Institute of Future Farming Systems, Central Queensland University, Rockhampton, QLD 4701, Australia.
Sensors (Basel). 2023 Apr 10;23(8):3868. doi: 10.3390/s23083868.
Forward estimates of harvest load require information on fruit size as well as number. The task of sizing fruit and vegetables has been automated in the packhouse, progressing from mechanical methods to machine vision over the last three decades. This shift is now occurring for size assessment of fruit on trees, i.e., in the orchard. This review focuses on: (i) allometric relationships between fruit weight and lineal dimensions; (ii) measurement of fruit lineal dimensions with traditional tools; (iii) measurement of fruit lineal dimensions with machine vision, with attention to the issues of depth measurement and recognition of occluded fruit; (iv) sampling strategies; and (v) forward prediction of fruit size (at harvest). Commercially available capability for in-orchard fruit sizing is summarized, and further developments of in-orchard fruit sizing by machine vision are anticipated.
收获量的预估需要有关果实大小和数量的信息。过去三十年来，水果和蔬菜的分选工作已经在包装厂实现了自动化，从机械方法发展到机器视觉。现在，这种转变也正在发生在对树上果实（即在果园中）的大小评估上。本综述重点介绍了：（i）果实重量与线性尺寸之间的比例关系；（ii）使用传统工具测量果实的线性尺寸；（iii）使用机器视觉测量果实的线性尺寸，同时注意深度测量和遮挡果实识别等问题；（iv）采样策略；以及（v）果实大小的预估（在收获时）。总结了商业上可用于果园中果实尺寸测量的能力，并预计机器视觉在果园中果实尺寸测量方面将会有进一步的发展。
