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首页> 外文期刊>Food Bioscience >Determination of starch content in adulterated fresh cheese using hyperspectral imaging
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Determination of starch content in adulterated fresh cheese using hyperspectral imaging

机译：高光谱成像的掺假新鲜奶酪中淀粉含量的测定

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摘要

The aim of this study was to measure the starch content in adulterated fresh cheese using hyperspectral imaging technique. Adulterated fresh cheese was prepared using concentrations of starch of 0.055–12.705mgg?1(0.0055–1.2705%); subsequently, hyperspectral imaging in the range of 200–1000nm, distributed in 101 bands were acquired. The modeling of starch content was performed by the method of partial least squares regression (PLSR). A correlation coefficient (R2) of 0.9915 and a Root Mean Square Error of cross-validation (RMSECV) of 0.3979 was obtained. With five latent variables, a correlation coefficient of validation (R2) of 0.8321 and a RMSEP of 1.3515 was obtained for a reduced model.Highlights?Non-destructive method to predict the starch content in adulterated fresh cheese by hyperspectral imaging.?PLSR was applied to establish the calibration and prediction models.?Starch content in fresh cheese can be predicted accurately based on hyperspectral imaging data.?The most important wavelength for the detection and prediction of starch in fresh cheese is 584nm.
机译：本研究的目的是使用高光谱成像技术测量掺假新鲜奶酪中的淀粉含量。使用0.055-12.705MGG的浓度〜1（0.0055-1.2705％）制备掺杂的新鲜奶酪;随后，获取在200-1000nm的范围内的高光谱成像，分布在101个带中。通过偏最小二乘回归（PLSR）的方法进行淀粉含量的建模。得到0.9915的相关系数（R2）和0.3979的交叉验证（RMSECV）的均方根误差。利用五个潜在变量，获得了0.8321的相关验证系数（R2）和1.3515的RMSEP，用于降低的模型.Highlights？非破坏性方法以预测掺假斑型奶酪中的淀粉含量通过高光谱成像。应用为了建立校准和预测模型。可以基于高光谱成像数据准确地预测新鲜奶酪中的校准和预测模型。新鲜奶酪中淀粉的检测和预测最重要的波长是584nm。

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