Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models

• Main Authors: Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.
• Other Authors: 58109032700
• Format: Article
• Published: Frontiers Media SA 2024
• Subjects: agriculture; chicken comb; chromaticity; classification model; diseases-infected chicken; energy; image processing; machine learning; accuracy; Article; bacterium detection; classifier; colorimetry; comparative study; data analysis; data extraction; decision tree; Gallus gallus; health status; illumination; k nearest neighbor; kernel method; learning algorithm; morphological trait; nonhuman; performance; probability; sensitivity and specificity; supervised machine learning; support vector machine; virus infection; walking speed
• Institution: Universiti Tenaga Nasional

Bacteria- or virus-infected chicken is conventionally detected by manual observation and confirmed by a laboratory test, which may lead to late detection, significant economic loss, and threaten human health. This paper reports on the development of an innovative technique to detect bacteria- or vir...