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Measurement of Protein Content in Sesame by Near-infrared Spectroscopy Technique

机译:近红外光谱技术测定芝麻中蛋白质含量

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The model of determining sesame protein was built using near infrared spectroscopy (NIRS) and the FOSS system as the analyzer. The influences on the model of factors, such as the mathematics methods and optics treatment methods were studied. The results of model validation showed that the best factors were SNV only for optics treatment method and "3, 3, 3, 1" for mathematics method. The average determination coefficient of validation (RSQ) was 0.9826, the square error of cross (SEC) was 0.2313, the correlation coefficient (1-VR) was 0.7272, the square error of cross validation (SECV) was 0.9134, the average determination coefficient of validation (RSQ) was 0.896, and the standard error of prediction (SEP) was 0.827. This model could determine the protein content in sesame used as a rapid method to detect the quality of sesame seeds.
机译:使用近红外光谱(NIRS)和FOSS系统作为分析器,建立了芝麻蛋白测定模型。研究了数学方法和光学处理方法等因素对模型的影响。模型验证的结果表明,最佳因素仅对于光学治疗方法是SNV,对于数学方法而言是“ 3、3、3、1”。验证的平均确定系数(RSQ)为0.9826,交叉的平方误差(SEC)为0.2313,相关系数(1-VR)为0.7272,交叉验证的平方误差(SECV)为0.9134,平均确定系数验证有效期(RSQ)为0.896,预测标准误(SEP)为0.827。该模型可以确定芝麻中的蛋白质含量,以此作为检测芝麻质量的快速方法。

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