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Potable NIR spectroscopy predicting soluble solids content of pears based on LEDs

机译:基于LED的梨子可溶性固体含量可溶性NIR光谱法

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A portable near-infrared (NIR) instrument was developed for predicting soluble solids content (SSC) of pears equipped with light emitting diodes (LEDs). NIR spectra were collected on the calibration and prediction sets (145:45). Relationships between spectra and SSC were developed by multivariate linear regression (MLR), partial least squares (PLS) and artificial neural networks (ANNs) in the calibration set. The 45 unknown pears were applied to evaluate the performance of them in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r). The best result was obtained by PLS with RMSEP of 0.62°Brix and r of 0.82. The results showed that the SSC of pears could be predicted by the portable NIR instrument.
机译:用于预测配备有发光二极管(LED)的可溶性固体含量(SSC)的便携式近红外(NIR)仪器。在校准和预测集上收集NIR光谱(145:45)。光谱和SSC之间的关系是由校准组中的多元线性回归(MLR),局部最小二乘(PLS)和人工神经网络(ANNS)开发的。应用45个未知的梨以评估它们的性能,从预测(RMSEP)和相关系数(R)的根均方误差方面。通过PLS获得最佳结果,RMSEP为0.62°BRIX和r为0.82。结果表明,便携式NIR仪器可以预测梨SSC。

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