Near Infrared Reflectance Spectroscopy Analysis of Forage Quality in Four Legume Species¹

Abstract

Near infrared reflectance Spectroscopy (NIRS) technology needs verification as to its utility for forages that represent diverse species, environments, and managements. Our objectives were to determine whether single NIRS calibration equations could reliably assess components of the feeding quality of alfalfa (Medicago saliva L.) grown to a range of maturities in several environments and whether single equations could be developed to simultaneously analyze components of the quality of total forage and plant parts of alfalfa, birdsfoot trefoil (Lotus cornieulattis L.), red clover (Trifolium pratense L.), and white clover (Trifolium repens L.). In the first experiment, we assayed four forage quality components in 234 alfalfa samples from eight cutting schedules of two cultivars grown in two locations in each of 2 years. In Exp. II, we assayed five quality components in 167 samples of total forage and plant parts selected from seven harvests from two growth periods of two cultivars of each of four perennial legume species. Calibration equations for in vitro digestible dry matter (IVDDM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL) were obtained by multiple linear regression of known conventional laboratory assay values on NIR spectra from up to 204 samples using a scanning monochromator NIR spectre‐computer system. Equations were validated with up to 49 additional samples that had been selected from the original populations. From three to nine wavelengths were required to develop the best calibration equations for the various quality components. The squared coefficients of determination (R2) of these equations ranged from 0.93 to 0.99. These equations allowed NIRS analysis of quality values in verification samples within standard errors (dag/kg) of 1.56 to 2.06 for IVDDM, 0.42 to 1.0 for CP, 1.46 to 2.23 for NDF, 1.30 to 1.70 for ADF, and 0.63 for ADL. We concluded that our NIRS system can quickly evaluate the feeding quality of perennial legumes to a degree of accuracy similar to that of laborious conventional analyses and that several species can be evaluated simultaneously with single calibration equations nearly as well as can single species.

Densidade populacional de Pratylenchus spp. em pastagens de Brachiaria spp. e sua influência na disponibilidade e na qualidade da forragem

“…Também, avaliou-se o valor nutritivo da forragem, quantificando-se os teores de proteína bruta (PB), fibra em detergente neutro (FB), lignina em ácido sulfúrico (LigS), celulose (Cel), nitrogênio total (Ntotal) e digestibilidade in vitro da matéria orgânica (DIVMO), utilizando-se a espectroscopia de reflectância do infravermelho próximo, utilizando-se o aparelho FOSS® NIRSystems mod. 5000, conforme Marten et al (1985).…”

Satellite-based monitoring of tropical seagrass vegetation: current techniques and future developments

“…Hence, for this kind of application, hyperspectral (HS) remote sensing is best suited. Over the past decades, HS remote sensing (imaging spectroscopy) has developed from a laboratory-based technique, used to measure the chemical composition of standardized, dried and ground samples (Marten et al, 1985), to an experimental technique used to measure vegetation characteristics from airplanes and satellites (Secker et al, 2001;Williams & Hunt, 2002;Underwood et al, 2003;Schmidtlein & Sassin, 2004).…”

Genetic Modification of Herbaceous Plants for Feed and Fuel

“…The selection of the plants to be mated is the critical component of the conventional breeding process because breeders evaluate phenotypes in order to select superior genotypes. The other component, hybridization or mating, can usually be done in a routine manner, although for some species the procedures are tedious and require a high degree of skill (Fehr and Hadley, 1980;Martinez-Reyna and Vogel, 1998). Breeding systems have been developed and continue to be developed that can be used to improve virtually all forage species.…”

“…Rapid, reliable, and repeatible analytical technologies are needed that have a low per sample cost. Near infrared reflectance spectroscopy or NIRS Westerhouse, 1994, 1995;Marten et al, 1989) meets these criteria. This technology was developed to determine quality of agricultural products, including protein and oil content of grains and oilseeds, and was adapted to measure forage quality parameters.…”