Training system affects sweet cherry harvest efficiency

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Abstract

Intuitively, tree architecture will affect harvest efficiency of tree fruit crops, yet there are no empirical studies that document this. The objective of the current research was to investigate the role of training system on harvest rate of individual pickers in commercial sweet cherry (Prunus avium L.) orchards. We used a real-time labor monitoring system (LMS) with the ability to track and record individual picker efficiency in 11 orchards throughout the Pacific Northwest. Trees were trained to one of five different architectures: 1) upright fruiting offshoots (UFO), a planar architecture comprised of unbranched vertical fruiting wood; 2) Y-trellised, an angled dual planar architecture; 3) Kym Green Bush (KGB), a multileader bush; 4) central leader (CL); and 5) traditional multileader open center (MLOC), trees comprised of three to five main leaders. A consistent picking crew was used to facilitate comparisons among systems and eliminate variability in skill among pickers. The LMS calculated harvest rate, picking cost, weight of harvested fruit, number of harvested buckets, range in fruit weight per bucket/bin, and mean fruit weight per bucket/bin for individual pickers. Tests revealed a significant effect of canopy architecture on labor efficiency. The highest mean (± SE) harvest rates (0.94 ± 0.02 kg·min-1 and 0.78 ± 0.03 kg·min-1) were recorded in 'Cowiche'/'Gisela®5' and 'Tieton'/'Gisela®5' orchards trained to the UFO system, respectively. High harvest efficiency in these orchards was likely the result of the planar, simplified architecture and that most fruit were accessible from the ground. The third highest picking rate was recorded in the KGB system (0.73 ± 0.04 kg·min-1), a fully pedestrian orchard. Interestingly, harvest rate of slower pickers was improved to a greater extent (+132%) than skilled pickers (+83%) when comparing pedestrian and planar systems (e.g., UFO and KGB) with traditional architecture (MLOC). Furthermore, picking rate of individual pickers varied within 1 day by more than 100%, likely as a result of variability in fruit density within trees, tree size as well as fruit accessibility. We documented variability of more than 35 kg in final bin weight across all orchards and a range in bucket weight between ≈7 and 13 kg. These results suggest that architecture has a major effect on harvest efficiency and that current systems of piece-rate picker reimbursement are beset with inaccuracy.

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APA

Ampatzidis, Y. G., & Whiting, M. D. (2013). Training system affects sweet cherry harvest efficiency. HortScience, 48(5), 547–555. https://doi.org/10.21273/hortsci.48.5.547

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