Characterization and quantification of secondary metabolite profiles in leaves of red and white clover species by NIR and ATR-IR spectroscopy

Krähmer, Andrea; Gudi, Gennadi; Weiher, N.; Gierus, M.; Schütze, Wolfgang; Schulz, Hartwig

doi:10.1016/j.vibspec.2013.05.012

Cited by 36 publications

(39 citation statements)

References 27 publications

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“…White clover is one of the most important perennial forage legumes worldwide (Annicchiarico et al, 2015;Barrett et al, 2015). Thus, several NIR spectroscopy studies has been performed to predict forage quality (Berardo, 1997;Lister and Dhanoa, 1998;Alomar et al, 2009;Krahmer et al, 2013). However, all these works have used samples of aerial biomass (leaves + petiole).…”

Section: Discussionmentioning

confidence: 99%

“…A high throughput methodology to determiner WSC is required to a successful implementation of this trait as selection criterion in a plant breeding program. Near-infrared spectroscopy is considered a robust, reliable, and highthroughput methodology to estimate chemical composition of forage species (Alomar et al, 2009;Nie et al, 2009;Krahmer et al, 2013;Piaskowski et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…The NIR spectroscopy has been successfully used to estimate forage-quality traits in diverse species including white clover (Berardo, 1997;Lister and Dhanoa, 1998;Alomar et al, 2009;Krahmer et al, 2013). There are several works where NIR-spectroscopy has already been used to predict WSC (Nie et al, 2009;Widdup et al, 2010;Lobos et al, 2013;Piaskowski et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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NIR-Prediction of water-soluble carbohydrate in white clover and its genetic relationship with cold tolerance

Inostroza

Lobos

Acuña

et al. 2017

Chilean J. Agric. Res.

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In temperate climates, cold stress constrains productivity of white clover (Trifolium repens L.), the most important perennial forage legume in intensive grazing systems for ruminants. Metabolism of water sugar carbohydrate (WSC) has been proposed as an important trait conferring cold tolerance to white clover. Conventional methodologies for WSC determination are considered high-cost and timeconsuming. Near-infrared (NIR) spectroscopy is a robust, reliable, and high-throughput methodology to estimate chemical composition of forage species. The objectives of this work were to determine the accuracy of NIR spectroscopy for predicting WSC in stolon samples of white clover, and to evaluate the genetic relationship between WSC and cold tolerance. A white clover association mapping (WCAM) population was stablished in three location that represent a winter low temperature gradient associated with altitude. Dry matter production and some morphological traits were evaluated during three growing seasons. Samples for WSC determination were collected three time during a winter period. Samples were scanned with a NIR system, and a prediction model for WSC was fitted using partial least squares (PLS) regression. The adjusted prediction model achieved suitable predictive ability (R 2 > 0.85). The WSC per se did not show significant genetic relationship with morphological and agronomically important traits. However, the WSC degradation rate (WSCdr) across the winter period showed significant genetic correlation with DM production during spring (r g = 0.64), which is the result of genetic/ physiological mechanism expressed during the cold period. The NIR spectroscopy is a reliable and high-throughput methodology to predict WSC in stolon samples of white clover. The metabolism of WSC, evaluated as WSCdr, is involved in the cold tolerance of the WCAM population. The methodology implemented in this work is suitable to be applied in a plant breeding program routine.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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NIR-Prediction of water-soluble carbohydrate in white clover and its genetic relationship with cold tolerance

Inostroza

Lobos

Acuña

et al. 2017

Chilean J. Agric. Res.

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“…In contrast, in a study on two clover species, Krähmer et al . () presented a calibration model for the content of phenolic acids with much lower accuracy ( R ² = 0.64 and RPD = 1.72).…”

Section: Discussionmentioning

confidence: 99%

Trade‐offs between physical and chemical carbon‐based leaf defence: of intraspecific variation and trait evolution

et al. 2015

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Summary1. Despite recent advances in studies on trade-offs between plant defence traits, little is known about whether trade-offs reflect (i) evolutionary constraints at the species level or (ii) allocation constraints at the individual level. Here, we asked to which degree physical and chemical carbon-based leaf defence traits covary within and across species. 2. We assessed leaf toughness, leaf total phenolic and tannin concentrations for 51 subtropical tree species. Species trait means, sample-specific values and phylogenetically independent contrasts were used in regression analyses. Phylogenetic signals and trait evolution were assessed along the phylogeny. 3. Analyses of species-level trait means revealed significant negative trait covariations between physical and chemical defence traits in analyses over all species. These covariations were inconsistent at the within-species level. All three defence aspects showed strong phylogenetic signals, but differed in the degree of conservatism along the phylogeny. Inclusion of intraspecific trait variability significantly decreased the strength of these covariations. Strong negative covariations were detected between physical and chemical defence traits when phylogenetic non-independence was accounted for. 4. Synthesis. We addressed two sources of variation (allocation and evolution) independently from each other in the context of trait interrelationships. The observed negative covariations hint at the existence of a trade-off between physical and chemical defence traits. The finding that intraspecific trait variation contributed less to this relationship suggests that the trade-off is dominated by evolutionary constraints rather than by carbon allocation constraints.

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“…Therefore, it may provide a more precise determination of specific chemical components than NIR. It has been demonstrated that NIR has advantages for determination of sum parameters, while FT‐IR is more suitable for the quantification of individual compounds in several studies regarding the comparison of FT‐IR and NIR for the determination of various parameters or chemical components (Schonbichler and others ; Krähmer and others ; Schönbichler and others ). Thus, for the determination of specific amino acids, FT‐IR may be a better option.…”

Section: Introductionmentioning

confidence: 99%

Use of Attenuated Total Reflectance Mid‐Infrared Spectroscopy for Rapid Prediction of Amino Acids in Chinese Rice Wine

Long

et al. 2015

Journal of Food Science

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The high content of amino acids of Chinese rice wine (CRW), especially essential amino acids makes it a food increasingly demanded by consumers. Rapid detection technique of amino acid content, which is an important quality and function index of CRW, is highly desirable for consumers, producers as well as administrative authorities. In this study, the potential of Fourier transform infrared spectroscopy (FT-IR) as a novel and rapid analytical technique to determine 17 free amino acids in CRW were investigated. Genetic algorithms (GA) and synergy interval partial least squares (SiPLS) were used to select the most efficient spectral variables to improve the prediction precision of the classic partial least squares (PLS) model constructed on the full-spectrum. The results demonstrated that compared with the PLS model using all wavelengths of FT-IR spectra, the prediction precision of model based on the spectral variables selected by GA and SiPLS was significantly improved, especially for arginine and proline. After systemic comparison and discussion, it was found that GA-SiPLS model achieved the best performance, with the correlation coefficient in calibration (R(2) (cal)) higher than 0.80 and the residual predictive deviation higher than 2.00 for all of the free amino acids analyzed in this study. The overall results confirmed that FT-IR combined with efficient variable selection algorithms is a method that may be useful to replace the traditional methods for routine analysis of free amino acids in CRW.

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Characterization and quantification of secondary metabolite profiles in leaves of red and white clover species by NIR and ATR-IR spectroscopy

Cited by 36 publications

References 27 publications

NIR-Prediction of water-soluble carbohydrate in white clover and its genetic relationship with cold tolerance

NIR-Prediction of water-soluble carbohydrate in white clover and its genetic relationship with cold tolerance

Trade‐offs between physical and chemical carbon‐based leaf defence: of intraspecific variation and trait evolution

Use of Attenuated Total Reflectance Mid‐Infrared Spectroscopy for Rapid Prediction of Amino Acids in Chinese Rice Wine

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