Literature DB >> 33401804

Recent Progress of Hyperspectral Imaging on Quality and Safety Inspection of Fruits and Vegetables: A Review.

Yuan-Yuan Pu1, Yao-Ze Feng1, Da-Wen Sun1.   

Abstract

Objective quality assessment and efficacious safety surveillance for agricultural and food products are inseparable from innovative techniques. Hyperspectral imaging (HSI), a rapid, nondestructive, and chemical-free method, is now emerging as a powerful analytical tool for product inspection by simultaneously offering spatial information and spectral signals from one object. This paper focuses on recent advances and applications of HSI in detecting, classifying, and visualizing quality and safety attributes of fruits and vegetables. First, the basic principles and major instrumental components of HSI are presented. Commonly used methods for image processing, spectral pretreatment, and modeling are summarized. More importantly, morphological calibrations that are essential for nonflat objects as well as feature wavebands extraction for model simplification are provided. Second, in spite of the physical and visual attributes (size, shape, weight, color, and surface defects), applications from the last decade are reviewed specifically categorized into textural characteristics inspection, biochemical components detection, and safety features assessment. Finally, technical challenges and future trends of HSI are discussed.
© 2015 Institute of Food Technologists®.

Keywords:  classification; fruits and vegetables; hyperspectral imaging; quality assessment; safety inspection

Year:  2015        PMID: 33401804     DOI: 10.1111/1541-4337.12123

Source DB:  PubMed          Journal:  Compr Rev Food Sci Food Saf        ISSN: 1541-4337            Impact factor:   12.811


  4 in total

1.  A Novel Hyperspectral Method to Detect Moldy Core in Apple Fruits.

Authors:  Andrea Genangeli; Giorgio Allasia; Marco Bindi; Claudio Cantini; Alice Cavaliere; Lorenzo Genesio; Giovanni Giannotta; Franco Miglietta; Beniamino Gioli
Journal:  Sensors (Basel)       Date:  2022-06-14       Impact factor: 3.847

2.  Design of Electronic Nose Detection System for Apple Quality Grading Based on Computational Fluid Dynamics Simulation and K-Nearest Neighbor Support Vector Machine.

Authors:  Xiuguo Zou; Chenyang Wang; Manman Luo; Qiaomu Ren; Yingying Liu; Shikai Zhang; Yungang Bai; Jiawei Meng; Wentian Zhang; Steven W Su
Journal:  Sensors (Basel)       Date:  2022-04-14       Impact factor: 3.847

3.  Phenotyping Local Eggplant Varieties: Commitment to Biodiversity and Nutritional Quality Preservation.

Authors:  Eva Martínez-Ispizua; Ángeles Calatayud; José Ignacio Marsal; Rubén Mateos-Fernández; María José Díez; Salvador Soler; José Vicente Valcárcel; Mary-Rus Martínez-Cuenca
Journal:  Front Plant Sci       Date:  2021-07-01       Impact factor: 5.753

4.  Detecting Bacterial Biofilms Using Fluorescence Hyperspectral Imaging and Various Discriminant Analyses.

Authors:  Ahyeong Lee; Saetbyeol Park; Jinyoung Yoo; Jungsook Kang; Jongguk Lim; Youngwook Seo; Balgeum Kim; Giyoung Kim
Journal:  Sensors (Basel)       Date:  2021-03-22       Impact factor: 3.576

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.