The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native ba...The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native barley varieties were chosen with the detection of 24 quality indexes in order to build a system of comprehensive evaluation.The results of the factor analysis indicated that seven common factors with an eigenvalue greater than 1 were extracted,cumulatively accounting for 96.21%of the total variance.The first common factor,including ASP,GLU,SER,GLY,ARG,TYR and CYS contents,accounted for 33.82% of the variance.The second common factor,including ash,the total starch,soluble fiber,VB_(3),Cu,Mn,Na and beta-glucan contents,accounted for 19.46%of the variance.The third common factor,including the total dietary fiber,α-VE,K,Zn and glutelin.The fourth common factor,including B,Ba and prolamin,explained the barley starch character of the rheological property.The fifth common factor included crude fiber.The sixth and the seventh common factors did not account for a substantial amount of variance.According to the comprehensive evaluation model,the score consequence was as the following:Zangqing25>Pengnaigabu>Lhasa changhei>2004Qing21>Lhasa duanbai>Liangamu>Zhikonggaxia>lianmubai>Jiangreejiu>Longzihei.展开更多
【目的】客观评价城市环境空气质量并分析其影响因素,对了解空气质量现状,控制污染源具有重要意义。【方法】依据污染因子浓度监测值构建基于模糊数学综合评价法的环境空气质量评价方法用于长治市的环境空气质量评价,并对首要污染因子...【目的】客观评价城市环境空气质量并分析其影响因素,对了解空气质量现状,控制污染源具有重要意义。【方法】依据污染因子浓度监测值构建基于模糊数学综合评价法的环境空气质量评价方法用于长治市的环境空气质量评价,并对首要污染因子与其他污染因子进行斯皮尔曼相关性分析。【结果】采用阶梯型隶属度函数的模糊综合评价法相较AQI(Ambient Air Quality Index)和内梅罗指数法能够综合所有污染因子的作用更加全面评价环境空气质量,且长治市2017—2022共6年间环境空气质量状况在逐渐好转。长治市的首要污染因子为PM_(10),且与PM_(2.5)、SO_(2)、NO_(2)、CO均具有相关性,相关性依次递减,而与O_(3)不具相关性。通过污染因子时间分布特征分析发现,每年一、四季度PM_(2.5)、PM_(10)、CO、NO_(2)、SO_(2)的浓度会上升,二、三季度5种污染因子的浓度呈现下降趋势,并且一、四季度5项污染因子的浓度值高于二、三季度。新冠肺炎疫情暴发期间,所有污染因子均呈现下降趋势,且CO浓度的下降趋势最为明显。展开更多
基金Supported by Chnia Agriculture Research Systemthe Scientific Research Fund of the Key Technology and Research and Development of Barley Characteristic Agricultural Products Processing(XZ201901NA04)Development and Industrialization Application of Xizang Highland Barley Baijiu(XZ202001ZY0017N)。
文摘The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native barley varieties were chosen with the detection of 24 quality indexes in order to build a system of comprehensive evaluation.The results of the factor analysis indicated that seven common factors with an eigenvalue greater than 1 were extracted,cumulatively accounting for 96.21%of the total variance.The first common factor,including ASP,GLU,SER,GLY,ARG,TYR and CYS contents,accounted for 33.82% of the variance.The second common factor,including ash,the total starch,soluble fiber,VB_(3),Cu,Mn,Na and beta-glucan contents,accounted for 19.46%of the variance.The third common factor,including the total dietary fiber,α-VE,K,Zn and glutelin.The fourth common factor,including B,Ba and prolamin,explained the barley starch character of the rheological property.The fifth common factor included crude fiber.The sixth and the seventh common factors did not account for a substantial amount of variance.According to the comprehensive evaluation model,the score consequence was as the following:Zangqing25>Pengnaigabu>Lhasa changhei>2004Qing21>Lhasa duanbai>Liangamu>Zhikonggaxia>lianmubai>Jiangreejiu>Longzihei.
文摘【目的】客观评价城市环境空气质量并分析其影响因素,对了解空气质量现状,控制污染源具有重要意义。【方法】依据污染因子浓度监测值构建基于模糊数学综合评价法的环境空气质量评价方法用于长治市的环境空气质量评价,并对首要污染因子与其他污染因子进行斯皮尔曼相关性分析。【结果】采用阶梯型隶属度函数的模糊综合评价法相较AQI(Ambient Air Quality Index)和内梅罗指数法能够综合所有污染因子的作用更加全面评价环境空气质量,且长治市2017—2022共6年间环境空气质量状况在逐渐好转。长治市的首要污染因子为PM_(10),且与PM_(2.5)、SO_(2)、NO_(2)、CO均具有相关性,相关性依次递减,而与O_(3)不具相关性。通过污染因子时间分布特征分析发现,每年一、四季度PM_(2.5)、PM_(10)、CO、NO_(2)、SO_(2)的浓度会上升,二、三季度5种污染因子的浓度呈现下降趋势,并且一、四季度5项污染因子的浓度值高于二、三季度。新冠肺炎疫情暴发期间,所有污染因子均呈现下降趋势,且CO浓度的下降趋势最为明显。