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    Computer Technology in Agriculture Essay

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    2.1 Computer Technology in Agriculture

    Agribusiness, in twenty-first century has gone far off from merely about harvest production or farm animal agriculture and allied activities. Ecological factors which adversely affect to the environment have to be considered in current agricultural processs. Therefore eco-friendly sustainable agribusiness is presently the limelight in all over the universe, and the application of Computer Technology in Agriculture ( CTA ) has become more and more of import in order to deliver the environment. Enhancing the Agricultural Information Technology ( AIT ) has been the major mark of many developed and developing states in recent times in order to accomplish the construct of low costs and high income by scientifically pull offing the agriculture activities.

    Internet and related applications ( net based ) play a prima function in agribusiness in footings of supplying information to husbandmans and other people who involved in agricultural concern ( Arumapperuma, 2008 ) . Several sorts of agricultural forums and cognition based larning depositories on the Internet provide assortment of information of all sorts of agricultural subjects ( Edge et al. , 2011 ) . Some illustrations can be found in the web as ICT in Agriculture ( www.ictinagriculture.org ) , NAFIS ( www.nafis.go.ke ) , AgNIC ( www.agnic.org ) , KAiNet ( www.kainet.or.ke ) , AGIS ( www.agis.agric.za/mis ) , GIEWS Food Price Data and Analysis Tool ( www.fao.org/giews/pricetool ) , FarmerNet ( www.farmer.lk/ ) , GAIN ( hypertext transfer protocol: //gain.fas.usda.gov ) . Farmers can link with experts through these services and work out their jobs and exchange cognition in several ways. Computer engineering has straight been used as direction package particularly in farm animal agriculture sector and harvest production sector as good with running under database direction systems ( DBMS ) . These sorts of comprehensive direction package usually supply services for record maintaining, simulation theoretical accounts ( e.g. conditions prediction, pest insect eruption ) and appraisal of net income and productiveness. Applications of computing machine engineering in agribusiness include simulation theoretical accounts and decision-support systems for agricultural production. Technologies such as Geographic Information System ( GIS ) , Remote Sensing ( RS ) and Global Positioning System ( GPS ) besides play a prima function in farming area appraisal which uses to pull out information like dirt conditions, conditions conditions, etc. Technologies such as GPS can besides be used for irrigation monitoring, field function, dirt sampling, machinery guiding and harvest exploratory survey. Another emerging field in computing machine engineering in agribusiness is automated farm machinery. Controlling of farm machinery has obtained a higher place in footings of consistence and dependability because of their independent computerized systems. Crop seeding and fertilizer application, robotic reapers, automated feeding systems and computerized milking machines are already being used. Assorted researches conducted by different scientists in different states on application of computing machine engineering in agribusiness can be found in Li and Zhao ( 2008, 2009 and 2010 ) .

    2.1.1E-Agriculture

    E-Agriculture is a recent emerging field of agricultural information engineering which aimed on advanced applications of information and communicating engineerings ( ICTs ) in agribusiness for eco-friendly sustainable agricultural development with particular focal point on rural countries. Agriculture related technological Fieldss such as agricultural information sciences and agricultural development and concern are besides included in E-Agriculture ( Mangstl, 2008 ) . This construct was populated with the airing of consequences from a planetary study 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 construct sing in their action lines as a major precedence for the sustainable agribusiness and rural development ( World Summit on the Information Society, 2003a, 2003b ) . Action line C7 of WSIS outcome papers explains this as to guarantee the systematic airing of information utilizing ICTs on agribusiness, carnal farming, piscaries, forestry and nutrient, in order to supply ready entree to comprehensive, up-to-date and elaborate cognition and information, peculiarly in rural countries ( WSIS Plan of Action, 2003 ) . The entire duty of forming 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 procedures in a sustainable manner has progressively been a great challenge. Although patterning agricultural systems has been dominated among agriculturalists, conservationists and proficient specializers, constructs to turn to the broad scope of issues originating in agribusiness are still scarce. Complex agricultural systems can be simplified spliting into many organisational degrees. It could be from the single constituents within a individual works or an animate being to big scale harvest or farm animal farms or a whole agricultural part. However the nucleus of an agricultural system is concerned with workss and therefore the basic degree that is of chief involvement to the agricultural scientists who are covering with the modeling is the works. Models of agricultural systems by and large are mathematical equations which could be represented the reactions happening within the works and the interactions between the works and the environment. Hence, within the works the scientists still need concentrating on other factors to incorporate with from a spectrum of subjects such as biological science, natural philosophies, chemical science, economic sciences and mathematics and to stipulate interactions of different nature such as physical ( conditions, visible radiation and dirt wet ) , chemical ( CO2 concentration and foods ) and biological ( plagues, diseases, weeds and other workss in the community ) ( Cheeroo-Nayamuth, 1999 ; Stockle 1989 ) . Agricultural theoretical accounts are built for specific intents and they are non cosmopolitan unlikely other Fieldss such as natural philosophies and technology. Since the nucleus of an agricultural system is concerned with workss, harvest theoretical accounts have been dominated in agricultural systems patterning. Most of the harvest theoretical accounts are built specifically to imitate a peculiar harvest and so calculate the potency of the harvestable output ( Cheeroo-Nayamuth, 1999 ) . Since the conditions informations are major input or act uponing factor for harvest growing simulation, conditions prediction theoretical accounts besides play an of import function in agricultural systems patterning and have most likely been developed at the same time with harvest theoretical accounts. However, theoretical accounts with different degrees of complexness have been developed depending on the sum of cognition base informations bing in a peculiar field. Several harvest theoretical accounts have been developed by assorted scientists and the most referred are viz. , 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 (Triticumspp ) is the most widely adult cereal harvest in the universe. It is counted among the “big three” cereal harvests with over 674 million metric tons ( Mt ) of one-year production, and it is the 3rd largest cereal harvest production in the universe, after corn and rice ( Table 2.2 ) . For illustration, in 2012, the entire universe production was about 674.9 Meitneriums compared with rice ( 718 Mt ) and maize ( 875 Mt ) ( FAOSTAT, 2013 ) . Wheat has been successful in footings of its adaptability and high output. Because wheat is a stalwart harvest that can turn in a broad assortment of environmental conditions in different geographical locations than any other commercial nutrient. Wheat is cultivated in large-scale and can be harvested utilizing mechanical combine reapers. Long-run storage could besides be ensured if the H2O content is kept below 15 % dry weight and plague is efficaciously controlled ( Shewry, 2009 ) . Harmonizing to the FAO statistical yearbook, approximately 65 % of the wheat harvest is used for nutrient, it is presently 2nd to rice as the chief human nutrient harvest, and 17 % for carnal provender. Another 12 % is used in industrial applications with particular focal point on biofuels. World trade in wheat is obtained a higher place since wheat is the taking vegetable protein beginning in human nutrient. Wheat is besides holding higher protein content when compared to other major cereal harvests such as corn and rice, and provides more nourishment for worlds. Wheat grain is easy converted into flour for doing comestible nutrients such as staff of life, noodle, biscuit, cooky, bar and pasta. Wheat flour is besides used to do beer and other alcoholic drinks.

    Harmonizing to FAO statistics, in 2012, China is the taking wheat manufacturer in the universe with 120.6 Mt while India ( 94.9 Mt ) and USA ( 61.8 Mt ) were 2nd and 3rd manufacturers severally ( Table 2.1 ) . Within China, wheat is the 2nd most important grain harvest in footings of human nutrient after rice. In China, wheat is grown in most parts of the state particularly in the North. Wei and Fen River vale on the Loess tableland are most popular wheat lands in China in add-on to the lands in Sichuan, Hubei and Jiangsu states.

    Table 2.1Top 10 wheat bring forthing states in the universe ( FAOSTAT, 2013 )

    Rank

    State

    Production ( Mt )

    1

    China

    120,580,320

    2

    India

    94,880,000

    3

    United States of America

    61,755,240

    4

    France

    40,300,800

    5

    Russian Federation

    37,719,640

    6

    Australia

    29,905,009

    7

    Canada

    27,012,900

    8

    Pakistan

    23,517,000

    9

    Germany

    22,432,000

    10

    Turkey

    20,100,000

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

    Rank

    Commodity

    Production ( Mt )

    1

    Maize

    875,098,630

    2

    Rice

    718,345,379

    3

    Wheat

    674,884,372

    4

    Soies

    253,137,072

    5

    Barley

    132,350,224

    2.2.2 Insect Plagues of Wheat

    Wheat is attacked by many insect plagues. But, fortuitously, merely a few insect species are potentially of import, doing terrible harm or eruption over big geographical countries. Most of the insect plague species are merely occasional plagues and are non doing pest eruption ( Prescott et al. , 1986 ) . This subdivision discusses merely major insect plagues including aphids, stink bugs, army worms, cutworms, cereal foliage beetle, thrips, hessian fly, wheat root maggot, white chow, wireworms. In add-on to these plagues, there are others such as sawfly, bullets, snails, grasshoppers, crickets and touchs, who can assail wheat works, but the harm is non terrible.

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