VARIATION IN HARVESTING LOSSES IN RELATION TO FRUIT YIELD, PLANT HEIGHT AND SLOPE: A BASIS FOR AUTOMATION OF HARVESTER

Abstract. Knowledge of spatial variability in mechanical harvesting losses in relation to fruit yield, plant height and topographic features can assist in automation of wild blueberry harvester to improve harvestable yield. Currently, harvester operators are adjusting head height, ground speed and revolutions manually, emphasizing the need for automation of harvester to improve berry picking efficiency and reduce operator‘s stress. The goal of this work was to identify the potential for automation of blueberry harvester in spatially variable wild blueberry fields. Completely randomized experiments were designed in selected fields and plots were constructed to examine the picking performance of harvester in five zones of plant height, fruit yield and slope. Fruit yield, and total losses were collected from each plot within selected fields. Plant height and slope were recorded manually to examine their impact on fruit losses.

Results of classical and geostatistical analysis in conjunction with mapping revealed significant variability within selected fields. These findings illustrated the importance of changing machine operating parameters based on spatial variability to reduce berry losses during harvesting. Variability in fruit losses with respect to fruit yield, plant height and slope were analyzed through zonal analysis in ArcGIS 10.2 software. Raster categories of data were extracted and analyzed statistically to compare the means of fruit losses in different zones of fruit yield, plant height and slope. Results revealed the dependence of fruit losses on fruit yield, plant height and slope within the selected fields. In general, fruit losses increased with an increase in fruit yield and slope during mechanical harvesting. Results showed that the picking performance of blueberry harvester was influenced by the variations in plant height with selected fields. On-the-go adjustments in the machine operating parameters (by automating the harvester) in accordance with spatial variations can enhance picking performance and increase profit margins with no additional cost.