BACKGROUND: Near-infrared reflectance spectroscopy (NIRS) has been widely used in forage quality control because it is faster, cleaner and less expensive than conventional chemical procedures. In Lolium perenne (perennial ryegrass), one of the most important forage grasses, the infection by asymptomatic Epichloë fungal endophytes alters the plant nutritional quality due to the production of alkaloids. In this research, we developed a rapid method based on NIRS to detect and quantify endophyte alkaloids (peramine, lolitrem B and ergovaline) using a heterogeneous set of L. perenne plants obtained from wild grasslands and cultivars. RESULTS: NIR spectra from dried grass samples were recorded and classified according to the absence or presence of alkaloids, based on reference methods. The best discriminant equations for detection of alkaloids classified correctly 94.4%, 87.5% and 92.9% of plants containing peramine, lolitrem B and ergovaline, respectively. The quantitative NIR equations obtained by modified partial least squares (MPLS) algorithm had coefficients of correlation of 0.93, 0.41, and 0.76 for peramine, lolitrem B and ergovaline respectively. CONCLUSION: NIRS is a suitable tool for qualitative analysis of endophyte alkaloids in grasses and for the accurate quantification of peramine and ergovaline.
BACKGROUND: Near-infrared reflectance spectroscopy (NIRS) has been widely used in forage quality control because it is faster, cleaner and less expensive than conventional chemical procedures. In Lolium perenne (perennial ryegrass), one of the most important forage grasses, the infection by asymptomatic Epichloë fungal endophytes alters the plant nutritional quality due to the production of alkaloids. In this research, we developed a rapid method based on NIRS to detect and quantify endophyte alkaloids (peramine, lolitrem B and ergovaline) using a heterogeneous set of L. perenne plants obtained from wild grasslands and cultivars. RESULTS: NIR spectra from dried grass samples were recorded and classified according to the absence or presence of alkaloids, based on reference methods. The best discriminant equations for detection of alkaloids classified correctly 94.4%, 87.5% and 92.9% of plants containing peramine, lolitrem B and ergovaline, respectively. The quantitative NIR equations obtained by modified partial least squares (MPLS) algorithm had coefficients of correlation of 0.93, 0.41, and 0.76 for peramine, lolitrem B and ergovaline respectively. CONCLUSION: NIRS is a suitable tool for qualitative analysis of endophyte alkaloids in grasses and for the accurate quantification of peramine and ergovaline.
Authors: Giovanni Cagnano; Beatriz R Vázquez-de-Aldana; Torben Asp; Niels Roulund; Christian S Jensen; Milton Carlos Soto-Barajas Journal: Microorganisms Date: 2020-05-21