Senwes Scenario December 2016 / January 2017 | Page 22

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TRADE NEWS

MANAGEMENT OF VARIABLES IN A FARMING SYSTEM WITH the assistance of precision farming

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FARMING PRODUCTION SYSTEMS DERIVED A LOT OF BENEFIT FROM TECHNOLOGICAL DEVELOPMENT AND THE PROGRESS MADE IN RESPECT THEREOF IN OTHER INDUSTRIES . DUE TO THE CURRENT AVAILABLE TECHNOLOGY AND PRODUCTION SYSTEMS , AGRICULTURE CAN DERIVE BENEFIT FROM MECHANISATION , SYNTHETIC AND ORGANIC FERTILISERS , GENETIC ENGINEERING AND AUTOMISATION . THIS TECHNOLOGY CAN BE INTEGRATED TO ENSURE PROGRESS IN RESPECT OF PRECISION FARMING
DEC 2016 / JAN 2017 • SENWES Scenario
HENFRED LINDE , * VOSSIE VAN STRAATEN AND * LUAN VAN DER WALT
UFS , DEPARTMENT OF AGRICULTURAL ECONOMICS AND SOIL AND CROP SCIENCE

Precision farming relates to the management of soil and crop variables . The large scale on which farmers produce these days makes it difficult to take variables into account . The development of technology makes it possible to manage variables effectively and profitably .

The objectives of precision farming in agriculture are low inputs , high efficiency and sustainability . This approach is made possible by Global Positioning Systems ( GPS ), Geographic Information Systems ( GIS ), miniaturised computer components , automated control , on-field and distance observation , mobile computers , advanced information processing skills and telecommunication . With this technology data can be gathered spatially and over time in order to increase yield and profit .
Farmers are still unsure as to whether precision farming systems should be used . The motivation of this system may come from environmental legislation , public concern about the excessive application of agricultural chemicals and economic profits from decreased agricultural inputs and improved farm management . The success of precision farming technology will , after all , be measured by economic and environmental profits .
VARIABLES IN A FARMING SYSTEM Variables which have a meaningful influence on agricultural production , can be divided into six groups :
2.1 Yield variables Historic and current yield distribution .
2.2 Land variables Topography : Height above sea level , slope , aspect , terrace , distance from streams , marshes , etcetera .
2.3 Soil variables Soil fertility : N , P , K , Ca , Mg , C , Fe , Mn , Zn and Cu ; Soil physics , texture , density , conductivity ,