不同籼米品种米饭加工适宜性研究  

Evaluation of rice processing suitability for different varieties of indica rice

作　　者：米永洁 王振华[1] 张敏[1] 关丽娜 李思萱 MI Yongjie;WANG Zhenhua;ZHANG Min;GUAN Lina;LI Sixuan(Beijing Advanced Innovation Center for Food Nutrition and Human Health,Beijing Engineering and Technology Research Center of Food Additives,Beijing Technology and Business University,Beijing 100048,China)

机构地区：[1]北京工商大学食品营养与人类健康北京高精尖创新中心,北京市食品添加剂工程技术研究中心,北京100048

出　　处：《河南工业大学学报（自然科学版）》2024年第3期58-68,共11页Journal of Henan University of Technology：Natural Science Edition

基　　金：食品科学与工程领域人才培养质量和一流专业(市级)计划。

摘　　要：为了筛选适宜米饭加工的优质籼米品种,建立米饭加工适宜性评价模型,以我国20种代表性籼米为原料,采用描述性分析及相关性分析探究了大米品质与米饭品质的关系,筛选出籼米品质指标中变异系数大于10%且与米饭品质有显著相关性的16个核心评价指标。采用最大-最小归一化方法将米饭11项品质指标转化为一维的综合品质评价指标,并与筛选出的籼米品质指标建立加工适宜性模型,对比逐步回归、偏最小二乘法、支持向量机和神经网络4种模型,发现神经网络建立的模型拟合度最高,决定系数为0.9998,该模型可快速准确预测米饭品质综合得分,判断不同籼米品种米饭加工适宜性。通过聚类分析确定了5种适宜制作米饭的优质籼米品种,分别为粮发香油占、广粮香2号、天优华占、广粮香丝、湘早籼45。本研究可为籼米米饭综合品质评价和育种选择提供科学依据。In order to screen high-quality indica rice varieties suitable for rice processing,and establish a model for evaluating the suitability of rice processing.Twenty indica rice varieties with large planting area,high yield or pleasant taste in China were selected as raw materials for rice production.Correlation analysis and descriptive analysis were used to investigate the relationship between rice appearance quality,nutritional quality,cooking quality,and gelatinization characteristics with textural characteristics and sensory quality of rice.Sixteen core evaluation indicators with a variation coefficient greater than 10%and a significant correlation with rice quality were selected.They were whiteness,width,aspect ratio,moisture content,protein content,amylose content,straight branch ratio,taste value,valley viscosity,disintegration value,final viscosity,retrogradation value,iodine blue value,water absorption,expansion rate,and dry matter of rice soup.Using the maximum-minimum normalized method,multiple quality indicators of rice were calculated into a one-dimensional evaluation indicator.The obtained one-dimensional data were used as the comprehensive rice quality score,which were significantly correlated with the sensory score and the fitting degree was 0.824.A processing suitability model was established based on the screened rice raw material quality indicators and the rice comprehensive quality score.By comparing the fitting quality of the four methods,namely,stepwise regression,partial least squares,support vector machine,and neural network models,the integrated rice quality was predicted.The model built using stepwise regression was simple,had good fitting effect,and could quickly predict the comprehensive quality score of rice.The model built using neural network had the highest fitting degree,with a model determination coefficient of R^(2) of 0.9998 and a root mean square error RMSE of 0.008.Using the neural network model,the comprehensive quality score of rice could be accurately predicted,and the suitabi

关 键 词：米饭 偏最小二乘法 支持向量机 神经网络 加工适宜性 

分 类 号：TS212[轻工技术与工程—粮食、油脂及植物蛋白工程]