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Non-destructive prediction of total soluble solids, titratable acidity and maturity index of limes by near infrared hyperspectral imaging

机译:通过近红外高光谱成像的无损性预测总可溶性固体,可滴定酸度和石浆成熟度指数

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摘要

This study was implemented for non-destructive prediction of total soluble solids (TSS), titratable acidity (TA) and calculation of TSS/TA as a measure of maturity index in intact limes using laboratory-based push-broom hyperspectral imaging (HSI) in reflectance mode in the range of 929-1671 nm. Limes were scanned by the HSI system in order to develop calibration models for predicting TSS, TA and TSS/TA using partial least square regression (PLSR). Original spectra obtained optimal conditions for establishing the models for TSS and TA while smoothing spectra for TSS/TA. The accuracy of the models for TSS, TA and TSS/TA provided coefficient of determination of prediction (R-P(2)) of 0.838, 0.694 and 0.775, respectively and root mean square errors of prediction (RMSEP) of 0.237%, 0.288% and 0.049, respectively. Image processing algorithms were then built up by interpreting predictive values, from the models, to colors in each pixel of the images. The predictive visualization of TSS, TA and TSS/TA in all portions of the limes based on a color scale was presented. The results showed that the HSI technique has the capability of predicting TSS, TA and TSS/TA of intact limes non-destructively and the results could be visualized by different colors of the predictive images.
机译:本研究用于对总可溶性固体(TSS)的非破坏性预测,可滴定酸度(TA)和TSS / TA的计算,以及使用基于实验室的推送扫帚高光谱成像(HSI)的完整性石灰的成熟度指数的量度反射模式在929-1671 nm的范围内。通过HSI系统扫描雷米,以便使用部分最小二乘回归(PLSR)来开发用于预测TSS,TA和TSS / TA的校准模型。原始光谱获得了建立TSS和TA模型的最佳条件,同时平滑TSS / TA的光谱。 TSS,TA和TS / TA的模型的准确性提供了预测的测定系数(RP(2))分别为0.838,0.694和0.775的预测(RMSEP)的均线平均误差为0.237%,0.288% 0.049分别。然后通过将预测值从模型中解释为图像的每个像素中的颜色来构建图像处理算法。提出了基于颜色刻度的晶粒的所有部分的TSS,TA和TS / Ta的预测性可视化。结果表明,HSI技术的能力是非破坏性地预测完整酸值的TSS,TA和TSS / TA,并且可以通过预测图像的不同颜色可视化结果。

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