Environmental stress evaluation of Coffea arabica L. leaves from spectrophotometric fingerprints by PCA and OSC–PLS–DA

Scheel, Guilherme Luiz; Pauli, Elis Daiane; Rakocevic, Miroslava; Bruns, Roy E.; Scarmínio, Ieda Spacino

doi:10.1016/j.arabjc.2016.05.014

Cited by 14 publications

(4 citation statements)

References 44 publications

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“…Lin et al ( 2014 ) also described enhanced accumulation of secondary metabolites (flavones and flavonols) through chemical fingerprint analysis of Phyla nodiflora (L.) methanol extracts. Scheel et al ( 2019 ) also reported that sunlight exposure induced the accumulation of pheophytin in Coffea arabica (L.) leaves. Delaroza et al ( 2014 ) observed the presence of caffeine, chlorogenic acid, and theobromine in sunlight-exposed leaves of C. arabica (L.).…”

Section: Resultsmentioning

confidence: 95%

Spectral fingerprinting revealed modulation of plant secondary metabolites in providing abiotic stress tolerance to invasive alien plants Lantana camara (L.), Parthenium hysterophorous (L.), Ricinus communis (L.), and Ageratum conyzoides (L.) (plant metabolites in stress tolerance to invasive plants)

Sharma¹,

Kaur²,

Chand³

2021

bta

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Section: Resultsmentioning

confidence: 95%

Spectral fingerprinting revealed modulation of plant secondary metabolites in providing abiotic stress tolerance to invasive alien plants Lantana camara (L.), Parthenium hysterophorous (L.), Ricinus communis (L.), and Ageratum conyzoides (L.) (plant metabolites in stress tolerance to invasive plants)

Sharma¹,

Kaur²,

Chand³

2021

bta

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“…Wold et al proposed the orthogonal signal correction (OSC) in 1998, 19 which is a data preprocessing method that can eliminate the signals orthogonal to the dependent variables in the independent variables and filter out the noise in the original data. This method has been widely used in the field of chemometrics 20–22 . Li et al introduced OSC to preprocess the original independent variables, remove the signals unrelated to the dependent variables, and then establish the PLS monitoring model for improving the interpretability of the dam monitoring model 23 .…”

Section: Introductionmentioning

confidence: 99%

“…This method has been widely used in the field of chemometrics. [20][21][22] Li et al introduced OSC to preprocess the original independent variables, remove the signals unrelated to the dependent variables, and then establish the PLS monitoring model for improving the interpretability of the dam monitoring model. 23 However, the OSC cannot remove the influence of information overlap among independent variables to achieve effective filtering.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis method for the importance of stress influencing factors of a high arch dam during the operation period using SPA–OSC–PLS

Han

Yao

et al. 2022

Structural Contr & Hlth

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Stress analysis is an important part of the health monitoring and evaluation of a high arch dam. At present, a reasonable quantitative analysis method for the importance of stress influencing factors of a high arch dam during the operation period remains lacking. According to measured data of strain gauge groups, a quantitative analysis method is proposed integrating succession projection algorithm (SPA), orthogonal signal correction (OSC), and partial least squares (PLS). First, based on the stress calculation of the strain gauge group of a concrete dam, the statistical model of high arch dam stress is established.Second, independent variables are preprocessed using SPA and OSC to screen out effective influencing factors without noise signals. Finally, the principal component with the strongest explanation for the dependent variable is extracted using PLS, and the importance of stress influencing factors of a high arch dam during the operation period is quantitatively separated. Results show that the SPA-OSC-PLS method can effectively eliminate the effects of multiple correlations, information overlap, and noise among influencing factors. In addition, the predictive ability and interpretability of the SPA-OSC-PLS method are superior to the PLS and SPA-PLS methods, which can reasonably obtain the importance of stress influencing factors of a high arch dam. The proposed method can accurately reveal the change law and action mechanism of the stress of a high arch dam during the operation period.

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“…Moreover, the obtained data were processed using SIEVE 2.0, including denoising, baseline correction, overlapping‐peak resolution, and peak alignment, and then the m/z , the retention time, and the peak intensity of samples from 15 regions were obtained. Hierarchical clustering analysis (HCA) was used to compare the compositions and contents of 92 chemical components in the samples, while principal component analysis (PCA) was used to analyze the diversity of the samples by region. This quantitative information was propitious for quality evaluation by distinguishing the diversity of the composition in Valeriana jatamansi Jones from 15 regions.…”

Section: Introductionmentioning

confidence: 99%

Flexible and powerful strategy for qualitative and quantitative analysis of valepotriates in Valeriana jatamansi Jones using high‐performance liquid chromatography with linear ion trap Orbitrap mass spectrometry

Wang

Zheng

Deng

et al. 2017

J of Separation Science

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Valeriana jatamansi Jones is an important medicinal plant and its quality is closely related to its region of origin. In the current study, we utilized a flexible and powerful strategy for comprehensive evaluation of the quality diversity for 15 regions in China. The method was based on a hybrid linear ion trap-Orbitrap mass spectrometry platform. For structure characterization, fragmentation patterns were detected by analyzing a series of standard compounds using data dependent multistage mass spectrometry acquisition. A fragment ion database for valepotriates was established, and the acquired data were high throughput filtered by fragment ion search for compound identification. For quantitative purposes, we normalized the mass spectrometry data of 15 samples using SIEVE 2.0 and the differences in composition were analyzed using principal component analysis combined with hierarchical clustering analysis. The results identified a total of 92 compounds from Valeriana jatamansi Jones. Samples from Dali, Kunming, and Baoshan have better qualities and concentrations of the main active constituents. To verify our strategy, we compared the valtrate, acevaltrate, and baldrinal contents using high-performance liquid chromatography with diode array detector. We developed and validated a comprehensive qualitative and quantitative analytical method to achieve quality control of Valeriana jatamansi Jones.

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Environmental stress evaluation of Coffea arabica L. leaves from spectrophotometric fingerprints by PCA and OSC–PLS–DA

Cited by 14 publications

References 44 publications

Quantitative analysis method for the importance of stress influencing factors of a high arch dam during the operation period using SPA–OSC–PLS

Flexible and powerful strategy for qualitative and quantitative analysis of valepotriates in Valeriana jatamansi Jones using high‐performance liquid chromatography with linear ion trap Orbitrap mass spectrometry

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