利用高速线性轨道双激光扫描系统检测 "Scilate "苹果的内部褐变情况

IF 6.4 1区 农林科学 Q1 AGRONOMY
Zhen Wang , Jason Sun , Rainer Künnemeyer , Andrew McGlone
{"title":"利用高速线性轨道双激光扫描系统检测 \"Scilate \"苹果的内部褐变情况","authors":"Zhen Wang ,&nbsp;Jason Sun ,&nbsp;Rainer Künnemeyer ,&nbsp;Andrew McGlone","doi":"10.1016/j.postharvbio.2024.113200","DOIUrl":null,"url":null,"abstract":"<div><p>This study reports on a linear-rail, dual-laser scanning system for high-speed, non-destructive detection of internal quality of fruit. The system was used to detect internal browning of ‘Scilate’ apples. A sample of 200 ‘Scilate’ apples with four different (healthy, slight, moderate, and severe) levels of browning was investigated. The new system’s performance was compared to that of a bench-top near infrared spectroscopy (NIRS) system. Apples with moderate and severe browning were easily detected by both systems. A comprehensive binary classification was made between healthy apples and those with slight browning. The classification results showed that the dual-laser scanning system performed very well for classifying apples with slight internal browning, achieving high accuracies of around 90 % compared to that of 82 % with the NIRS method. The dual-laser system operated successfully while fruit were moving at high speeds of 1.125 m/s and was able to identify small or localised defects.</p></div>","PeriodicalId":20328,"journal":{"name":"Postharvest Biology and Technology","volume":"219 ","pages":"Article 113200"},"PeriodicalIF":6.4000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0925521424004459/pdfft?md5=f100bbfab772f4563f8e8624b74701a4&pid=1-s2.0-S0925521424004459-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Detection of internal browning in ‘Scilate’ apples with a high-speed linear-rail dual-laser scanning system\",\"authors\":\"Zhen Wang ,&nbsp;Jason Sun ,&nbsp;Rainer Künnemeyer ,&nbsp;Andrew McGlone\",\"doi\":\"10.1016/j.postharvbio.2024.113200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study reports on a linear-rail, dual-laser scanning system for high-speed, non-destructive detection of internal quality of fruit. The system was used to detect internal browning of ‘Scilate’ apples. A sample of 200 ‘Scilate’ apples with four different (healthy, slight, moderate, and severe) levels of browning was investigated. The new system’s performance was compared to that of a bench-top near infrared spectroscopy (NIRS) system. Apples with moderate and severe browning were easily detected by both systems. A comprehensive binary classification was made between healthy apples and those with slight browning. The classification results showed that the dual-laser scanning system performed very well for classifying apples with slight internal browning, achieving high accuracies of around 90 % compared to that of 82 % with the NIRS method. The dual-laser system operated successfully while fruit were moving at high speeds of 1.125 m/s and was able to identify small or localised defects.</p></div>\",\"PeriodicalId\":20328,\"journal\":{\"name\":\"Postharvest Biology and Technology\",\"volume\":\"219 \",\"pages\":\"Article 113200\"},\"PeriodicalIF\":6.4000,\"publicationDate\":\"2024-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0925521424004459/pdfft?md5=f100bbfab772f4563f8e8624b74701a4&pid=1-s2.0-S0925521424004459-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Postharvest Biology and Technology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0925521424004459\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Postharvest Biology and Technology","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0925521424004459","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0

摘要

本研究报告介绍了一种用于高速、无损检测水果内部质量的线性导轨双激光扫描系统。该系统用于检测 "Silate "苹果的内部褐变。对 200 个'Silate'苹果样品进行了调查,这些样品有四种不同的褐变程度(健康、轻微、中等和严重)。新系统的性能与台式近红外光谱(NIRS)系统的性能进行了比较。两种系统都能轻松检测出中度和重度褐变的苹果。对健康苹果和轻微褐变苹果进行了全面的二元分类。分类结果表明,双激光扫描系统在对内部轻微褐变的苹果进行分类时表现非常出色,准确率高达 90%,而 NIRS 方法的准确率仅为 82%。双激光系统在水果以 1.125 米/秒的速度高速移动时也能成功运行,并能识别小的或局部的缺陷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of internal browning in ‘Scilate’ apples with a high-speed linear-rail dual-laser scanning system

This study reports on a linear-rail, dual-laser scanning system for high-speed, non-destructive detection of internal quality of fruit. The system was used to detect internal browning of ‘Scilate’ apples. A sample of 200 ‘Scilate’ apples with four different (healthy, slight, moderate, and severe) levels of browning was investigated. The new system’s performance was compared to that of a bench-top near infrared spectroscopy (NIRS) system. Apples with moderate and severe browning were easily detected by both systems. A comprehensive binary classification was made between healthy apples and those with slight browning. The classification results showed that the dual-laser scanning system performed very well for classifying apples with slight internal browning, achieving high accuracies of around 90 % compared to that of 82 % with the NIRS method. The dual-laser system operated successfully while fruit were moving at high speeds of 1.125 m/s and was able to identify small or localised defects.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Postharvest Biology and Technology
Postharvest Biology and Technology 农林科学-农艺学
CiteScore
12.00
自引率
11.40%
发文量
309
审稿时长
38 days
期刊介绍: The journal is devoted exclusively to the publication of original papers, review articles and frontiers articles on biological and technological postharvest research. This includes the areas of postharvest storage, treatments and underpinning mechanisms, quality evaluation, packaging, handling and distribution of fresh horticultural crops including fruit, vegetables, flowers and nuts, but excluding grains, seeds and forages. Papers reporting novel insights from fundamental and interdisciplinary research will be particularly encouraged. These disciplines include systems biology, bioinformatics, entomology, plant physiology, plant pathology, (bio)chemistry, engineering, modelling, and technologies for nondestructive testing. Manuscripts on fresh food crops that will be further processed after postharvest storage, or on food processes beyond refrigeration, packaging and minimal processing will not be considered.
×
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