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PREDICTING THE ORGANOLEPTIC QUALITY OF SOME ROMANIAN BEERS FROM PHYSICAL-CHEMICAL DATA USING MULTIVARIATE ANALYSIS

机译:使用多元分析从理化数据中预测某些罗马尼亚啤酒的有机质量

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摘要

Two categories of pale lager beer produced in Romania, of which twelve samples are common pale lager beer type and eight samples are superior pale lager beer type were studied to evaluate their quality through physical-chemical (apparent extract, original extract, alcohol concentration, pH, turbidity, viscosity, colour, acidity, bitterness value) and sensorial (appearance, colour, odour, taste, gas release, foam stability) characteristics. Beer characteristics measurements were examined by multivariate data analysis, using principal component analysis (PCA). The analysis of the principal components sheds light on the correlations between variables as well as on differences between the samples analyzed. The values of correlation coefficients indicate important direct statistical relations between the variables taste and alcohol concentration for all the 20 samples of beer analyzed. For the samples belonging to the category of common pale lager beer type, the values of correlation coefficients show that there are reverse statistical connections between the bitterness value and characteristics used in the sensorial analysis (p 3 0.05). For this type of beer, Skol was mostly appreciated, while for the superior pale lager beer category Ursus Premium was considered the best, both types of beer being regarded as very good quality beers according to the sensorial evaluation methodology described by SR 13355-1:1997.
机译:研究了罗马尼亚生产的两类淡啤酒,其中十二种为普通淡啤酒类型,八种为上等淡啤酒类型,通过物理化学方法(如表观提取物,原始提取物,酒精浓度,pH ,浊度,粘度,颜色,酸度,苦味值)和感官(外观,颜色,气味,味道,气体释放,泡沫稳定性)特征。使用主成分分析(PCA)通过多变量数据分析检查了啤酒的特性。主成分的分析揭示了变量之间的相关性以及所分析样品之间的差异。相关系数的值表明了所分析的所有20个啤酒样品的变量味道和酒精浓度之间的重要直接统计关系。对于属于普通淡啤酒类型的样品,相关系数的值表明,苦味值与感官分析中使用的特征之间存在反向统计联系(p 3 0.05)。对于这种类型的啤酒,Skol最受赞赏,而对于上等淡啤酒类别的Ursus Premium被认为是最好的啤酒,根据SR 13355-1描述的感官评估方法,这两种类型的啤酒均被视为非常优质的啤酒: 1997年。

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