Assessment of grapevine bunch withering: advances in fruit 3D morphology and colour evaluation

IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING
Alessandro Zanchin , Anna Perbellini , Marco Sozzi , Francesco Marinello , Lorenzo Guerrini
{"title":"Assessment of grapevine bunch withering: advances in fruit 3D morphology and colour evaluation","authors":"Alessandro Zanchin ,&nbsp;Anna Perbellini ,&nbsp;Marco Sozzi ,&nbsp;Francesco Marinello ,&nbsp;Lorenzo Guerrini","doi":"10.1016/j.biosystemseng.2025.104145","DOIUrl":null,"url":null,"abstract":"<div><div>The agro-industrial sector is experiencing a new wave of innovation driven by goods-inspecting devices designed to optimise operations, improve product quality, and reduce yield losses. Grape withering is widely used to concentrate berry juice for raisin and sweet wine production. While this process alters wine characteristics, it also introduces costs and risks, as pathogen infections can compromise the quality of the final product. This study presents a reliable three-dimensional analysis for assessing grape colour and bunch morphology to evaluate infection risk and drying performance. Twenty <em>Vitis vinifera</em> bunches were dried under environmental conditions. Colour analysis focused on the distribution of colours in healthy versus rotten bunches. Three-dimensional digital replicas were generated with two methods: i) photogrammetry, and ii) a recently developed artificial intelligence model. The point clouds and meshes output from the two approaches were compared, and morphometric traits were directly measured, including volume, surface area, and both horizontal and vertical sections for each bunch. Key geometrical descriptors of the bunch's horizontal sections and individual berries were found to be relevant for classifying the risk of bunch rot. Additionally, morphometric traits related to bunch compactness were linked to drying speed. A linear model incorporating three-dimensional descriptors was developed to estimate weight loss during withering, achieving an R<sup>2</sup> value of 0.98 and a relative error of 0.07. The artificial intelligence-based technique produced lower-quality models for grape reconstruction, but the selected morphometric traits remained effective.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"254 ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems Engineering","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1537511025000819","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 0

Abstract

The agro-industrial sector is experiencing a new wave of innovation driven by goods-inspecting devices designed to optimise operations, improve product quality, and reduce yield losses. Grape withering is widely used to concentrate berry juice for raisin and sweet wine production. While this process alters wine characteristics, it also introduces costs and risks, as pathogen infections can compromise the quality of the final product. This study presents a reliable three-dimensional analysis for assessing grape colour and bunch morphology to evaluate infection risk and drying performance. Twenty Vitis vinifera bunches were dried under environmental conditions. Colour analysis focused on the distribution of colours in healthy versus rotten bunches. Three-dimensional digital replicas were generated with two methods: i) photogrammetry, and ii) a recently developed artificial intelligence model. The point clouds and meshes output from the two approaches were compared, and morphometric traits were directly measured, including volume, surface area, and both horizontal and vertical sections for each bunch. Key geometrical descriptors of the bunch's horizontal sections and individual berries were found to be relevant for classifying the risk of bunch rot. Additionally, morphometric traits related to bunch compactness were linked to drying speed. A linear model incorporating three-dimensional descriptors was developed to estimate weight loss during withering, achieving an R2 value of 0.98 and a relative error of 0.07. The artificial intelligence-based technique produced lower-quality models for grape reconstruction, but the selected morphometric traits remained effective.
求助全文
约1分钟内获得全文 求助全文
来源期刊
Biosystems Engineering
Biosystems Engineering 农林科学-农业工程
CiteScore
10.60
自引率
7.80%
发文量
239
审稿时长
53 days
期刊介绍: Biosystems Engineering publishes research in engineering and the physical sciences that represent advances in understanding or modelling of the performance of biological systems for sustainable developments in land use and the environment, agriculture and amenity, bioproduction processes and the food chain. The subject matter of the journal reflects the wide range and interdisciplinary nature of research in engineering for biological systems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信