Optical non-destructive techniques for small berry fruits: A review

被引:36
作者
Li, Shuping [1 ,3 ]
Luo, Hongpei [2 ]
Hu, Menghan [1 ,2 ]
Zhang, Miao [1 ,4 ]
Feng, Jianlin [1 ]
Liu, Yangtai [2 ]
Dong, Qingli [2 ]
Liu, Baolin [2 ]
机构
[1] East China Normal Univ, Shanghai Key Lab Multidimens Informat Proc, Shanghai 200241, Peoples R China
[2] Univ Shanghai Sci & Technol, Sch Med Instrument & Food Engineenng, 516 Jun Gong Rd, Shanghai 200093, Peoples R China
[3] East China Normal Univ, Meng Xiancheng Coll ECNU, Shanghai 200241, Peoples R China
[4] East China Normal Univ, Coll Fine Arts, Shanghai 200241, Peoples R China
来源
ARTIFICIAL INTELLIGENCE IN AGRICULTURE | 2019年 / 2卷
基金
中国博士后科学基金;
关键词
Berry fruit; Optical non-destructive measurement; Food quality and safety; RESOLVED DIFFUSE-REFLECTANCE; NEAR-INFRARED SPECTROSCOPY; SOLUBLE SOLIDS CONTENT; QUALITY INSPECTION; NIR SPECTROSCOPY; COMPUTER VISION; HYPERSPECTRAL TRANSMITTANCE; BLUEBERRY FRUIT; IMAGE-ANALYSIS; QUANTITATIVE-ANALYSIS;
D O I
10.1016/j.aiia.2019.07.002
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Small berries including strawberry and blueberry are extensively consumed fruits with great economic values due to their characteristic flavor and appearance as well as potential health benefits. This review elaborated the optical non-destructive techniques viz. Vis-NIR spectroscopy, computer vision system, hyperspectral imaging, multispectral imaging, laser-induced method and thermal imaging, and their applications for quality and safety control of small berry fruits. The discussion regarding the photoacoustic technique, X-ray technique, Terahertz spectroscopy, odor imaging, micro-destructive testing and smart mobile terminal-based analyzer was also presented. Furthermore, we proposed our personal understanding of the technical challenges and further trends for these optical non-des tructive techniques: 1) owing to the relatively low detection limit, the so-called micro-destructive techniques may be alternative to the traditional non-destructive techniques in both practical and fundamental research; 2) we suggest that the research articles like "collecting data first, and then modeling the relevant properties of agricultural products by machine learning" should be less produced in related fields. That's because such research methods are likely to be suspected of "cheating". It is recommended that some modeling competitions can be carried out in the agricultural engineering field to avoid or reduce the "cheating" model.& COPY; 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:85 / 98
页数:14
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