Can ruminant metabolizable energy of barley, chickpea and lentil straw be predicted using chemical composition?

Alkhtib, A. ORCID: 0000-0002-3381-0304, Burton, E. ORCID: 0000-0003-2784-6922, Rischkowsky, B. and Wamatu, J., 2019. Can ruminant metabolizable energy of barley, chickpea and lentil straw be predicted using chemical composition? Journal of Experimental Biology and Agricultural Sciences, 7 (1), pp. 74-85. ISSN 2320-8694

[img]
Preview
Text
13333_Alkhtib.pdf - Published version

Download (958kB) | Preview

Abstract

This study attempted to generate simple and robust models to predict metabolizable energy (ME) content of barley, chickpea and lentil straw using chemical composition. Crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL) and ME of 1933, 487 and 489 straw samples of barley, chickpea and lentil respectively were determined using near infrared reflectance spectroscopy. The samples belonged to 1933 genotypes of barley, 79 genotypes of chickpea and 66 genotypes of lentil. Barley samples were collected from experimental locations of International Center for Agricultural Research in the Dry Areas, Morocco. Chickpea and lentil samples were collected from Ethiopian Institute of agricultural Research experimental locations. Data of each crop was randomly divided into two sets, a training set (75% of the data) and a deployment set (25% of the data). Crude protein, NDF, ADF and ADL were regressed on ME and Box-cox transformed ME of the training sets to generate prediction models. Coefficients of these models were used to calculate residuals and prediction error (PE) in both training and deployment sets. Criteria used in the screening algorithm were low PE (95th percentile of PE≤4) and homogenous residuals in both training and deployment sets. Barley and chickpea models were unable to predict ME of deployment samples with a 95th percentile of PE less than 4. Heterogeneity of residuals of the deployment set was found in lentil model (positive residuals= 64% of overall residuals). Accordingly, chemical composition from NIR is a poor predictor for ME of straws of barley, chickpea and lentil to formulate rations for farm management and a direct measurement of ME of these straws is still required.

Item Type: Journal article
Publication Title: Journal of Experimental Biology and Agricultural Sciences
Creators: Alkhtib, A., Burton, E., Rischkowsky, B. and Wamatu, J.
Publisher: Journal of Experimental Biology and Agricultural Sciences
Date: 5 February 2019
Volume: 7
Number: 1
ISSN: 2320-8694
Identifiers:
NumberType
10.18006/2019.7(1).74.85DOI
Rights: All the articles published by (Journal of Experimental Biology and Agricultural Sciences) are licensed under a CC BY-NC 4.0
Divisions: Schools > School of Animal, Rural and Environmental Sciences
Depositing User: Jonathan Gallacher
Date Added: 27 Feb 2019 10:30
Last Modified: 27 Feb 2019 10:30
URI: http://irep.ntu.ac.uk/id/eprint/35824

Actions (login required)

Edit View Edit View

Views

Views per month over past year

Downloads

Downloads per month over past year