التفاصيل البيبلوغرافية
| العنوان: |
Real-time monitoring system for quality monitoring of jujube slice during drying process. |
| المؤلفون: |
Yuxue Cao1,2,3 452258900@qq.com, Xuedong Yao1,2,3 yaoxuedong@126.com, Yongzhen Zang1,2,3 2726498267@qq.com, Yubao Niu1,2,3 1324633525@qq.com, Hongwei Xiao1,4 xhwcaugxy@163.com, Huan Liu1,2,3 2337792832@qq.com, Rongguang Zhu1,2,3 rgzh_jd@163.com, Xia Zheng1,2,3 124899256@qq.com, Qiang Wang1,2,3 17613286@qq.com, Xiangnan Zhang1,2,3 1326388867@qq.com, Shiyu Wei5 978758380@qq.com |
| المصدر: |
International Journal of Agricultural & Biological Engineering. May2022, Vol. 15 Issue 3, p234-241. 8p. |
| مصطلحات موضوعية: |
*JUJUBE (Plant), *COMPUTER vision, *VEGETABLE drying, *COLORIMETERS, *COMPUTER monitors |
| مستخلص: |
The real-time monitoring and prediction system for quality attributes of jujube slices during the drying process was designed to solve the problem of destructive and inconvenient of the traditional quality detection method and realize quality online monitoring. Firstly, machine vision and automatic weighing were employed to monitor the color and moisture content changes of jujube slices in real-time. Secondly, correlation models between color parameter (a* value) and nutritional quality attributes (vitamin C, reducing sugar) were established to predict vitamin C and reducing sugar content of jujube slices during the drying process. Finally, the upper computer monitoring software was integrated and designed based on LABVIEW virtual instrument, and the real-time monitoring system was tested and validated. Results showed that: the changing trends of color (L*, a*, and b* values) monitored by the system were basically the same as the results detected by the color difference meter, and the average errors of L*, a*, and b* values were 0.93, 0.52, and 0.73, respectively. The average relative error of moisture content between the system monitoring and manual static detection was 0.18%. The average error of vitamin C and reducing sugar content between the system prediction and manual detection were 50 mg/100 g on dry basis and 0.71g/100 g on dry basis, respectively. The current work can provide a useful reference for real-time monitoring of quality attributes of fruits and vegetables during the drying process. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
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