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<p>Near Infrared Spectroscopy (NIRS) is a low cost technology widely used in animal feeds quality evaluation. The objective of this study was to develop prediction model to evaluate ash, dry matter and moisture of commercial chicken feed based on NIRS and partial least square analysis. A total of 203 samples were collected from the Central, Western, Eastern, and Northern regions of Uganda of which 142 samples were used for calibration and 61 for validation. The NIRS calibration model presented Coefficient of determination for calibration of 0.74, 0.32 and 0.32; Coefficient of determination for prediction of 0.85, 0.39, and 0.39; and a ratio of performance to deviation of 2.04, 0.94, and 0.94 for ash, dry matter and moisture respectively. The results obtained may suggest that prediction model for ash can be used for rough screening of feed samples. NIRS can serve as a useful tool for chicken producers, feed mills, regulators and researchers to estimate the ash content in commercial chicken feed and ingredients.</p>

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Commercial chicken mash feed quality evaluation using Near Infrared Spectroscopy (NIRS) in Uganda

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月8日

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  • Daniel Kizza,
  • Samuel Okello,
  • Margret Nabulime,
  • Dorothy Kalule Nampanzira,
  • Winfred Awino,
  • Robert Twinamatsiko,
  • Martha Abuo,
  • Sylvia Nalubwama,
  • Sylvia Angubua Baluka,
  • Edward Ssebuufu,
  • Immaculate Nakabugo,
  • Bob Mali,
  • Fiona Kisakye

摘要

Near Infrared Spectroscopy (NIRS) is a low cost technology widely used in animal feeds quality evaluation. The objective of this study was to develop prediction model to evaluate ash, dry matter and moisture of commercial chicken feed based on NIRS and partial least square analysis. A total of 203 samples were collected from the Central, Western, Eastern, and Northern regions of Uganda of which 142 samples were used for calibration and 61 for validation. The NIRS calibration model presented Coefficient of determination for calibration of 0.74, 0.32 and 0.32; Coefficient of determination for prediction of 0.85, 0.39, and 0.39; and a ratio of performance to deviation of 2.04, 0.94, and 0.94 for ash, dry matter and moisture respectively. The results obtained may suggest that prediction model for ash can be used for rough screening of feed samples. NIRS can serve as a useful tool for chicken producers, feed mills, regulators and researchers to estimate the ash content in commercial chicken feed and ingredients.