Articles
Predicting fruit set based on the fruit growth rate model with vision systems
Article number
1395_54
Pages
409 – 416
Language
English
Abstract
Chemical thinning is a common practice used in apple orchards.
It entails an early reduction in tree crop load, resulting an improvement of fruit size, quality and return bloom.
PACMAN (Precision Apple Crop Load MANagement) is an extremely effective method for successfully managing crop load.
The fruit growth model is an essential tool in precision crop load management.
Currently, there are several private companies with digital tools to help use this model.
The aim of this study was to evaluate two methods of predicting fruit set (Cornell MaluSim app and Farm Vision/Pometa digital scans). Trials were carried out in 18 orchards in Massachusetts, Michigan, New York, and North Carolina during two seasons (2022 and 2023). In each orchard block we selected 5 homogeneous trees and counted the total number of blossom clusters tree‑1. Fruit set was determined after natural fruit drop or at harvest.
Standard chemical thinning spray applications were made in all trials when king fruit diameters were between 6 and 8 mm.
The fruit diameters were evaluated 4 and 7 days after application at all locations in 15 flower clusters per tree (5 trees × 15 flusters = 75 flower clusters). There were significant correlations between final fruit numbers harvested and predicted fruit set with both systems.
The R2 correlations were between 0.7 and 0.8. When the number of fruit at harvest was lower than 200 fruit tree‑1, the predicted fruit set with both systems was very accurate (1:1). However, when the number of fruit at harvest was higher than 200 fruit tree‑1, both systems overestimated the number fruit at harvest.
These methods of predicting fruit set within 7 days of spraying a chemical thinner will allow growers to obtain actionable information to guide precision crop load management with less effort than the current manual measurement.
It entails an early reduction in tree crop load, resulting an improvement of fruit size, quality and return bloom.
PACMAN (Precision Apple Crop Load MANagement) is an extremely effective method for successfully managing crop load.
The fruit growth model is an essential tool in precision crop load management.
Currently, there are several private companies with digital tools to help use this model.
The aim of this study was to evaluate two methods of predicting fruit set (Cornell MaluSim app and Farm Vision/Pometa digital scans). Trials were carried out in 18 orchards in Massachusetts, Michigan, New York, and North Carolina during two seasons (2022 and 2023). In each orchard block we selected 5 homogeneous trees and counted the total number of blossom clusters tree‑1. Fruit set was determined after natural fruit drop or at harvest.
Standard chemical thinning spray applications were made in all trials when king fruit diameters were between 6 and 8 mm.
The fruit diameters were evaluated 4 and 7 days after application at all locations in 15 flower clusters per tree (5 trees × 15 flusters = 75 flower clusters). There were significant correlations between final fruit numbers harvested and predicted fruit set with both systems.
The R2 correlations were between 0.7 and 0.8. When the number of fruit at harvest was lower than 200 fruit tree‑1, the predicted fruit set with both systems was very accurate (1:1). However, when the number of fruit at harvest was higher than 200 fruit tree‑1, both systems overestimated the number fruit at harvest.
These methods of predicting fruit set within 7 days of spraying a chemical thinner will allow growers to obtain actionable information to guide precision crop load management with less effort than the current manual measurement.
Authors
L. Gonzalez Nieto, A. Wallis, J. Clements, M. Miranda Sazo, C. Kahlke, T.M. Kon, T.L. Robinson
Keywords
Malus × domestica, Pometa, Farm Vision, computer vision system, trunk cross sectional area (TCSA), bloom intensity, yield estimation
Groups involved
- Division Temperate Tree Nuts
- Division Vine and Berry Fruits
- Division Temperate Tree Fruits
- Division Precision Horticulture and Engineering
- Division Plant-Environment Interactions in Field Systems
- Division Tropical and Subtropical Fruit and Nuts
- Working Group Precision Management of Orchards and Vineyards
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