衰减全反射傅立叶变换红外光谱法用于预测植物体内的激素浓度

IF 3.6 3区 化学 Q2 CHEMISTRY, ANALYTICAL
Analyst Pub Date : 2024-04-30 DOI:10.1039/D3AN01817B
Claire A. Holden, Martin R. McAinsh, Jane E. Taylor, Paul Beckett, Alfonso Albacete, Cristina Martínez-Andújar, Camilo L. M. Morais and Francis L. Martin
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引用次数: 0

摘要

植物激素在控制种子萌发、衰老、开花、气孔开度等生理和发育过程中起着重要作用,并最终影响植物的整体生长和产量。目前许多快速准确量化此类生长调节剂的方法都需要使用复杂的分析技术进行大量的样品纯化。在此,我们使用超高效液相色谱-高分辨质谱法(UHPLC-HRMS),利用日本结缕草(Reynoutria japonica)植物在不同环境条件下生长时的冻干碎叶组织和提取的木质部汁液的衰减全反射傅立叶变换红外光谱图谱,创建并验证了激素浓度预测。除了利用偏最小二乘法回归进行预测外,还利用化学计量学技术(包括主成分分析、线性判别分析和支持向量机(SVM))对光谱数据进行了进一步分析。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,因此可以通过 ATR-FTIR 光谱和 SVM 成功地进行区分。ATR-FTIR 光谱生物标志物突出显示了导致不同生长环境光谱特征不同的一系列生物分子,如三酰甘油、蛋白质和氨基酸、单宁、果胶、多糖(如淀粉和纤维素)、DNA 和 RNA。利用偏最小二乘法回归,我们展示了从 ATR-FTIR 光谱图谱准确预测植物激素浓度的潜力,并通过超高效液相色谱-质谱联用仪(UHPLC-HRMS)对激素数据进行定量校准。与现有方法相比,ATR-傅立叶变换红外光谱和化学计量学的应用可准确预测植物样本中的激素浓度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Attenuated total reflection Fourier-transform infrared spectroscopy for the prediction of hormone concentrations in plants†

Attenuated total reflection Fourier-transform infrared spectroscopy for the prediction of hormone concentrations in plants†

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.

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来源期刊
Analyst
Analyst 化学-分析化学
CiteScore
7.80
自引率
4.80%
发文量
636
审稿时长
1.9 months
期刊介绍: The home of premier fundamental discoveries, inventions and applications in the analytical and bioanalytical sciences
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