近红外光谱法对高酸柑橘的分类

K. Miyamoto, Miyuki Kawauchi, Toshitaka Fukuda
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引用次数: 5

摘要

用近红外透射光谱法在线测定了蜜橘中糖的含量。探讨了同时测定柠檬酸含量的可行性。采用unscbler软件,用PLS1分析了NaOH滴定法测定的柠檬酸含量和710 ~ 930 nm范围内自动标度的二阶导数吸收值。用NIR系统模型6250对去皮水果的光谱进行了分析,结果表明,由12个因子组成的模型精度最高;R为0.93,平均残差(Bias)为-0.013%,预测标准误差(SEP)为0.146%。采用在线回归法对完整柑橘中柠檬酸含量进行了回归分析。由5个因子组成的模型对689个样本进行了校正,结果表明模型的准确度最高;548个样本的预测结果R=0.83, Bias=0.024%, SEP=0.147%。利用近红外光谱对高酸果进行无损分类是可行的,误差率约为20%。
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Classification of High Acid Satsuma Mandarins by Near Infrared Transmittance Spectroscopy
On-line measurement of sugar content in satsuma mandarins was already achieved using NIR transmittance spectroscopy. The feasibility of simultaneous measurement of citric acid content was investigated. The citric acid content determined by titration with NaOH and the second derivative absorption values autoscaled in the 710-930 nm region were analyzed by PLS1 using Unscrambler software. The spectra of peeled fruits measured by an NIR Systems Model 6250 were analyzed, and the model composed of 12 factors indicated the highest accuracy; R was 0.93, the mean residual (Bias) was -0.013% and the standard error of prediction (SEP) was 0.146%. The citric acid content in intact satsuma mandarins was regressed by the same method using an on-line instrument. The model composed of 5 factors calibrated from 689 samples showed the highest accuracy; R=0.83, Bias=0.024% and SEP=0.147% as a prediction result from 548 samples. It was possible to classify nondestructively the high acid fruits using near infrared (NIR) transmittance spectroscopy at about 20% error rate.
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