Prediction of crude protein, extractable fat, calcium and phosphorus contents of broiler chicken carcasses using near-infrared reflectance spectroscopy

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Abstract

Near-infrared reflectance spectroscopic (NIRS) calibrations were developed for accurate and fast prediction of whole broiler chicken carcass composition. The Feed and Forage Foss systems Model 5000 Reflectance Transport Model 5000 with near-infrared reflectance spectroscopy (NIRS)-WinISI II windows software was used for this purpose. One equation was developed for the prediction of each carcass component. One hundred and fifty freeze dried broiler whole carcass samples were ground in a Cyclotech 1,093 sample mill and analyzed for dry matter, protein, fat, calcium and phosphate. Samples were divided into two sets: a calibration set from which equations were derived and a prediction set used to validate these equations. The chemical analysis values (mean±SD) were calculated based on dry matter basis as follows: dry matter: 33.41±2.78 (range: 26.41-43.47), protein: 54.04±6.63 (range: 36.20-76.09), fat 35.44±8.34 (range: 7.50-55.03), calcium 2.55±0.65 (range: 0.99-4.41), phosphorus 1.38±0.26 (range: 0.60-2.28). One hundred and three samples were used to calibrate the equations and prediction values. The software used was modified to obtain partial least square regression statistics, as it is the most suitable for natural products analysis. The coefficients of determination (R2) and the standard errors of prediction were 0.82 and 1.83 for the dry matter, 0.96 and 1.98 for protein, 0.99 and 1.07 for fat, 0.90 and 0.30 for calcium and 0.91 and 0.11 for phosphorus, respectively. The present study indicated that NIRS can be calibrated to predict the whole broiler carcass chemical composition, including minerals in a rapid, accurate, and cost effective manner. It neither requires skilled operators nor generates hazardous waste. These findings may have practical importance to improve instrumental procedures for quick evaluation of broiler carcass composition.

Original languageEnglish
Pages (from-to)1036-1040
Number of pages5
JournalAsian-Australasian Journal of Animal Sciences
Volume18
Issue number7
Publication statusPublished - Jul 2005

Fingerprint

chicken carcasses
Near-Infrared Spectroscopy
near-infrared spectroscopy
Phosphorus
Chickens
crude protein
broiler chickens
Fats
Calcium
calcium
phosphorus
Calibration
prediction
reflectance
Software
lipids
Hazardous Waste
carcass composition
Proteins
Biological Products

Keywords

  • Broilers
  • Carcass Composition
  • Near-infrared Reflectance Spectroscopy

ASJC Scopus subject areas

  • Animal Science and Zoology

Cite this

@article{ff476dfe2f74459191717edbaa0886bd,
title = "Prediction of crude protein, extractable fat, calcium and phosphorus contents of broiler chicken carcasses using near-infrared reflectance spectroscopy",
abstract = "Near-infrared reflectance spectroscopic (NIRS) calibrations were developed for accurate and fast prediction of whole broiler chicken carcass composition. The Feed and Forage Foss systems Model 5000 Reflectance Transport Model 5000 with near-infrared reflectance spectroscopy (NIRS)-WinISI II windows software was used for this purpose. One equation was developed for the prediction of each carcass component. One hundred and fifty freeze dried broiler whole carcass samples were ground in a Cyclotech 1,093 sample mill and analyzed for dry matter, protein, fat, calcium and phosphate. Samples were divided into two sets: a calibration set from which equations were derived and a prediction set used to validate these equations. The chemical analysis values (mean±SD) were calculated based on dry matter basis as follows: dry matter: 33.41±2.78 (range: 26.41-43.47), protein: 54.04±6.63 (range: 36.20-76.09), fat 35.44±8.34 (range: 7.50-55.03), calcium 2.55±0.65 (range: 0.99-4.41), phosphorus 1.38±0.26 (range: 0.60-2.28). One hundred and three samples were used to calibrate the equations and prediction values. The software used was modified to obtain partial least square regression statistics, as it is the most suitable for natural products analysis. The coefficients of determination (R2) and the standard errors of prediction were 0.82 and 1.83 for the dry matter, 0.96 and 1.98 for protein, 0.99 and 1.07 for fat, 0.90 and 0.30 for calcium and 0.91 and 0.11 for phosphorus, respectively. The present study indicated that NIRS can be calibrated to predict the whole broiler carcass chemical composition, including minerals in a rapid, accurate, and cost effective manner. It neither requires skilled operators nor generates hazardous waste. These findings may have practical importance to improve instrumental procedures for quick evaluation of broiler carcass composition.",
keywords = "Broilers, Carcass Composition, Near-infrared Reflectance Spectroscopy",
author = "Kadim, {I. T.} and O. Mahgoub and W. Al-Marzooqi and K. Annamalai",
year = "2005",
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journal = "Asian-Australasian Journal of Animal Sciences",
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T1 - Prediction of crude protein, extractable fat, calcium and phosphorus contents of broiler chicken carcasses using near-infrared reflectance spectroscopy

AU - Kadim, I. T.

AU - Mahgoub, O.

AU - Al-Marzooqi, W.

AU - Annamalai, K.

PY - 2005/7

Y1 - 2005/7

N2 - Near-infrared reflectance spectroscopic (NIRS) calibrations were developed for accurate and fast prediction of whole broiler chicken carcass composition. The Feed and Forage Foss systems Model 5000 Reflectance Transport Model 5000 with near-infrared reflectance spectroscopy (NIRS)-WinISI II windows software was used for this purpose. One equation was developed for the prediction of each carcass component. One hundred and fifty freeze dried broiler whole carcass samples were ground in a Cyclotech 1,093 sample mill and analyzed for dry matter, protein, fat, calcium and phosphate. Samples were divided into two sets: a calibration set from which equations were derived and a prediction set used to validate these equations. The chemical analysis values (mean±SD) were calculated based on dry matter basis as follows: dry matter: 33.41±2.78 (range: 26.41-43.47), protein: 54.04±6.63 (range: 36.20-76.09), fat 35.44±8.34 (range: 7.50-55.03), calcium 2.55±0.65 (range: 0.99-4.41), phosphorus 1.38±0.26 (range: 0.60-2.28). One hundred and three samples were used to calibrate the equations and prediction values. The software used was modified to obtain partial least square regression statistics, as it is the most suitable for natural products analysis. The coefficients of determination (R2) and the standard errors of prediction were 0.82 and 1.83 for the dry matter, 0.96 and 1.98 for protein, 0.99 and 1.07 for fat, 0.90 and 0.30 for calcium and 0.91 and 0.11 for phosphorus, respectively. The present study indicated that NIRS can be calibrated to predict the whole broiler carcass chemical composition, including minerals in a rapid, accurate, and cost effective manner. It neither requires skilled operators nor generates hazardous waste. These findings may have practical importance to improve instrumental procedures for quick evaluation of broiler carcass composition.

AB - Near-infrared reflectance spectroscopic (NIRS) calibrations were developed for accurate and fast prediction of whole broiler chicken carcass composition. The Feed and Forage Foss systems Model 5000 Reflectance Transport Model 5000 with near-infrared reflectance spectroscopy (NIRS)-WinISI II windows software was used for this purpose. One equation was developed for the prediction of each carcass component. One hundred and fifty freeze dried broiler whole carcass samples were ground in a Cyclotech 1,093 sample mill and analyzed for dry matter, protein, fat, calcium and phosphate. Samples were divided into two sets: a calibration set from which equations were derived and a prediction set used to validate these equations. The chemical analysis values (mean±SD) were calculated based on dry matter basis as follows: dry matter: 33.41±2.78 (range: 26.41-43.47), protein: 54.04±6.63 (range: 36.20-76.09), fat 35.44±8.34 (range: 7.50-55.03), calcium 2.55±0.65 (range: 0.99-4.41), phosphorus 1.38±0.26 (range: 0.60-2.28). One hundred and three samples were used to calibrate the equations and prediction values. The software used was modified to obtain partial least square regression statistics, as it is the most suitable for natural products analysis. The coefficients of determination (R2) and the standard errors of prediction were 0.82 and 1.83 for the dry matter, 0.96 and 1.98 for protein, 0.99 and 1.07 for fat, 0.90 and 0.30 for calcium and 0.91 and 0.11 for phosphorus, respectively. The present study indicated that NIRS can be calibrated to predict the whole broiler carcass chemical composition, including minerals in a rapid, accurate, and cost effective manner. It neither requires skilled operators nor generates hazardous waste. These findings may have practical importance to improve instrumental procedures for quick evaluation of broiler carcass composition.

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