Prediction of the nutritional composition of the crop contents of free-living scarlet macaw chicks by near-infrared reflectance spectroscopy
Juan Cornejo A D E , Ryan Taylor B , Thomas Sliffe B , Christopher A. Bailey C and Donald J. Brightsmith A
+ Author Affiliations
- Author Affiliations
A The Schubot Center, Department of Veterinary Pathobiology, College of Veterinary Medicine, Texas A&M University, 4467 TAMU, College Station, TX 77843, USA.
B Perten Instruments Inc., 6444 South Sixth Street, Springfield, IL 62712, USA.
C Department of Poultry Science, College of Agriculture and Life Science, Texas A&M University, 2472 TAMU, College Station, TX 77843, USA.
D Present address: Bronx Zoo/WCS, 2300 Southern Boulevard, Bronx, NY 10460, USA.
E Corresponding author. Email: J.cornejo.c@hotmail.com
Wildlife Research 39(3) 230-233 https://doi.org/10.1071/WR11130
Submitted: 23 July 2011 Accepted: 12 January 2012 Published: 12 April 2012
Abstract
Context: It is difficult to determine with accuracy the nutrition of bird diets through observation and analysis of dietary items. Collection of the ingested material from the birds provides an alternative but it is often limited by the small sizes of samples that can be obtained.
Aims: We tested the efficacy of near-infrared reflectance spectroscopy (NIRS) to assess the nutritional composition of very small samples of growing-parrot crop content.
Methods: We used 30 samples of the crop content of free-living scarlet macaw (Ara macao) chicks. Samples were scanned with a near-infrared reflectance analyser, and later analysed by traditional wet laboratory methods for crude protein/N, fat, ash, neutral detergent fibre, P, K, Ca, Mg, Cu, Zn and S. A calibration model was developed using principal components analysis.
Key results: Coefficients of determination in the calibration (R2) and standard errors of cross-validation (SECV) for most of the nutrients showed a good performance (mean R2 of 0.91 ± 0.11 s.d., n = 10) when excluding Zn (R2 of 0.15, SECV = 25.37).
Conclusions: The present results established NIRS as a valid technique for the non-destructive, low-cost prediction of a variety of nutritional attributes of avian crop contents as small as 0.5-g dry weight.
Implications: The use of NIRS expands the possibilities of wild-animal nutrition research.
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