基于熵权-逼近理想解排序法结合体外模拟消化评价功能性水稻品质

Quality evaluation of functional rice based on entropy weight-technique for order preference by similarity to ideal solution combined with in vitro simulated digestion

中文关键词:  功能性水稻  抗性淀粉  综合品质评价  熵权-TOPSIS模型，OPLS-DA

英文关键词:functional rice  resistant starch  comprehensive quality evaluation  entropy weight-technique for order preference by similarity to ideal solution  orthogonal partial least-squares discrimination analysis

中文摘要:

      目的 探究不同品种功能性水稻的品质差异性指标, 并进行综合品质评价。方法 以来源于咸宁市农业科学院的7种功能性水稻为研究对象, 对其7项基本营养成分、9种矿物质元素含量、3类淀粉含量和1种血糖预测指数共计20项营养品质指标进行对比分析, 在利用正交偏最小二乘法-判别分析(orthogonal partial least-squares discrimination analysis, OPLS-DA)筛选重要差异性指标的基础上, 建立熵权-逼近理想解排序法(technique for order preference by similarity to ideal solution, TOPSIS)模型对7种功能性水稻的综合品质进行评价。结果 不同品种功能性水稻的基本营养成分在较小范围内波动, 但钾元素含量和淀粉含量的变化范围较大, 其中水稻GN 7、GN 5、GN 6在钾元素含量方面表现较好, 水稻GN 4、GN 1、GN 3抗性淀粉含量最高, 预估血糖生成指数(estimated glycemic index, eGI)值更低, 抗消化能力优于其他品种。OPLS-DA分析筛选出锌、钠、钾、抗性淀粉、钙、镁、灰分、支链淀粉、砷、硒、直链淀粉、镉12项指标为品质差异重要性指标, 结合熵权-TOPSIS模型评价出7种功能性水稻品质的优劣顺序: GN 4、GN 1、GN 3、GN 2、GN 6、GN 5、GN 7。结论 该研究建立的品质评价模型科学、合理, 可广泛用于各类粮食果蔬的综合品质评价, 为水稻培育、种质筛选提供理论参考。

英文摘要:

      Objective To explore the quality difference index of different functional rice varieties, and evaluate the quality of functional rice. Methods Seven kinds of functional rice from the Xianning Academy of Agricultural Sciences were studied, and 20 nutritional quality indexes, including 7 basic nutrients, 9 mineral element content, 3 starch content, and 1 glycemic index, were compared and analyzed. On the basis of screening for important difference indicators with orthogonal partial least-squares discrimination analysis (OPLS-DA), the entropy weight-technique for order preference by similarity to ideal solution (TOPSIS) model was established to evaluate the comprehensive quality of 7 kinds of functional rice. Results The basic nutrients of different functional rice varieties fluctuated within a small range, but the potassium content and starch content of different functional rice varieties varied widely. Among them, the potassium content of rice GN 7, GN 5, and GN 6 was better, and the resistant starch content of rice GN 4, GN 1, and GN 3 was the highest, the estimated glycemic index (eGI) value was lower, and the anti-digestive ability was better than other varieties. Twelve indexes of zinc, sodium, potassium, resistant starch, calcium, magnesium, ash, amylopectin, arsenic, selenium, amylose, and cadmium were selected by OPLS-DA analysis as the important indexes of quality difference. The quality sequence of 7 functional rice varieties was evaluated by the entropy weight-TOPSIS model: GN 4, GN 1, GN 3, GN 2, GN 6, GN 5, GN 7. Conclusion The quality evaluation model established in this study is scientific and reasonable and can be used for comprehensive quality evaluation of various kinds of grains, fruits, and vegetables widely. It also provides theoretical references for rice breeding and germplasm screening .