为减少有害微生物对小麦粉的污染,本文研究了电子束辐照对小麦粉的杀菌效果以及对其理化性质、流变学品质的影响。结果表明:电子束辐照处理可显著降低小麦粉中的微生物含量,且随着辐照剂量的增加,杀菌效果越显著;菌落总数、霉菌、酵母...为减少有害微生物对小麦粉的污染,本文研究了电子束辐照对小麦粉的杀菌效果以及对其理化性质、流变学品质的影响。结果表明:电子束辐照处理可显著降低小麦粉中的微生物含量,且随着辐照剂量的增加,杀菌效果越显著;菌落总数、霉菌、酵母、蜡样芽孢杆菌、需氧芽孢菌的辐照杀菌剂量D10值分别为1.94、2.12、2.69、2.51和2.46 k Gy;剂量为1~5 kGy时,辐照对小麦粉基本营养成分及氨基酸含量无明显影响;辐照后小麦粉的湿面筋含量、面筋持水率也无明显变化,但面筋指数、降落数值随着剂量增加有所减小;辐照可提高小麦粉面团的吸水率,降低形成时间和稳定时间等;面团的拉伸面积、拉伸阻力和拉伸比例等面团流变学特性参数,均呈现先升高后降低趋势,但变化幅度很小。展开更多
Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuz...Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy.展开更多
文摘为减少有害微生物对小麦粉的污染,本文研究了电子束辐照对小麦粉的杀菌效果以及对其理化性质、流变学品质的影响。结果表明:电子束辐照处理可显著降低小麦粉中的微生物含量,且随着辐照剂量的增加,杀菌效果越显著;菌落总数、霉菌、酵母、蜡样芽孢杆菌、需氧芽孢菌的辐照杀菌剂量D10值分别为1.94、2.12、2.69、2.51和2.46 k Gy;剂量为1~5 kGy时,辐照对小麦粉基本营养成分及氨基酸含量无明显影响;辐照后小麦粉的湿面筋含量、面筋持水率也无明显变化,但面筋指数、降落数值随着剂量增加有所减小;辐照可提高小麦粉面团的吸水率,降低形成时间和稳定时间等;面团的拉伸面积、拉伸阻力和拉伸比例等面团流变学特性参数,均呈现先升高后降低趋势,但变化幅度很小。
基金supported by the National Natural Science Foundation of China(61309022)
文摘Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy.
