|
Precision farming or precision agriculture is an agricultural concept relying on the existence of in-field variability. It requires the use of new technologies, such as global positioning (GPS), sensors, satellites or aerial images, and information management tools (GIS) to assess and understand variations. Collected information may be used to more precisely evaluate optimum sowing density, estimate fertilizers and other inputs needs, and to more accurately predict crop yields. It seeks to avoid applying same practices to a crop, regardless of local soil/climate conditions and may help to better assess local situations of disease or lodging. In the Midwest it is associated not with sustainable agriculture but with mainstream farmers who are trying to maximize profits by spending money only in areas that need fertilizer. This practice allows the farmer to vary the rate of fertilizer across the field according to the need identified by GPS guided Grid Sampling. Fertilizer that would have been spread in areas that don't need it can be placed in areas that do, thereby optimizing its use. Precision farming may be used to improve a field or a farm management from several perspectives adjustment of cultural practices to take into account the real needs of the crop (e.g., better fertilization management) better time management at the farm level (e.g. planification of agricultural activity) reduction of agricultural impacts (better estimation of crop nitrogen needs implying limitation of nitrogen run-off) increase of the output and/or reduction of the input, increase of efficiency (e.g., lower cost of nitrogen fertilization practice) Other benefits for the farmer may be to help him set an history of his/her farm practices and results, to help him in his decision making and traceability requirements (as increasingly required in developed countries).
See also | ||||||||
|
| |||||||||
 |
|
| |