Visible/near-infrared Spectroscopy and Hyperspectral Imaging Facilitate the Rapid Determination of Soluble Solids Content in Fruits
文献类型： 外文期刊
作者： Zhao, Yiying 1 ; Zhou, Lei 2 ; Wang, Wei 3 ; Zhang, Xiaobin 1 ; Gu, Qing 1 ; Zhu, Yihang 1 ; Chen, Rongqin 4 ; Zhang, Chu 5 ;
作者机构： 1.Zhejiang Acad Agr Sci, Inst Digital Agr, Hangzhou 310021, Peoples R China
2.Nanjing Forestry Univ, Coll Mech & Elect Engn, Nanjing 210037, Peoples R China
3.Chinese Acad Sci, Inst Urban Environm, Xiamen 361021, Peoples R China
4.Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Peoples R China
5.Huzhou Univ, Sch Informat Engn, Huzhou 313000, Peoples R China
关键词： VIS/NIR spectroscopy; Hyperspectral imaging; Fruit SSC; Data acquisition and analysis; Internal and external interference; Compensation strategy
期刊名称：FOOD ENGINEERING REVIEWS （ 影响因子：6.6； 五年影响因子：7.1 ）
ISSN： 1866-7910
年卷期： 2024 年
页码：
收录情况： SCI
摘要： Soluble solids content (SSC) is an essential internal quality attribute of fruits that directly affects consumers' degree of satisfaction. The traditional determination method, the refractometer, is characterized by inherent drawbacks of destructiveness, labor intensiveness, and low efficiency. Visible/near-infrared (VIS/NIR) spectroscopy and hyperspectral imaging (HSI) can be promising alternative approaches as being non-destructive, accurate, and rapid and have attracted extensive attention. This review endeavors to elucidate the advantages and limitations of applying VIS/NIR and HSI techniques in determining fruit SSC, drawing upon a comprehensive analysis of the pertinent literature. The latest progress of instrument configuration is described, and an outline for crucial steps involved in data acquisition and analysis is presented to provide empirical support for future research. Notably, the main internal and external factors that interfere with the model performance in complex application scenarios are comprehensively discussed for the first time. Additionally, the advances in strategies devised to compensate for these interference are summarized. To facilitate the transition of VIS/NIR and HSI techniques for fruit SSC into practical use, future research activities should be focused on addressing the challenges in big data acquisition, sample representativeness, feature fusion, model verification and interpretation, and model improvement.
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