Document Detail

Evaluation of Local Approaches to Obtain Accurate Near-Infrared (NIR) Equations for Prediction of Ingredient Composition of Compound Feeds.
MedLine Citation:
PMID:  23876731     Owner:  NLM     Status:  In-Data-Review    
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.
Elvira Fernández-Ahumada; Tom Fearn; Augusto Gómez-Cabrera; José Emilio Guerrero-Ginel; Dolores C Pérez-Marín; Ana Garrido-Varo
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Applied spectroscopy     Volume:  67     ISSN:  1943-3530     ISO Abbreviation:  Appl Spectrosc     Publication Date:  2013 Aug 
Date Detail:
Created Date:  2013-07-23     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0372406     Medline TA:  Appl Spectrosc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  924-9     Citation Subset:  IM    
Department of Animal Production, University of Córdoba, Campus Rabanales, N-IV, Km 396, 14071, Córdoba, Spain.
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