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利用近红外技术鉴别干酪的季节性。

Discrimination of seasonality in cheeses by near-infrared technology.

机构信息

Departamento de Química Analítica, Nutrición y Bromatología, Facultad de Ciencias Químicas, C/Plaza de la Merced s/n, E-37008 Salamanca, Spain.

出版信息

J Sci Food Agric. 2011 Apr;91(6):1064-9. doi: 10.1002/jsfa.4283. Epub 2011 Feb 15.

Abstract

BACKGROUND

Owing to the importance of the season of collection of milk for cheese quality, a study was made of the usefulness of near-infrared spectroscopy (NIRS) for discriminating the seasonal origin (winter or summer) of milk and quantifying the fat content of cheeses, since fat is one of the components most affected by the season of collection of milk for the elaboration of cheeses.

RESULTS

In the internal validation, 96% of samples from winter milk and 97% of samples from summer milk were correctly classified, while in the external validation the prediction rate of samples correctly classified was 92%. Moreover, quantitative models allowed the determination of fat in winter, summer and winter + summer cheeses.

CONCLUSION

Rapid prediction of the fat content of cheeses and the seasonal origin (winter or summer) of milk was achieved using NIRS without previous destruction or treatment of samples.

摘要

背景

由于牛奶采集季节对奶酪质量的重要性,本研究旨在探讨近红外光谱(NIRS)在鉴别牛奶的季节性来源(冬季或夏季)和定量奶酪脂肪含量方面的应用,因为脂肪是受牛奶采集季节影响最大的奶酪成分之一。

结果

内部验证中,96%的冬季牛奶样本和 97%的夏季牛奶样本被正确分类,而外部验证中正确分类的样本预测率为 92%。此外,定量模型允许测定冬季、夏季和冬夏混合奶酪中的脂肪。

结论

无需对样品进行预处理或破坏,即可使用 NIRS 快速预测奶酪的脂肪含量和牛奶的季节性来源(冬季或夏季)。

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