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投稿时间：2024-01-30
投稿时间：2024-01-30
中文摘要: 杨梅因营养丰富和新鲜多汁等优点深受国内外消费者的喜爱，但分级分拣存在人工成本高、标准不一、误差率高、分组速度慢等缺点，机器分级分拣技术能够提高生产效率和保证品质一致性。利用可见/近红外光谱技术、计算机视觉技术及高光谱成像技术等基于光学特性的无损检测方法在杨梅品质检测方面的研究取得一些研究成果。该文基于上述光学特性的杨梅品质无损检测技术进行综述，分析各技术的优缺点，为基于光学特性无损检测技术在杨梅品质评价方面的应用提供参考。
Abstract:Chinese bayberry was popular among domestic and foreign consumers for the rich nutrients， freshness， and juiciness. However， the grading and sorting of Chinese bayberry face shortcomings such as high labor cost， inconsistent standards， high error rate， and slow speed. Machine grading and sorting can improve the efficiency and quality consistency. In recent years， research progress has been achieved in nondestructive testing methods based on optical characteristics， such as visible/near-infrared spectroscopy， computer vision technology， and hyperspectral imaging， in the quality inspection of Chinese bayberry. The nondestructive testing technologies for Chinese bayberry quality based on optical characteristics were reviewed， and their advantages and disadvantages were summarized， with a view to providing a reference for the application of nondestructive testing technologies based on optical characteristics in the evaluation of Chinese bayberry quality.
keywords: optical characteristics nondestructive testing Chinese bayberry quality spectroscopy imaging technology
文章编号：202507028 中图分类号： 文献标志码：
基金项目:温州市基础性公益科研项目（N20220027）；文成县科技计划项目（2021NKY07）
| 作者 | 单位 |
| 张百刚1，孟子轩1，2，张井2，蒋巧俊2，邹盈2，苏凤贤2，3 * | 1. 兰州理工大学 生命科学与工程学院，甘肃 兰州 730050；2. 温州科技职业学院 农业与生物技术学院，浙江 温州 325006；3. 温州市农业科学研究院 浙南作物育种重点实验室，浙江 温州 325006 |
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