Journal of Animal Production, Print ISSN: 2008-6776., Online ISSN: 2382-994X

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Comparison of NIR and wet chemistry methods for evaluation of chemical composition and nutrient digestibility in forage legumes

Document Type : Research Paper

Authors

1 Department of Animal and Poultry Sciences, Aburayhan Faculty of Agricultural Technology, University of Tehran, Tehran, Iran. E-mail: j_khani@ut.ac.ir

2 Corresponding Author, Department of Animal and Poultry Science, Aburayhan Faculty of Agricultural Technology, University of Tehran, Tehran, Iran. E-mail: a.alamouti@ut.ac.ir

3 Department of Animal Science, Faculty of Agriculture, Malayer University, Malayer, Iran. E-mail: myari@malayeru.ac.ir

10.22059/jap.2026.398903.623859

Abstract

Objective: Understanding chemical composition and nutritional quality of feedstuffs, especially forage crops, are important components of ration formulation, livestock performance, and production costs. Near-infrared reflectance (NIR) spectroscopy is becoming popular as a rapid, non-destructive, and cost-effective alternative to traditional wet chemistry methods for determining chemical composition and nutritional quality of feedstuffs. The objective of this study was to compare the accuracy of NIR with standard laboratory procedures in determining chemical constituents, protein and carbohydrate fractions according to the Cornell Net Carbohydrate and Protein System (CNCPS), and nutritional attributes of four legume forages.
Method: Organic matter (OM), ash, acid detergent lignin (ADL), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), starch, and CNCPS-based fractionation of protein and carbohydrates, and nutritional attributes such as potential dry matter intake (DMI), total digestible nutrients (TDN), digestible energy (DE), metabolizable energy (ME), and quality index (QI) were measured in forage samples from four species including two cultivars of common vetch (Vicia sativa) and hairy vetch (Vicia villosa), one cultivar of forage pea (Pisum arvense), and second-year alfalfa (Medicago sativa, used as the control crop). All analyses were conducted in parallel using NIR and the reference wet chemistry methods and statistical agreement and precision between the two methods were assessed using mean bias, root mean square error (RMSE), concordance correlation coefficient (CCC), and Bland–Altman limits of agreement (LOA).
Results: The NIR results were highly accurate and highly correlated (CCC> 0.85, P> 0.05) with wet chemistry methods for key components (CP, OM, starch, total carbohydrates, and fraction B1 (B1)), but acceptable precision was observed for predicting energy-related parameters (TDN, DE, and ME) which are critical for ration formulation. However, the accuracy and concordance declined, and statistically significant differences were observed for structural constituents (ADL, NDF,  protein fractions (ADIP, NADIP) and carbohydrates (B2, B3, and C). This indicates that NIR has limited spectral sensitivity when evaluating slowly degradable or indigestible fractions of carbohydrate and protein, which are the parameters of dynamic nutritional models such as CNCPS.
Conclusions: Owing to special advantages, particularly speed, ease of operation, and applicability to field analyses, NIR can replace routine proximate analysis in feed laboratories; but conventional chemical methods provide more benefits for evaluation of CNCPS model components, especially those that resist digestion. The NIR integrated with classical approaches may represent a rational cost-effective strategy for extensive feed analyses.

Keywords

References
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Journal of Animal Production, Print ISSN: 2008-6776., Online ISSN: 2382-994X
Volume 28, Issue 1
March 2026
Pages 15-26
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