General Site-Specific Farming
Click here to see a yield map from a wheat field in Winters, California
Precision agriculture is also known as site-specificcrop management. The main idea of precision agriculture is very simple. Agricultural crop fields, although they may look uniform at first glance, are actually quite variable from one part to another. Some parts are sandier, or have deeper topsoil (possibly due to laser leveling), a higher clay content, or higher soilborne pathogen levels. Therefore, it stands to reason that production would be more efficient if inputs such as nitrogen, fungicide, etc. could be precisely tailored to each location in the field. This is precision agriculture. Most of the activity in precision agriculture has been in the corn, wheat, and soybeans systems of the Midwest.
One of the reasons precision agriculture has caught on so quickly is that it is based on existing technology. This includes the following components: intensive sampling, remote sensing, geographic information systems (GIS), yield monitoring, global positioning systems (GPS), and variable rate applicators.
Intensive sampling means simply collecting data such as weed, disease, and soil samples at many different places in the field. Typically this is done on a square grid of roughly one sample per acre. Soils are analyzed for N, P, K levels; clay, sand and silt content, etc. Remote sensing can be used in the form of aerial infrared photographs that indicate the vigor of vegetation at each point in the field. A yield monitor is a device that is attached to the combine or picker and measures the rate of harvested material coming from the field. By mounting a GPS on the harvester and linking it to the yield monitor, the yield at each point in the field can be recorded. This can then be entered into the GIS to produce a yield map of the field. Based on the combined information from the maps of the field the grower can, when he applies an input (such as fertilizer), use the GPS to determine exactly where he is in the field adjust the application rate accordingly using a variable-rate applicator.
The GIS is the heart of the whole effort since it is used to store the data, generate the maps, and do the analyses and cartographic modeling of the system. Thus, the GIS integrates the ground-level sampling data, remote sensing data, and yield data. The ultimate goal is to adjust input application rate based on soil and yield data. In order for the farmer to properly adjust the application rate of an input, he must know by how much and under what circumstances to adjust it. Considerable research has been done in Midwestern cropping systems to address this question, but much more needs to be done.
California cropping systems differ from those of the Midwest in that in California even those crops grown in very large fields are often relatively high-value crops such as cotton, grapes, and tomatoes.
Publications in general site-specific crop management
Rosenstock, T.S., R.E. Plant and P.H. Brown, Spatial patterns confound experiments in orchard crops. Proceedings of the International Plant Nutrition Colloquium XVI. Paper 1424, http://repositories.cdlib.org/ipnc/xvi/1424 (2009)
Perez-Quezada, J., G.S. Pettygrove, and R.E. Plant. Spatial-temporal analysis of yield and the influence of soil factors in two four-crop-rotation fields in the Sacramento Valley, California. Agronomy Journal 95:676-687 (2003)
Perez, J.F., S. Pettygrove, and R.E. Plant Testing suitability of SSURGO soil-unit definition and the EPIC model to reproduce within-field yield variability in a four-crop rotation field. Proceedings of the Sixth International Conference on Precision Agriculture (2003)
Plant, R.E. Site-Specific Management: The Application of Information Technology to Crop Production. Computers and Electronics in Agriculture 30: 9-29 (2001).
Plant, R.E., G.S. Pettygrove, and W.R. Reinert. Precision agriculture: crop production in the twenty-first century. California Agriculture 54(4): 66-71 (2000).
Pettygrove, G.S., S.K. Upadhyaya, M.G. Pelletier, T.K. Hartz, R.E. Plant and R.F. Denison. Tomato yield - color infrared photograph relationahips. Proc. Fourth International Conference on Precision Agriculture, St. Paul, Minnesota. 1483-1492 (1999)
Miller, R.O., S. Pettygrove, R.F. Denison, L.F. Jackson, M. Cahn, R. Plant and T. Kearney. Site-specific relationships between flag leaf nitrogen, SPAD meter values and grain protein in irrigated wheat. Proceedings of the Fourth International Conference on Precision Agriculture 113-122 (1999)
Plant, R.E., A. Mermer, G.S. Pettygrove, M.P. Vayssieres, J.A. Young, R.O. Miller, L.F. Jackson, R.F. Denison, and K. Phelps. Factors underlying grain yield spatial variability in three irrigated wheat fields. Transactions of the ASAE 42: 1187-1202 (1999)