Plant hormones are important in the control of physiological and developmental processes including seed germination, senescence, flowering, stomatal aperture, and ultimately the overall growth and yield of plants. Many currently available methods to quantify such growth regulators quickly and accurately require extensive sample purification using complex analytic techniques. Herein we used ultra-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) to create and validate the prediction of hormone concentrations made using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectral profiles of both freeze-dried ground leaf tissue and extracted xylem sap of Japanese knotweed (Reynoutria japonica) plants grown under different environmental conditions. In addition to these predictions made with partial least squares regression, further analysis of spectral data was performed using chemometric techniques, including principal component analysis, linear discriminant analysis, and support vector machines (SVM). Plants grown in different environments had sufficiently different biochemical profiles, including plant hormonal compounds, to allow successful differentiation by ATR-FTIR spectroscopy coupled with SVM. ATR-FTIR spectral biomarkers highlighted a range of biomolecules responsible for the differing spectral signatures between growth environments, such as triacylglycerol, proteins and amino acids, tannins, pectin, polysaccharides such as starch and cellulose, DNA and RNA. Using partial least squares regression, we show the potential for accurate prediction of plant hormone concentrations from ATR-FTIR spectral profiles, calibrated with hormonal data quantified by UHPLC-HRMS. The application of ATR-FTIR spectroscopy and chemometrics offers accurate prediction of hormone concentrations in plant samples, with advantages over existing approaches.

中文翻译：

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用于预测植物激素浓度的衰减全反射傅里叶变换红外光谱

植物激素对于控制生理和发育过程非常重要，包括种子发芽、衰老、开花、气孔孔径，以及最终植物的整体生长和产量。目前许多快速准确地量化此类生长调节剂的可用方法需要使用复杂的分析技术进行广泛的样品纯化。在此，我们使用超高效液相色谱-高分辨率质谱 (UHPLC-HRMS) 来创建并验证使用两种冻干地面的衰减全反射傅里叶变换红外 (ATR-FTIR) 光谱曲线对激素浓度的预测。在不同环境条件下生长的日本虎杖（ Reynoutria japonica ）植物的叶组织和提取的木质部汁液。除了使用偏最小二乘回归进行的这些预测之外，还使用化学计量技术对光谱数据进行进一步分析，包括主成分分析、线性判别分析和支持向量机 (SVM)。在不同环境中生长的植物具有足够不同的生化特征，包括植物激素化合物，从而可以通过 ATR-FTIR 光谱与 SVM 结合成功区分。 ATR-FTIR 光谱生物标志物强调了一系列导致生长环境之间不同光谱特征的生物分子，例如三酰甘油、蛋白质和氨基酸、单宁、果胶、淀粉和纤维素等多糖、DNA 和 RNA。使用偏最小二乘回归，我们展示了根据 ATR-FTIR 光谱曲线准确预测植物激素浓度的潜力，并使用 UHPLC-HRMS 量化的激素数据进行校准。 ATR-FTIR 光谱和化学计量学的应用可以准确预测植物样品中的激素浓度，与现有方法相比具有优势。