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Non-destructive evaluation by Vis-NIR spectroscopy and PLS regression of soluble solids in several stone fruits..

机译:通过Vis-NIR光谱和PLS回归对几种核果中的可溶性固体进行无损评估。

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摘要

In known applications of Vis-NIR spectroscopy in non-destructive postharvest quality evaluation of fruits either a full spectrum PLS regression or a few-wavelength MLR are adopted. However, dealing with very complex matrices such as intact fruitsaccuracy at the 0.5-0.6鳥rix level over a range of values at least 5-6鳥rix wide are difficult to obtain. In this contribution experimental results are presented demonstrating the advantage of wavelength selection practices in the development of PLS regression-based calibrations for SSC of cherries, apricots, and peaches. As regards cherry, a simple spectral selection scheme (one every five lines acquired) led to satisfactory results considering only the Vis-Herschel wavelengths from 600 nm to 1100 nm.The SEP was 0.49鳥rix against a SSC standard deviation of 2.96鳥rix and a range of 15.13鳥rix. Apricot represented a more interesting case, with a SEP improvement from 0.66鳥rix to 0.43鳥rix over full spectrum PLS using exactly the same pretreatments (first derivative, 6 point gap and 3 point segment, Weighted MSC) and 9 PLS factors. In addition, retaining 7 distinct segments, only a Vis-Herschel calibration can be determined. The whole data set (162 apricots) had a SSC standard deviation of 1.95鳥rix and a range of 9.55鳥rix. The last fruit considered is peach: selecting a big number of segments, up to 19, a SEP of 0.40鳥rix was obtained for 9 PLS factors. The whole data set (108 peaches) had a SSC standard deviation of about 1.64鳥rix and a range of7.92鳥rix.
机译:在Vis-NIR光谱技术在水果非破坏性采后质量评估中的已知应用中,采用全光谱PLS回归或少数波长MLR。但是,很难处理非常复杂的矩阵,例如完整的水果精度(0.5-0.6鸟rix级别),其值范围至少为5-6鸟rix宽。在此贡献中,提供了实验结果,证明了波长选择方法在开发基于PLS回归的樱桃,杏和桃子SSC校准标定中的优势。对于樱桃,仅考虑Vis-Herschel波长从600 nm至1100 nm的简单光谱选择方案(每五行获得一个)即可获得令人满意的结果.SEP为0.49鸟rix,而SSC标准偏差为2.96鸟rix和范围为15.13鸟rix。杏子代表了一个更有趣的情况,使用完全相同的预处理(一阶导数,6点间隔和3点片段,加权MSC)和9个PLS因子,SEP比全谱PLS的SEP从0.66鸟rix提高到0.43鸟rix。此外,保留7个不同的段,只能确定Vis-Herschel校准。整个数据集(162个杏)的SSC标准偏差为1.95鸟rix,范围为9.55鸟rix。最后考虑的果实是桃子:选择大量的片段,最多19个,对于9个PLS因子,SEP为0.40鸟rix。整个数据集(108个桃子)的SSC标准偏差约为1.64鸟rix,范围为7.92鸟rix。

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