Yield mapping methods for manually harvested crops
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During the harvest of citrus and other fruit crops, fruits are placed into bags across the field before they are loaded into trucks. The location of bags can be georeferenced for yield mapping purposes. Several alternatives are possible for processing bag location data to produce the final yield map. The objective of this study was to demonstrate and test the accuracy of different data processing methods for yield mapping in manually harvested crops. Two main types of data processing and variations of these were studied. The first type calculates yield at each point by dividing the mass of the bag by its coverage area in the field. The second type is based on the distribution and density of points across the field. The proposed methods were tested over orange bag location data and also over a modeled yield map. All methods showed similar yield variation patterns, but with different levels of detail and accuracy. Methods that calculate yield at every bag location got the highest correlation (R2=0.7) and lowest average error (15%) among the evaluated methods. These methods were considered suitable to produce yield maps and support further site-specific management actions.