Prediction of composition and ruminal degradability characteristics of barley straw by near infrared reflectance spectroscopy

Abstract

P. 1999. Prediction of composition and ruminal degradability characteristics of barley straw by near infrared reflectance spectroscopy. Can. J. Anim. Sci. 79: 519-523. The usefulness of near infrared reflectance spectroscopy (NIRS) for the prediction of the nutritive value of straw was examined with 195 samples of barley straw. Excluding lignin, NIRS technique explained 84 to 94% of the variation in chemical components in the validation set. From 69 to 84% of the variation in ruminal degradability characteristics, excluding rate of degradation, was explained by NIRS. With the exception of neutral detergent fiber, accuracies of prediction were not improved when NIRS calibrations were based upon calibration sets containing straw only in contrast with when barley hay and barley silage were included with straw in the calibration set. We conclude that near infrared reflectance spectroscopy is a useful method for predicting chemical composition of straw and estimating its ruminal degradability characteristics.Key words: Barley, straw, near infrared reflectance spectroscopy, in situ, degradability Mathison, G. W., Hsu, H., Soofi-Siawash, R., Recinos-Diaz, G., Okine, E. K., Helm, J. et Juskiw, P. 1999. Prédiction de la composition et de la dégradabilité ruminale de la paille d'orge par spectrométrie de réflectance dans le proche infrarouge. Can. J. Anim. Sci. 79: 519-523. Nous avons observé sur 195 échantillons de paille l'utilité de la spectrométrie de réflectance dans le proche infrarouge (SPIR) pour la prédiction de la valeur nutritive de la paille d'orge. Sauf pour la lignine, la technique SPIR rendait compte de 94 % de la variation affectant les composants chimiques des échantillons de validation. En outre, elle expliquait de 69 à 84 % de la variation des paramètres de dégradabilité ruminale,sauf le taux de dégradation. À l'exception de la teneur en FDN, le degré de précision des prédictions n'était pas amélioré lorsque les calibrations SPIR étaient basées sur le jeu d'échantillonsde calibration ne contenant que de la paille seule plutôt qu'un mélange de paille et de foin et d'ensilage d'orge. La spectrométrie de réflectance dans le proche infrarouge se présente donc comme une méthode intéressante pour prédire la composition chimique de la paille et pour estimer ses paramètres de dégradabilité dans le rumen. Mots clés:Orge, paille, SPIR, spectrométrie de réflectance dans le proche infrarouge, in situ, dégradabilitéThe majority of wintering beef cow diets in Western Canada contain straw as a result of direct inclusion in rations or because cows obtain it by eating bedding. Methods for measurement of nutritive value of straw are important since it varies in its nutritive value (Mathison et al. 1999). The in situ procedure has been widely used to estimate the nutritive value of feeds for ruminant animals. von Keyserlingk and Mathison (1989) reported that up to 86 and 92% of the variation in voluntary dry matter (DM) intake and digestibility, respectively, could be explained by differences in in situ degradation chara...

Prediction of rumen degradability parameters of a wide range of forages and non-forages by NIRS

“…For FF, the inclusion of silages provided another factor. Silages provided more accurate predictions of DM and CP degradability parameters (de La Roza et al, 1998) than other forage sources (Todorov et al, 1994;Mathison et al, 1999). However, when silages were included to forage sources predictions were improved (Hsu et al, 1998).…”

Comparative Efficiency of Conventional and NIR Based Technique for Proximate Composition of Pigeon Pea, Soybean and Rice Cultivars

“…NIRS is an accepted method to predict forage fiber traits of barley straw (Mathison et al, 1999), rice (Kong et al, 2005;Jin, 2007), green cereal crops (Bruno-Soares et al, 1998), leguminous shrubs (Garcia et al, 2004), and oat hulls (Redaelli, 2007).…”

Options for improving the yield and nutritive value of maize and grain legume residues for ruminants in East African farming systems

“…The poor prediction of the total N concentration in soybean in the present study may have been associated with the small population size (n=25) and that this material tends to be spectrally different to the other forages and crop residues. Except for total N prediction of soybean, the RPDv values obtained in the present study were higher than the values obtained in whole plant maize (Campo et al, 2013) and barley straw (Mathison et al, 1999) and comparable with the RPDv values in temperate forages (Norman et al, 2015). In general, the RPDv values obtained in the validation data set of the present study for CR quality attributes measured indicates that the better NIRS predictions of the parameters with good accuracy and further confirmed the improved predictive ability and robustness of the of chemometric models developed for DMD, Total N, NDF and ADF based on the NA dataset.…”

“…Several authors are however of the opinion that RPDv values higher than 2.5 in any equation are required for an acceptable predictability (Edney et al, 1994;Mathison et al, 1999). On the other hand, Esbensen et al (2014) has been critical of the ubiquitous use of the RPDv statistic as a sole index of the quality of any NIR calibration without further criteria.…”