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Crop Agriculture

Types of Post-Calibration of Field average and Variability

Post-calibration of field average

Post-calibrating the field average can be done two ways. One way is simply to add or subtract the difference between the field average shown by a clean yield map and the actual weighed field average to all the yield points. This will not change the variability of yield within a field (the average difference of values from any new average stays the same) but will change the ratios between yield (for example, the highest yield point divided by the lowest yield point will change). Another method is to normalize to the field mean (average) by dividing (normalizing) all clean yield points by the field mean (other normalization techniques are discussed in the yield monitor data analysis section). When normalizing to the mean, the average of normalized yield points will equal one (or virtually one) and any field average can then be calculated by multiplying all normalized yield points by the desired field average. Normalizing to the mean keeps the ratios between yield points the same (the highest yield point divided by the lowest yield point will be the same). Normalized maps of different crops can be averaged and compared more equally than if not normalized because the average yield of fields for any crops will be one (this is described more in yield monitor data analysis section). The preferred method of normalizing data, particularly different crops, is to normalize to differences. Differences are calculated by subtracting the lowest clean yield value from all the values so the range of values starts at zero. The values can then be normalized to the maximum difference which will results in a range of values from 0 to 1 for any crop or season.

Linear and non-linear post-calibration of yield variability

Post-calibration of yield variability can be linear or non-linear and is described through the Post-calibration examples document. Calibrate variability can be based on specifications from a grower or agronomist. This can include a yield range (highest and lowest values) based on a clean yield map or can be based on estimates of yield differences for areas within a field. Areas in a field to base calibration on do not have to be large and are specified to be a certain amount different than each other based on viewing a clean yield map (do not need to actual quantities, only differences). The difference amounts can be estimated in-season or can be performed after the season by viewing a clean yield map. For example, if you may designate one area as being 20 b/a higher than another area; the whole map will be calibrated/scaled to meet that criteria then the field average can also be calibrated so the areas have the correct difference and the field has the correct average. This can be done based on two areas (linear post-calibration) or three or more areas (inevitably this will be non-linear post-calibration).