Abstract:Potatoes are China’s fourth major food crop. With the government’s continuous emphasis on potato production and sales and the strategy of potato staple foods, its market share has also increased year by year. However, the quality of potatoes varies from place to place and even in the same region, which has a serious impact. The development of the potato industry. Therefore, realizing rapid non-destructive testing of potato quality has important practical significance for developing the potato staple food industry. This paper aims to develop a low-cost non-destructive rapid detection device for the potato quality. The successive projections algorithm (SPA) is used to analyze the distribution of characteristic wavelengths of potato processing quality in a spectrometer environment. According to the model results in the preprocessing state of the standard normal variate transformation (SNV), a selection of 7 bands (700,750,800,850,900,950 and 1 000 nm) is selected. Based on the potato’s special epidermal characteristics and internal texture uniformity, a handheld potato multi-quality visible/near infrared local diffuse transmission detection device is designed, including a light source module, a spectrum acquisition module, a control module, and a power supply. Module, display module, the size of the whole device is 140 mm×80 mm×70 mm, and the weight is 340 g. A potato multi-quality partial least squares prediction model was established using the research and development equipment. The root means square error of the potato dry matter and starch content prediction model verification sets were 1.05% and 1.02%, respectively. At the same time, based on the development tools of QT, the real-time analysis equipment control software was written in C language, which realized the one-click real-time non-destructive inspection of the internal quality of potatoes. Finally, the testing stability and accuracy of the R&D device were tested and verified. The results show that the developed handheld potato multi-quality sensor detection device can meet the needs of on-site real-time detection and provide technical support for developing the potato staple food industry.
王 威,李永玉,彭彦昆,杨延铭,闫 帅,马劭瑾. 手持式马铃薯品质多通道离散光谱检测装置设计与试验[J]. 光谱学与光谱分析, 2022, 42(12): 3889-3895.
WANG Wei, LI Yong-yu, PENG Yan-kun, YANG Yan-ming, YAN Shuai, MA Shao-jin. Design and Experiment of a Handheld Multi-Channel Discrete Spectrum Detection Device for Potato Processing Quality. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3889-3895.
[1] LI Zi-han, YANG Xiao-jing(李子涵,杨晓晶). Food and Nutrition in China(中国食物与营养), 2016, 22(5): 5.
[2] Subedi P P,Walsh K B. Potato Research,2009,52(1):67.
[3] López-Maestresalas Ainara, Keresztes Janos C, Goodarzi Mohammad, et al. Food Control, 2016, 70: 229.
[4] López Ainara, Arazuri Silvia, Jarén Carmen, et al. Procedia Technology, 2013, 8: 488.
[5] Rady Ahmed M., Guyer Daniel E. Postharvest Biology and Technology, 2015, 103: 17.
[6] DING Ji-gang, HAN Dong-hai, LI Yong-yu, et al(丁继刚,韩东海,李永玉,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2020, 40(6): 1909.
[7] Tiwari G, Slaughter D C,Cantwell M. Postharvest Biology & Technology,2013,86(3):221.
[8] Huang Y, Lu R, Chen K. Journal of Food Engineering,2018,236.
[9] Borba Karla R,Aykas Didem P, Milani Maria I, et al. Applied Sciences,2021,11(7):3209.
[10] LIU Ya-chao, LI Yong-yu, PENG Yan-kun, et al(刘亚超,李永玉,彭彦昆,等). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报), 2019, 50(8): 351.
[11] WANG Fan, LI Yong-yu, PENG Yan-kun, et al(王 凡,李永玉,彭彦昆,等). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报), 2018, 49(7): 348.
[12] XIAO Hui, SUN Ke, TU Kang, et al(肖 慧,孙 柯,屠 康,等). Food Science(食品科学), 2019, 40(8): 300.
[13] LIU Ya-chao, LI Yong-yu, PENG Yan-kun, et al(刘亚超,李永玉,彭彦昆,等). Chinese Journal of Analytical Chemistry(分析化学), 2019, 47(5): 785.
[14] ZHANG Jian-guang, LIU Yu-fang, SHI Rui-de(张建光,刘玉芳,施瑞德). Hebei Fruit(河北果树), 2001,(2): 11.
[15] XU Chang-jie,CHEN Wen-jun,CHEN Kun-song,et al(徐昌杰,陈文峻,陈昆松,等). Biotechnology(生物技术),1998,8(2):41.