked by many insect pests. But, fortunately, only a few insect species are potentially important, causing severe damage or outbreak over large geographical areas. Most of the insect pest species are only occasional pests and are not causing pest outbreak (Prescott et al., 1986). This section discusses only major insect pests including aphids, stink bugs, armyworms, cutworms, cereal leaf beetle, thrips, hessian fly, wheat stem maggot, white grubs, wireworms. In addition to these pests, there are others such as sawfly, slugs, snails, grasshoppers, crickets and mites, who can attack wheat plant, but the damage is not severe.