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ANTONIO COMPARETTI

Precision Agriculture: Past, Present and Future

  • Autori: Comparetti, A
  • Anno di pubblicazione: 2011
  • Tipologia: eedings
  • Parole Chiave: within-field spatial variability, GPS, sensors, yield mapping, geo-referenced application of crop inputs
  • OA Link: http://hdl.handle.net/10447/66282

Abstract

From 1978 the Global Positioning System, needed for sensing the position of military targets (e.g. buildings, machinery), was developed as a pure military system, while in 1983 it was made available also for public use. Therefore, at the beginning of 80s precision agriculture, requiring GPS for sensing the position to which any measured field parameter must be geo-referenced, was implemented for the first time in US. In fact, soil and crop parameters are spatially variable in a field, so that spatially uniform rate crop input applications cause increased environmental impact and crop input waste. In order to reduce the environmental impact and optimise the use of crop inputs, precision agriculture was born: it is the geo-referenced application of crop inputs, whose rates must be those required by the crop. At present a profitable implementation of precision agriculture, depending on the crop Gross Saleable Product, can be achieved only in medium-large farms. As a consequence, precision agriculture is widespread only in large areas of US, Germany, Denmark, Netherlands and United Kingdom. In the future precision agriculture could be implemented on a larger scale if the following requirements will be satisfied: to quantify its environmental and economic benefits; to develop common vehicle bus standards (e.g. CAN-bus) on agricultural machines, sensors for mapping soil and crop parameters and user-friendly software for processing and interpreting the measured data; to use devices compatible among each other and an integrated user-friendly software for all the spatially variable field operations; to develop soil-crop simulation models, in order to identify the causes of within-field spatial variability and, therefore, adjust the crop input rates from the next growing season.