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傅里叶变换中红外光谱在磅蛋糕贮藏过程中品质监测中的应用。

Application of Fourier-transform mid infrared spectroscopy for the monitoring of pound cakes quality during storage.

机构信息

Univ. Artois, EA 7394, Institut Charles VIOLLETTE, Lens F-62300, France.

Univ. Artois, EA 7394, Institut Charles VIOLLETTE, Lens F-62300, France; ISA Lille, EA 7394, Institut Charles VIOLLETTE, Lille F-59000, France; Ulco, EA 7394, Institut Charles VIOLLETTE, Boulogne sur Mer F-62200, France; Univ. Lille, EA 7394, Institut Charles VIOLLETTE, Lille F-59000, France; ADRIANOR, Tilloy Les Mofflaines F-62217, France.

出版信息

Food Chem. 2018 Jun 30;252:327-334. doi: 10.1016/j.foodchem.2018.01.122. Epub 2018 Jan 31.

Abstract

The aim of the present study was to investigate the ability of MIR and texture analyzer to evaluate the quality of pound cake samples produced with palm oil and rapeseed oil throughout storage. The MIR spectra analyzed by using principal component analysis (PCA) showed a clear separation of pound cakes as a function of the storage time and the nature of the used oil in the recipe. By applying partial least square regression (PLSR), excellent prediction was obtained for hardness (R = 0.91; RPD = 2.26), while an approximate qualitative prediction was found for springiness (R = 0.73; RPD = 2.07), cohesiveness (R = 0.67; RPD = 1.31) and resilience (R = 0.65; RPD = 1.24). It could be concluded that the MIR spectroscopy could be used as a rapid and non-destructive technique for monitoring texture of pound cakes throughout storage as well as for the prediction of their hardness.

摘要

本研究旨在探讨 MIR 和质地分析仪评估使用棕榈油和油菜籽油制作的磅蛋糕样品在储存过程中质量的能力。通过主成分分析(PCA)分析的 MIR 光谱显示,磅蛋糕可以根据储存时间和配方中使用的油的性质进行清晰的分离。通过应用偏最小二乘回归(PLSR),可以对硬度进行极好的预测(R=0.91;RPD=2.26),而对弹性(R=0.73;RPD=2.07)、内聚性(R=0.67;RPD=1.31)和回弹性(R=0.65;RPD=1.24)的预测则较为近似定性。可以得出结论,MIR 光谱学可以用作一种快速、非破坏性的技术,用于监测磅蛋糕在储存过程中的质地,并预测其硬度。

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