Zhu Min, Chen Ping, Hu Xin-Jun, Mao Xiang, Tian Jian-Ping, Luo Hui-Bo, Huang Dan
College of Bioengineering Sichuan University of Science & Engineering Zigong City China.
Food Sci Nutr. 2019 Nov 27;8(1):179-189. doi: 10.1002/fsn3.1289. eCollection 2020 Jan.
Lack of moisture can lead to the aging of pit mud, excessive moisture will make it difficult to maintain its shape or even collapse. Therefore, a rapid and nondestructive detection technology for moisture in pit mud using hyperspectral imaging was firstly investigated. Modeling efficiency of various processing was compared in visible (400-1,000 nm) and near-infrared (900-1,700 nm) regions, and the optimal model was SNV-SPA-SVM in near-infrared spectroscopy; the and RMSEP of model were .9953 and 0.0029, respectively. Furthermore, the distribution map showed that the moisture in the new cellar was generally lower than that of old, and the moisture distribution of the old pit mud was more even. Moreover, the moisture content of different layers in the same cellar increased from top to bottom. This work provides strong technical support for liquor brewing enterprises to effectively implement online monitoring of pit mud changes and open a new era for the application of hyperspectral imaging technology in the field of liquor solid-state fermentation.
水分不足会导致窖泥老化,水分过多则会使其难以保持形状甚至坍塌。因此,首先研究了一种利用高光谱成像技术对窖泥水分进行快速无损检测的技术。比较了在可见光(400 - 1000 nm)和近红外(900 - 1700 nm)区域各种处理的建模效率,最佳模型是近红外光谱中的SNV - SPA - SVM;模型的 和RMSEP分别为0.9953和0.0029。此外,分布图显示新窖泥中的水分普遍低于老窖泥,老窖泥的水分分布更均匀。而且,同一窖池中不同层的水分含量从顶部到底部逐渐增加。这项工作为白酒酿造企业有效实施窖泥变化的在线监测提供了有力的技术支持,并为高光谱成像技术在白酒固态发酵领域的应用开启了新的时代。