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Smart Agriculture ›› 2021, Vol. 3 ›› Issue (4): 14-28.doi: 10.12133/j.smartag.2021.3.4.202106-SA011

• 专题--农产品加工与检测 • 上一篇    下一篇

果蔬品质劣变传感检测与监测技术研究进展

郭志明1,2(), 王郡艺1, 宋烨3, 邹小波1,2, 蔡健荣1   

  1. 1. 江苏大学 食品与生物工程学院,江苏 镇江 212013
    2. 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
    3. 中华全国供销合作总社济南果品研究院,山东 济南 250220
  • 收稿日期:2021-06-30 修回日期:2021-07-13 出版日期:2021-12-30
  • 基金项目:
    国家重点研发计划项目(2017YFC1600802);国家自然科学基金项目(31972151);济南市“高校20条”资助项目(2020GXRC028);江苏省重点研发计划项目(BE2019359)
  • 通信作者: 郭志明(1982-),男,博士,教授,博士生导师,研究方向为农产品品质安全无损检测。电话:0511-88780201。E-mail:

Research Progress of Sensing Detection and Monitoring Technology for Fruit and Vegetable Quality Control

GUO Zhiming1,2(), WANG Junyi1, SONG Ye3, ZOU Xiaobo1,2, CAI Jianrong1   

  1. 1. School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
    2. International Joint Research Laboratory of Intelligent Agriculture and Agri-products Processing (Jiangsu University), Jiangsu Education Department, Zhenjiang 212013, China
    3. Jinan Fruit Research Institute, All China Federation of Supply & Marketing Cooperatives, Jinan 250220, China
  • Received:2021-06-30 Revised:2021-07-13 Online:2021-12-30
  • Foundation items:National Key Research and Development Program of China(2017YFC1600802);National Natural Science Foundation of China(31972151); Jinan City "20 High School Grants" Project (2020GXRC028); Key Research and Development Plan Project of Jiangsu Province (BE2019359)
  • Corresponding author:GUO Zhiming, E-mail:

摘要:

果蔬在采后贮藏和运输过程中极易发生品质劣变,食用价值降低且造成巨大的经济损失。为保障果蔬品质,减少产后劣变导致的资源浪费,本文综述了果蔬品质劣变传感检测与监测技术最新研究现状,分析了各类检测技术的原理、特点及优缺点。其中,机器视觉可检测果蔬外部品质和表面缺陷,电子鼻可监测果蔬的劣变气味,近红外光谱可检测果蔬内部品质和隐性缺陷,高光谱成像能实现可视化检测果蔬内外品质、监测劣变过程,拉曼光谱可检测果蔬腐败菌及其代谢产物,多技术联用和多信息融合能综合评价果蔬劣变。以各种传感器为感知节点构建物联网监测系统,进而实现果蔬品质劣变信息的智能化实时监测,为解决果蔬加工过程中品质劣变控制技术难题提供参考,对降低果蔬产后的经济损失,推进果蔬产业可持续发展具有重要意义。

关键词: 智能感知, 无损检测, 品质劣变, 物联网, 机器视觉, 高光谱, 近红外, 拉曼光谱, 电子鼻

Abstract:

Vegetable and fruit planting areas and products of China have always ranked first in the world, and the vegetable and fruit industry is respectively the second and third largest agricultural planting industry after grain. Vegetables and fruits are prone to quality deterioration during postharvest storage and transportation, resulting in reduced edible value and huge economic losses. To ensure fruit and vegetable quality and reduce the waste of resources caused by postnatal deterioration, this paper summarizes the latest research status of sensor detection and monitoring technology for fruit and vegetable quality deterioration and analyzed the principle, characteristics, advantages, and disadvantages of various detection technology. Among them, machine vision can detect the external quality and surface defects of fruits and vegetables, but fruits and vegetables are different from the standard machined products, and they are affected by many factors in the growth process, which seriously interfere with the image collection work and easily lead to misjudgment. An electronic nose equipped with expensive gas sensors can monitor the odor deterioration of fruits and vegetables but would require improved sensitivity and durability. Near-infrared can detect the internal quality and recessive defects of fruits and vegetables, but the applicability of the model needs to be improved. Hyperspectral imaging can visually detect the internal and external quality of fruits and vegetables and track the deterioration process, but the huge amount of data obtained leads to data redundancy, which puts forward higher requirements for system hardware. Therefore, low-cost multispectral imaging systems should be developed and characteristic wavelength extraction algorithms should be optimized. Raman spectroscopy can detect fruit and vegetable spoilage bacteria and their metabolites, but there is no effective Raman enhanced substrate production and accurate Raman standard spectrogram database. The comprehensive evaluation of fruit and vegetable deterioration can be realized by multi-technology and multi-information fusion. It can overcome the limitation of single sensor information analysis, improve the robustness and parallel processing ability of the detection model, and provide a new approach for high-precision detection or monitoring of fruit and vegetable quality deterioration. The Internet of Things monitoring system is constructed with various sensors as the sensing nodes to realize the intelligent real-time monitoring of fruit and vegetable quality deterioration information, provide a reference for solving the technical limitation of quality deterioration control in the processing of fruit and vegetable. This is of great significance for reducing the postpartum economic loss of fruits and vegetables and promoting the sustainable development of the fruit and vegetable industry.

Key words: intelligent perception, nondestructive detection, quality deterioration, Internet of Things, machine vision, hyperspectral, near-infrared, Raman spectroscopy, electronic nose

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