Skip to main content

Evaluation of Local Approaches to Obtain Accurate Near-Infrared (NIR) Equations for Prediction of Ingredient Composition of Compound Feeds

Buy Article:

$29.00 plus tax (Refund Policy)


This research work investigated new methods to improve the accuracy of intact feed calibrations for the near-infrared (NIR) prediction of the ingredient composition. When NIR reflection spectroscopy, together with linear models, was used for the prediction of the ingredient composition, the results were not always acceptable. Therefore, other methods have been investigated. Three different local methods (comparison analysis using restructured near-infrared and constituent data [CARNAC]), locally weighed regression [LWR], and LOCAL) were applied to a large (N = 20 320) and heterogeneous population of non-milled feed compounds for the NIR prediction of the inclusion percentage of wheat and sunflower meal, as representative of two different classes of ingredients. Compared with partial least-squares regression, results showed considerable reductions of standard error of prediction values for all methods and ingredients: reductions of 59, 47, and 50% with CARNAC, LWR, and LOCAL, respectively, for wheat, and reductions of 49, 45, and 43% with CARNAC, LWR, and LOCAL, respectively, for sunflower meal. These results are a valuable achievement in coping with legislation and manufacture requirements concerning the labeling of intact feedstuffs.

Keywords: CARNAC; LOCAL; LWR (locally weighed regression); Large population; Local methods; NIRS (near-infrared reflection spectroscopy); Non-milled feedstuffs

Document Type: Research Article


Affiliations: Department of Animal Production, University of Córdoba, Campus Rabanales, N-IV, Km 396, 14071, Córdoba, Spain

Publication date: August 1, 2013

More about this publication?

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more