Precision-Ag, on-farm research, normalized difference vegetation index (NDVI)


Nowadays, good agronomical practices demand the adoption of new technologies that deliver better resource efficiency. The objective of this study was to identify and work closely with high-yielding soybean farmers in order to implement precision agriculture tools, in this case, satellite imagery. A field of 150 acres located in Perry, KS, was evaluated in the 2016 season. The study is based on working with the field variation and the selection of three productivity zones outlined according to normalized difference vegetation index (NDVI) values. In situ methods of data collection were performed across the entire field and data from vegetation indices (VIs) were extracted from Landsat 8 satellite (American Earth observation satellite) imagery. Results demonstrated a strong relationship between soybean dry weight (plant biomass) and NDVI. Satellite imagery proved to be a useful tool for delineating productivity zones. A precise and adequate management per zone can be planned via the use of satellite imagery.


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