Quantification of Condensed Tannins in Sainfoin Powder (Onobrychisviciifolia) by FT-NIR Spectroscopy

C. Camps, S. Werne, M. Quennoz, X. Simonnet, C. Gilli
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引用次数: 1

Abstract

Models based on FT-NIR spectroscopy and PLS-regressions were developed over three harvest years to determine the condensed tannins contents (CT, %(w/w)) in sainfoin powders. The three data sets corresponding to the three harvest years were used as calibration and then validation sets, successively. Finally, a global model gathering all the three years data sets has been developed. The developed models predict CT in a range of 2.06 to 11.28 %(w/w). The accuracy of the models depended on the range of CT-values of the calibration and validation sets. Finally, it was possible to predict the CT with a SEP-value lower than 0.5% (w/w) and R2-value higher than 0.9. In the present study, some of the PLS-parameters such as bias, slope and SEP have been statistically evaluated using the international standard ISO 12099:2017. The final global model was very promising since bias was not significantly different from 0, the slope was not significantly different from 1, and obtained SEP was 0.49% (w/w) while the calculated SEP-limit was 0.47% (w/w). The presently developed model was robust over the three years and the global model presented very interesting values. Such approach would be very useful to develop a new quantitative, rapid and low cost method to assess the CT of sainfoin powders. This method will allow us to free ourselves from the traditional chemical method that consumes time, money and chemicals.
红外光谱法测定红枫粉中缩合单宁的含量
基于FT-NIR光谱和pls回归的模型在三个收获年的时间里被开发出来,以确定红素粉末中浓缩单宁含量(CT, %(w/w))。3个收获年份对应的3个数据集依次作为标定集和验证集。最后,建立了一个收集所有三年数据集的全球模型。所建立的模型对CT的预测范围为2.06 ~ 11.28% (w/w)。模型的准确性取决于校准集和验证集的ct值的范围。最后,sep值小于0.5% (w/w), r2值大于0.9时,可以预测CT。本研究采用国际标准ISO 12099:2017对pls参数的偏置、斜率和SEP进行了统计评估。最终的全局模型非常有希望,因为偏差与0没有显著差异,斜率与1没有显著差异,获得的SEP为0.49% (w/w),而计算的SEP极限为0.47% (w/w)。目前开发的模型在三年内是稳健的,全球模型呈现出非常有趣的值。该方法将有助于开发一种新的定量、快速、低成本的方法来评估红素粉末的CT。这种方法将使我们从传统的化学方法中解脱出来,传统的化学方法耗费时间、金钱和化学品。
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