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中国精品科技期刊2020
邓慧清,吴卫国,廖卢艳. 基于主成分分析法构建高蛋白重组米品质评价体系[J]. 食品工业科技,2022,43(20):78−86. doi: 10.13386/j.issn1002-0306.2021120279.
引用本文: 邓慧清,吴卫国,廖卢艳. 基于主成分分析法构建高蛋白重组米品质评价体系[J]. 食品工业科技,2022,43(20):78−86. doi: 10.13386/j.issn1002-0306.2021120279.
DENG Huiqing, WU Weiguo, LIAO Luyan. Development of the Quality Evaluation System of High Protein Recombinant Rice by Principal Component Analysis[J]. Science and Technology of Food Industry, 2022, 43(20): 78−86. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021120279.
Citation: DENG Huiqing, WU Weiguo, LIAO Luyan. Development of the Quality Evaluation System of High Protein Recombinant Rice by Principal Component Analysis[J]. Science and Technology of Food Industry, 2022, 43(20): 78−86. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021120279.

基于主成分分析法构建高蛋白重组米品质评价体系

Development of the Quality Evaluation System of High Protein Recombinant Rice by Principal Component Analysis

  • 摘要: 为探究高蛋白重组米品质指标间相互关系,以碎米与16种常见蛋白粉为原料通过挤压分别制备16种高蛋白重组米,测定高蛋白重组米质构特性、蒸煮特性、糊化度、水溶性指数、吸水性指数、膨化度,并运用主成分分析法计算不同高蛋白重组米的综合得分,通过逐步回归对高蛋白重组米品质的评价指标进行筛选,构建其综合评价体系。结果表明,不同蛋白制备的高蛋白重组米蒸煮品质指标以及质构品质指标差异较大。主成分分析提取的3个主成分累计贡献率达到了85.148%,分别是59.4725%(X1)、17.527%(X2)、8.149%(X3),其中,胶粘性、米汤干物质、硬度、吸水性指数、咀嚼性、内聚性、糊化度、回复性、大米吸水率对第一主成分起主要作用;弹性、膨化度和碘蓝值对第二主成分起主要作用;水溶性指数是第三主成分的重要指标。以主成分分析得到的各高蛋白重组米综合得分为因变量(F值),以参加主成分分析的各指标值为自变量,通过逐步回归分析法建立高蛋白重组米综合品质评价的理论模型:Y=0.915X胶粘性+0.208X糊化度−0.475X米汤干物质+0.436X回复性。该模型得出高蛋白重组米的质量最优为大米蛋白重组米,其次为大豆分离蛋白重组米,与主成分综合得分呈极显著正相关(P<0.01),进一步证实该模型具有很高的可靠性。

     

    Abstract: In order to explore the relationship among quality indexes of high protein recombinant rice, 16 kinds of high protein recombinant rice were prepared by extrusion using broken rice and 16 kinds of common protein powder as raw materials. The texture properties, cooking characteristics, gelatinization degree, water solubility index, water absorption index and expansion degree of high protein recombinant rice were determined, and the comprehensive scores of different high protein recombinant rice were calculated by principal component analysis. The quality evaluation index of high protein recombinant rice was screened by stepwise regression, and the comprehensive evaluation system was constructed. The results showed that the cooking quality indexes and texture quality indexes of high protein recombinant rice prepared by different proteins were quite different. The cumulative contribution rate of the three principal components extracted by principal component analysis reached 85.148%, which were 59.4725%(X1), 17.527%(X2) and 8.149%(X3), respectively. Gumminess, dissolution of solid material, hardness, water absorption index, chewiness, cohesion, gelatinization degree, resilience and rice water absorption played a major role in the first principal component, while elasticity, expansion and iodine blue value played a major role in the second principal component. Water solubility index was an important index of the third principal component. Taking the comprehensive score of high protein recombinant rice obtained by principal component analysis as dependent variable (F value), and each index value participating in principal component analysis as independent variable, the theoretical model of comprehensive quality evaluation of high protein recombinant rice was established by stepwise regression analysis: Y=0.915Xgumminess+0.208Xgelatinization degree−0.475Xdissolution of solid material+0.436Xresilience. According to the model, the best quality of high protein recombinant rice was rice protein recombinant rice, followed by soybean protein isolate recombinant rice, having a good agreement and significant positively correlated with the comprehensive score of principal components (P<0.01), which further confirmed that the model had high reliability.

     

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