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Non-destructive prediction of quality of intact apple using near infrared spectroscopy

机译:使用近红外光谱技术对完整苹果品质进行无损预测

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摘要

Potential of near infrared spectroscopy (NIRS) in the wavelength range of 900–1700 nm for determination of sweetness (total soluble solids, TSS); sourness (acidity) and their ratio for 5 cultivars of apple was studied. Partial least square and multiple linear regression (MLR) employing pre-processing techniques were carried out. MLR models were found to be the best for prediction after treating the spectral data with multiple scatter correction technique. The multiple correlation coefficients for calibration and validation were found to be 0.887, 0.745 °Brix for TSS, 0.890, 0.752 % for acidity and 0.893, 0.751 for acidity/TSS ratio, respectively. The standard errors of calibration, prediction, biases and differences in them were low, which indicated that NIRS has potential to predict internal quality of apple non-destructively.
机译:在900-1700 nm波长范围内测定甜味的近红外光谱(NIRS)潜力(总可溶性固体,TSS);研究了5个苹果品种的酸度(酸度)及其比例。使用预处理技术进行了偏最小二乘和多元线性回归(MLR)。在使用多重散射校正技术处理光谱数据后,发现MLR模型最适合预测。校正和验证的多重相关系数分别为:TSS为0.887,Brix为0.745°Brix,酸度为0.890、0.752%和酸度/ TSS比为0.893、0.751。校准,预测,偏差和差异中的标准误差均很低,这表明NIRS具有无损预测苹果内部质量的潜力。

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