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以苹果为试材,采用电子感官与化学计量学相结合的方法,采用偏最小二乘法(PLS)进行回归,建立贮藏期有机酸、固形物含量的数学模型,并对回归方法进行统计分析,以找到快速测定苹果贮藏期和贮藏期间总酸和固形物含量的方法。结果表明:电子鼻第1、2主成分贡献率总计达到了90.616%,区分效果良好;苹果中总酸验证集的决定系数(R_v~2)为0.906 3,预测均方根误差(RMSEP)为0.888 1,RPD为2.75;固形物含量验证集的决定系数(R_v~2)为0.917 0,预测均方根误差(RMSEP)为0.747,RPD为2.69,均达到了较好的预测结果,表明该方法对快速检测苹果贮藏期和贮藏期总酸和固形物含量是可行的。
Using apple as the test material, using the combination of electronic sensory and chemometrics methods, the partial least squares (PLS) regression was used to establish the mathematical model of organic acid and solid content during storage, and the statistical analysis of the regression method, To find a quick method to determine the total acid and solid content of apple during storage and storage. The results showed that the total contribution rate of the first and second principal components of electronic nose reached 90.616%, and the discriminating effect was good. The determination coefficient (R_v ~ 2) of the total acid validation set in apple was 0.906 3. The root mean square error of prediction (RMSEP) 0.888 1 and RPD was 2.75. The coefficient of determination (R_v ~ 2) for the validation set of solid content was 0.917 0, the root mean square error of prediction (RMSEP) was 0.747, and the RPD was 2.69, all of which achieved good predictions, The method is feasible for rapid detection of total acid and solid content in apple during storage and storage.