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Research of the Measurement on Palmitic Acid in Edible Oils by Near-Infrared Spectroscopy

机译:近红外光谱法测定食用油中棕榈酸的研究

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A method for determination of palmitic acid in edible oils by the near-infrared spectroscopy was addressed in this paper. 56 samples were collected in the experiment. In terms of concentration content gradient method, 44 samples were selected for modeling set and 12 for testing set. This paper described the utilization of PLS for establishing a quantitative analysis model for predicting the content of palmitic acid in edible oils by near-infrared spectroscopy. The result shows that the model has a high accuracy for predicting the palmitic acid content with vector normalization and first-derivative preprocessing spectra with its best main factorial number of 8.The determination coefficients (R2), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and average bias are 99.59, 0.162, 0.306 and 0.148, respectively. The model used in the paper can be adopted for the measurement of palmitic acid in edible oils accurately.
机译:本文提出了一种通过近红外光谱法测定食用油中棕榈酸的方法。实验中收集了56个样品。根据浓度含量梯度法,选择了44个样品作为模型集,选择了12个样品作为测试集。本文描述了利用PLS建立定量分析模型以通过近红外光谱预测食用油中棕榈酸含量的方法。结果表明,该模型通过矢量归一化和一阶导数预处理光谱预测棕榈酸含量具有很高的准确性,其最佳主因子数为8.确定系数(R2),交叉验证的均方根误差(RMSECV) ),预测的均方根误差(RMSEP)和平均偏差分别为99.59、0.162、0.306和0.148。本文所采用的模型可用于准确测量食用油中的棕榈酸。

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