Welcome to Smart Agriculture 中文

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

• Topic--Agricultural Products Processing and Testing • Previous Articles     Next Articles

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:

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

CLC Number: