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Quantification of acidity and total soluble solids in guavas by near infrared hyperspectral imaging

机译:近红外高光谱成像的族酸度的定量酸度和总可溶性固体

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In order to provide premium quality for marketing of guavas the titratable acidity (TA) and total soluble solids (TSS) levels should be determined. A reflectance near infrared hyperspectral imaging (NIR-HSI) unit in the wavelength range of 936-1696 nm, which is a nondestructive technique, was tested for use in predicting TA and TSS. Samples of 100 guavas were scanned by NIR-HIS as a group for calibration (N=67) and as a group for prediction (N=33). The average spectra from the region of interest (ROI) of samples were used to establish the calibration models for TA and TSS by using partial least squares regression (PLSR) to establish calibration models. The calibration model for TA gave a coefficient of determination (R~2) of 0.972 and the root mean square error of prediction (RMSEP) of 0.010% and for TSS the R~2 was 0.801 and the RMSEP was 0.437°Bx. The accuracies of these results indicate that NIR-HSI has potential for use in measuring TA and TSS of guavas.
机译:为了提供促销促销销售的溢价质量,应确定可滴定的酸度(TA)和总可溶性固体(TSS)水平。在936-1696nm的波长范围内的近红外高光谱成像(NIR-HSI)单元的反射率被测试用于预测TA和TS的预测。 NIR-HIR作为校准(n = 67)的组和作为预测的组的群组扫描了100个Guavas的样本(n = 33)。来自样本的感兴趣区域(ROI)的平均光谱用于通过使用偏最小二乘回归(PLSR)来建立TA和TSS的校准模型来建立校准模型。 Ta的校准模型得到0.972的测定系数(R〜2),预测(RmSep)的根部均方误差为0.010%,对于TSS的R〜2为0.801,RmSep为0.437°Bx。这些结果的准确性表明,NIR-HSI具有用于测量GUAVAS的TA和TS的可能性。

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