Comparisons of commercially available NIRS-based analyte predictions of haylage quality for equid nutrition

A - Papers appearing in refereed journals

Le Cocq, K., Harris, P., Bell, N., Burden, F. A., Lee, M. R. F. and Davies, D. R. 2022. Comparisons of commercially available NIRS-based analyte predictions of haylage quality for equid nutrition. Animal Feed Science and Technology. 283, p. 115158. https://doi.org/10.1016/j.anifeedsci.2021.115158

AuthorsLe Cocq, K., Harris, P., Bell, N., Burden, F. A., Lee, M. R. F. and Davies, D. R.
Abstract

Maintaining animal health and performance relies on the availability of an appropriate diet. For herbivores, accurate assessment of forage nutrient quality is critical for appropriate diet formulation and rationing, including potential supplementation. Near-Infrared Reflectance Spectroscopy (NIRS) is a rapid method that is used in place of traditional chemical methodologies (wet chemistry) to predict analyte contents in forage samples. The method relies on scanning a sample with near-infra-red light and predicting the analyte content by comparing the reflected spectra to a model which has been developed with samples of known analyte content measured by wet chemistry. The purpose of this study was to examine the accuracy of four NIRS-based methods on haylage from seven farm holdings compared with wet chemistry (the control). We analysed 64 samples for a range of analytes (dry matter (DM), pH, ash, acid detergent fibre (ADF), neutral detergent fibre (NDF), crude protein (cp) and water-soluble carbohydrate (WSC) commonly assessed for haylage quality in equid nutrition). We compared results obtained by wet chemistry to corresponding NIRS-based predictions from four commercially available NIRS services. The results revealed large discrepancies amongst all five methods. The extent of these discrepancies from the wet chemistry also varied by analyte where for example, predictions for DM were more reliable than those for WSC and results demonstrated that predictions obtained by NIRS could result in feeding forage outside of target nutritional values.

KeywordsForage; Diet; Donkey; Equine; Analysis; Calibration; Ration; Model
Year of Publication2022
JournalAnimal Feed Science and Technology
Journal citation283, p. 115158
Digital Object Identifier (DOI)https://doi.org/10.1016/j.anifeedsci.2021.115158
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeS2N - Soil to Nutrition - Work package 2 (WP2) - Adaptive management systems for improved efficiency and nutritional quality
Output statusPublished
Publication dates
Online27 Nov 2021
Publication process dates
Accepted15 Nov 2021
PublisherElsevier Science Bv
ISSN0377-8401

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