{"title":"Computer-aided design and optimization of a multi-level fruit catching system for fresh-market fruit harvesting","authors":"","doi":"10.1016/j.compag.2024.109334","DOIUrl":null,"url":null,"abstract":"<div><p>Tree fruit harvesting is a labor-intensive operation. Multi-level fruit catching and retrieval (MFCR) systems have been proposed for the mass harvesting of soft fruits using trunk shaking. However, overcoming excessive fruit damage as fruits fall through the canopy is very challenging and requires optimization of several aspects of an MFCR’s design. In this work, we present a novel computer-aided design approach for optimizing design parameters of MFCR systems. A simplified index that utilizes geometry and simple mechanics is developed to quantify the interference between an MFCR’s catching booms and tree branches. Also, an index is introduced that utilizes geometry and simplified collision kinematics to represent accumulated damage on fruits falling through the canopy. These two indices are used in a case study to determine the optimal solution – and its sensitivity – for the number of layers of an MFCR system that maximizes marketable fruit collection over twenty digitized pear trees. In conjunction with more elaborate machine-tree-fruit interaction models, the proposed methodology can be used to optimize the design of fresh-fruit mass harvesters that utilize multi-level catching and retrieval systems.</p></div>","PeriodicalId":50627,"journal":{"name":"Computers and Electronics in Agriculture","volume":null,"pages":null},"PeriodicalIF":7.7000,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Electronics in Agriculture","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168169924007257","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Tree fruit harvesting is a labor-intensive operation. Multi-level fruit catching and retrieval (MFCR) systems have been proposed for the mass harvesting of soft fruits using trunk shaking. However, overcoming excessive fruit damage as fruits fall through the canopy is very challenging and requires optimization of several aspects of an MFCR’s design. In this work, we present a novel computer-aided design approach for optimizing design parameters of MFCR systems. A simplified index that utilizes geometry and simple mechanics is developed to quantify the interference between an MFCR’s catching booms and tree branches. Also, an index is introduced that utilizes geometry and simplified collision kinematics to represent accumulated damage on fruits falling through the canopy. These two indices are used in a case study to determine the optimal solution – and its sensitivity – for the number of layers of an MFCR system that maximizes marketable fruit collection over twenty digitized pear trees. In conjunction with more elaborate machine-tree-fruit interaction models, the proposed methodology can be used to optimize the design of fresh-fruit mass harvesters that utilize multi-level catching and retrieval systems.
期刊介绍:
Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.