近红外光谱及成像在果品无损检测中的应用
Application of nondestructive detection of fruit by near-infrared spectroscopy and imaging
郭志明 1桑伟兴 2杨忱 2邹小波3
作者信息
- 1. 江苏大学食品与生物工程学院,江苏镇江 212013;中国轻工业食品智能检测与加工重点实验室,江苏镇江 212013
- 2. 江苏大学食品与生物工程学院,江苏镇江 212013
- 3. 江苏大学食品与生物工程学院,江苏镇江 212013;江苏省智能农业与农产品加工国际合作联合实验室,江苏镇江 212013
- 折叠
摘要
近红外光谱及成像技术作为新兴传感无损检测技术,具有绿色、无污染、非破坏性等优势,为果品品质领域的快速、无损检测提供新的方法和手段.文章综述近红外光谱及成像技术在果品品质检测中的研究进展,介绍近红外光谱和成像技术的基本原理,分析近红外光谱技术在果品品质检测中的化学组成、成熟度评估和小型化设备开发的应用现状,探析近红外光谱成像技术在果品外观和质量、病虫害诊断中的应用现状,阐述其在果品组分分布和缺陷识别等方面的技术优势.同时,探讨近红外光谱及成像技术与人工智能、物联网结合应用的巨大潜力,以及对提高果品检测效率、精度和改善供应链智能管控等方面的应用前景做出展望,以期为果品无损检测的应用研究提供参考.
Abstract
Near-Infrared(NIR) spectroscopy and imaging technology emerge as innovative sensor-based non-destructive evaluation techniques,boasting of their environmental friendliness,absence of pollution,and non-destructive capabilities,thereby offering novel methodologies for the rapid and non-destructive detection within the domain of fruit quality.This paper reviews the advances in the research regarding the application of NIR spectroscopy and imaging technology in fruit quality assessment.It elucidates the fundamental principles underlying NIR spectroscopy and imaging technology and scrutinizes the current landscape of their application in online scenarios,including the analysis of chemical composition,maturity evaluation,and the development of miniaturized devices tailored for fruit quality inspection.Furthermore,the paper delves into the operational status of NIR spectroscopy imaging technology in examining the external appearance and quality of fruits,along with diagnosis of pest and disease infestations,and describes the technological superiority of NIR spectroscopy in discerning the distribution of fruit components and identifying defects.Moreover,it discusses the immense potential presented by the integration of NIR spectroscopy and imaging technology with Artificial Intelligence(AI) and the Internet of Things(IoT),forecasts the application prospects in terms of enhancing the efficiency and accuracy of fruit quality evaluation and improving intelligent supply chain management with a view to provide a reliable reference for application-based research of non-destructive fruit detection.
关键词
近红外光谱/高光谱成像/果品/无损检测/人工智能Key words
near-infrared spectroscopy/hyperspectral imaging/fruits/non-destructive detection/artificial intelligence引用本文复制引用
基金项目
国家重点研发计划项目(2023YFE0107100)
江苏省重点研发计划重点项目(BE2022363)
江苏省农业科技自主创新资金项目(CX223069)
出版年
2024
国家科技期刊平台
NSTL
万方数据