Breakpoint Planning Method for Rice Multibreak Milling

• Published in: Foods Vol. 12; no. 9; p. 1864
• Main Authors: Xiao, Yawen, Jia, Fuguo, Meng, Xiangyi, Han, Yanlong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 30.04.2023; MDPI
• Subjects: Analysis; Breakpoints; breakpoints planning; Food science; Friction; generalized regression neural network; Grain; Grain industry; hierarchical cluster analysis; Kernels; Methods; multibreak milling; Multivariate analysis; Nutrient loss; Physical properties; Polyethylene; principal component analysis; Rice; Scanning electron microscopy; China; breakpoints planning; hierarchical cluster analysis; multibreak milling; generalized regression neural network; principal component analysis
• ISSN: 2304-8158; 2304-8158
• DOI: 10.3390/foods12091864

Excessive milling of rice kernels will result in nutrient loss and grain waste. To avoid grain waste, multibreak milling systems have been widely used in large-scale commercial rice mills. However, there is still no reasonable breakpoint planning method to guide the multibreak milling process. To construct a reasonable multibreak milling system, in this research, taking rice milling, a typical heterogeneous cereal-kernel milling process, as an example, the multivariate analysis method was used to comprehensively analyze the characteristic changes of milled rice during the whole milling process. A breakpoint planning method was established, including planning the number of breakpoints, determining the degree of milling or milling time corresponding to each breakpoint, and estimating the actual breakpoint to which the milled rice belongs. The verification results showed the rationality and high accuracy of the planning method. The presented work will help operators to plan the multibreak milling system of rice efficiently and objectively so as to significantly improve the commercial value of milled rice.