The potential of non-movement behavior observation method for
                    detection of sick broiler chickens

Kim, Hyunsoo; Lee, Woo-Do; Jang, Hyung‐Kwan; Kang, Min; Kang, Hwan-Ku

doi:10.5187/jast.2022.e105

J Anim Sci Technol

2022

DOI: 10.5187/jast.2022.e105

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The potential of non-movement behavior observation method for detection of sick broiler chickens

Hyunsoo Kim¹,

Woo-Do Lee²,

Hyung‐Kwan Jang³

et al.

Abstract: ORCID (for more information, please visit https://orcid.org) Hyunsoo Kim (https://orcid.org/0000-0001-8887-1318) Woo-Do Lee (https://orcid.org/0000-0003-4861-4637) Hyung-Kwan Jang (https://orcid.org/0000-0003-3542-3620) Min Kang (https://orcid.org/0000-0001-5650-1144) Hwan-Ku Kang (https://orcid.org/0000-0002-4286-3141) Competing interestsNo potential conflict of interest relevant to this article was reported.

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“…Based on the identified behaviors, the activities of monitored poultry could be further analyzed. For example, if walking and drinking activities were reduced, individuals would be most susceptible to pathogens and might already be infected [60].…”

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confidence: 99%

Poultry disease early detection methods using deep learning technology

Yajie,

Md Johar,

Iqbal Hajamydeen

2023

IJEECS

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<span>Poultry production is a pivotal contributor to global economic growth, playing a central role in promoting human ecosystem sustainability. It offers affordable and readily accessible protein sources, encompassing meat, eggs, and other by-products. Beyond its direct nutritional benefits, poultry production enhances household income, bolsters food security, and aids in poverty reduction, making it integral to worldwide economic advancement. However, as the global population surges, so does the demand for poultry meat and eggs. Concurrently, poultry disease management emerges as a paramount challenge, leading to significant threats to food security and economic stability. Leveraging cutting-edge technology offers promising avenues to devise strategies that not only bolster farm profitability but also mitigate environmental impacts and foster the well-being of both animals and humans. This study systematically reviews the latest literature concerning poultry disease diagnosis based on deep learning techniques, elucidating the clinical manifestations associated with various ailments. The analysis indicates that emerging technological solutions, especially image processing and deep learning (DL), substantially outperform conventional manual inspection methods in early disease detection and warning in the poultry sector. Such innovations underscore their potential for revolutionizing poultry health management and disease mitigation.</span>

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mentioning

confidence: 99%

Poultry disease early detection methods using deep learning technology

Yajie,

Md Johar,

Iqbal Hajamydeen

2023

IJEECS

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The potential of non-movement behavior observation method for detection of sick broiler chickens

Cited by 1 publication

References 51 publications

Poultry disease early detection methods using deep learning technology

Poultry disease early detection methods using deep learning technology

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