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Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus pratensis by Near-Infrared Spectroscopy and Chemometrics

Near infrared spectroscopy (NIRS) is an accurate, fast and nondestructive technique whose use in predicting forage quality has become increasingly relevant in recent decades. Epichloë-infected grass varieties are commonly used in areas with high pest pressure due to their better performances compare...

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Autores principales: Cagnano, Giovanni, Vázquez-de-Aldana, Beatriz R., Asp, Torben, Roulund, Niels, Jensen, Christian S., Soto-Barajas, Milton Carlos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7285352/
https://www.ncbi.nlm.nih.gov/pubmed/32455703
http://dx.doi.org/10.3390/microorganisms8050776
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author Cagnano, Giovanni
Vázquez-de-Aldana, Beatriz R.
Asp, Torben
Roulund, Niels
Jensen, Christian S.
Soto-Barajas, Milton Carlos
author_facet Cagnano, Giovanni
Vázquez-de-Aldana, Beatriz R.
Asp, Torben
Roulund, Niels
Jensen, Christian S.
Soto-Barajas, Milton Carlos
author_sort Cagnano, Giovanni
collection PubMed
description Near infrared spectroscopy (NIRS) is an accurate, fast and nondestructive technique whose use in predicting forage quality has become increasingly relevant in recent decades. Epichloë-infected grass varieties are commonly used in areas with high pest pressure due to their better performances compared to endophyte-free varieties. The insect resistance of Epichloë-infected grasses has been associated with four main groups of endophyte secondary metabolites: ergot alkaloids, indole-diterpenes, lolines and peramine. Concentrations of these alkaloids are usually measured with high performance liquid chromatography or gas chromatography analysis, which are accurate methods but relatively expensive and laborious. In this paper, we developed a rapid method based on NIRS to detect and quantify loline alkaloids in wild accessions of Schedonorus pratensis infected with the fungal endophyte Epichloë uncinata. The quantitative NIR equations obtained by modified partial least squares algorithm had coefficients of correlation of 0.90, 0.78, 0.85, 0.90 for N-acetylloline, N-acetylnorloline and N-formylloline and the sum of the three, respectively. The acquired NIR spectra were also used for developing an equation to predict in planta fungal biomass with a coefficient of correlation of 0.75. These results showed that the use of NIRS and chemometrics allows the quantification of loline alkaloids and mycelial biomass in a heterogeneous set of endophyte-infected meadow fescue samples.
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spelling pubmed-72853522020-06-17 Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus pratensis by Near-Infrared Spectroscopy and Chemometrics Cagnano, Giovanni Vázquez-de-Aldana, Beatriz R. Asp, Torben Roulund, Niels Jensen, Christian S. Soto-Barajas, Milton Carlos Microorganisms Article Near infrared spectroscopy (NIRS) is an accurate, fast and nondestructive technique whose use in predicting forage quality has become increasingly relevant in recent decades. Epichloë-infected grass varieties are commonly used in areas with high pest pressure due to their better performances compared to endophyte-free varieties. The insect resistance of Epichloë-infected grasses has been associated with four main groups of endophyte secondary metabolites: ergot alkaloids, indole-diterpenes, lolines and peramine. Concentrations of these alkaloids are usually measured with high performance liquid chromatography or gas chromatography analysis, which are accurate methods but relatively expensive and laborious. In this paper, we developed a rapid method based on NIRS to detect and quantify loline alkaloids in wild accessions of Schedonorus pratensis infected with the fungal endophyte Epichloë uncinata. The quantitative NIR equations obtained by modified partial least squares algorithm had coefficients of correlation of 0.90, 0.78, 0.85, 0.90 for N-acetylloline, N-acetylnorloline and N-formylloline and the sum of the three, respectively. The acquired NIR spectra were also used for developing an equation to predict in planta fungal biomass with a coefficient of correlation of 0.75. These results showed that the use of NIRS and chemometrics allows the quantification of loline alkaloids and mycelial biomass in a heterogeneous set of endophyte-infected meadow fescue samples. MDPI 2020-05-21 /pmc/articles/PMC7285352/ /pubmed/32455703 http://dx.doi.org/10.3390/microorganisms8050776 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cagnano, Giovanni
Vázquez-de-Aldana, Beatriz R.
Asp, Torben
Roulund, Niels
Jensen, Christian S.
Soto-Barajas, Milton Carlos
Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus pratensis by Near-Infrared Spectroscopy and Chemometrics
title Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus pratensis by Near-Infrared Spectroscopy and Chemometrics
title_full Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus pratensis by Near-Infrared Spectroscopy and Chemometrics
title_fullStr Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus pratensis by Near-Infrared Spectroscopy and Chemometrics
title_full_unstemmed Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus pratensis by Near-Infrared Spectroscopy and Chemometrics
title_short Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus pratensis by Near-Infrared Spectroscopy and Chemometrics
title_sort determination of loline alkaloids and mycelial biomass in endophyte-infected schedonorus pratensis by near-infrared spectroscopy and chemometrics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7285352/
https://www.ncbi.nlm.nih.gov/pubmed/32455703
http://dx.doi.org/10.3390/microorganisms8050776
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