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Observational analysis mapped yield variability in tart cherries, suggesting affordable options for growers.
The mechanical harvesting of tart cherries has been a standard practice since the 1960’s but no technology has been proposed to map orchard yields. This study addresses this gap by introducing a low-cost yield monitor that tracks the distance between fruit bin changes using an ultrasonic proximity sensor, Global Navigation Satellite System (GNSS) positioning, and a microcomputer to collect and store the data. Results demonstrated agreement between the used GNSS receiver and differential-GNSS receivers, with positional errors under 4 m (m). The average final weight of 70 bins measured at the orchards was 512 kg, while the average final weight for 2,142 bins measured at the processing plant was 483 kg. The maximum difference in average final bin weight between seven operators was up to 24 kg in the orchards. Two orchard blocks were mapped over 2023 and 2024 with yields ranging from 6 to 46 Mg ha − 1 . The time taken by operators to harvest a single tree was between 26 and 37 s. Beyond its immediate practical advantages, our method also paves the way for future innovations in precision agriculture. Its flexible design allows it to be adapted for use with other crops that employ shake-and-catch harvesting systems. The proposed method offers an affordable solution to provide tart cherry growers with valuable insights about yield variability and harvest labor efficiency.
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Kurt Wedegaertner (2025) studied this question.
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