Crop Yield

If maps of the spatial distribution of soil productivity potential (maps of expected yield) and maps of the spatial distribution of plant nutrients available from the soil are developed for a field, fertilizers and organic wastes can be applied in amounts per acre that are directly proportional to the soil's expected yield and adjusted for the soil's fertility at any location in the field. Such a procedure would optimize the economic potential of a field, yet minimize the leaching of nutrients.

The above protocol depends on having a good map of the spatial variation of expected yields for crop fields. Maps of past crop yields for a field could be used for this purpose. However, multiple years of spatial yield

Yield (left) vs. Remote Sensing (right)
Reds correspond to higher yield,
blues and greens to lower yields.

data would be needed to overcome variations caused by year to year differences in weather, especially rainfall, and there remains multiple factors which result in lack of year to year correlation.

An alternative to mapping of actual crop yields would be to use remote sensing to determine spatial distribution of plant status (health or efficiency) and the corollary expected yields. A major advantage of this approach is that remote sensing can provide a current assessment of the overall plant health of the crop rather than relying on past history of yields.

Several different approaches exist for using remote sensing data for this purpose. Most of the commonly recognized techniques depend on measuring the greenness of the field. Typically, this involves some relationship comparing the reflectance of a visible band (such as red light) to the reflectance of a near-IR band. Since green vegetation has a very sharp change in reflectivity across this range and other materials do not, virtually any technique will in fact detect it. The approach suffers from several defects. For example, it is a relative technique and can be significantly affected by soil conditions.

Flight lines during the 1998 campaign.

We have pursued a different path in this research. We have examined the thermodynamic efficiency of the crop. The core of our approach depends on energy in the thermal-IR. Our experiment was to study the energy budget of the crops and demonstrate a relationship between multi-temporal thermal imagery and crop yield.

For a cotton crop in Crisp county Georgia, both the growth rate and the hand picked yield of cotton lint varied with location in the field. Various measurement sites were selected in the field with dry weights of cotton being lowest in the sandier soils, and dry weights higher in areas with higher concentrations of organic matter in the soil. These differences could not be explained due to lack of nutrients. Samples taken throughout the field indicated adequate plant available phosphorous, potassium, and nitrogen. Also, no toxicities from aluminum or manganese were apparent in the samples.

Cotton crop yield (left) and Remote Sensing (right)

Differences in the growth rate and consequently yield appear to have been due to differences in water stress in various parts of the field. Soon after the emergence of the cotton, it became apparent that growth rates were more favored in the lower elevations of the field. This was due in part to runoff from the higher elevations. Lower yields were indicated in soils with sandy A and E horizons more than 100 cm thick and eroded soils in convex slopes. Highest yields were achieved in shallow closed depressions with dark colored surface horizons. Water stresses were due to low rainfall during the growing season. Those soils which were able to store plant available water (dependent on soil organic matter and clay content) were likely the cause of the yield differences.

Links of Interest

Nutrient Removal by Alabama Crops
Georgia State Plan for Sustainable Agriculture
Georgia Agricultural Economics Department
Peanut Resources
Optimized Nitrogen Fertilization
Case Advanced Farming Systems
John Deere Greenstar Precision Farming Equipment

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Last Updated: October 4, 1999