Deep Learning-Driven Poultry Fecal Image Recognition and Disease Early Warning System Design
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Abstract
The sustainable development of the poultry industry is constrained by frequent disease outbreaks and delayed clinical diagnosis, while conventional disease-control approaches based on manual experience are inadequate for precise management in large-scale farming. This study proposes an intelligent poultry-disease early-warning system based on deep-learning-driven fecal image recognition. Fecal morphological features are used as key indicators for early disease detection, and a dataset containing 10,548 valid samples across five categories—healthy, coccidiosis, Newcastle disease, infectious bursal disease, and salmonellosis—is constructed in collaboration with large-scale poultry farms in Guangdong Province. EfficientNet-B3 is adopted as the backbone network, and a Convolutional Block Attention Module (CBAM) and lightweight Lite-FPN multi-scale feature fusion structure are embedded to enhance fine-grained lesion recognition. The system integrates edge computing, industrial imaging, and wireless sensing for real-time deployment in poultry houses. Results show that warning accuracy reaches 91.6%, system availability reaches 99.94%, and the mortality-and-culling rate decreases by 22.6%, demonstrating the engineering feasibility and practical utility of the proposed system.
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References
A. Ngonyoka, “Ethnoveterinary plant remedies and practices used for treatment of chicken diseases in Dodoma, Tanzania,” Heliyon, vol. 12, no. 1, e44277, 2026. DOI: https://doi.org/10.1016/j.heliyon.2025.e44277
A. Nabatanzi, B. S. Obakiro, A. Walusansa, et al., “Knowledge and practices of traditional treatment of chicken diseases using medicinal plants by indigenous communities in Najjembe sub-county, Buikwe district central Uganda,” BMC Veterinary Research, vol. 21, no. 1, 551, 2025. DOI: https://doi.org/10.1186/s12917-025-05008-z
X. Guo, Y. Wang, J. Li, et al., “DOSA-YOLO: Improved model research for the detection of common chicken diseases using phenotypic features,” Agriculture, vol. 15, no. 19, 1996, 2025. DOI: https://doi.org/10.3390/agriculture15191996
H. M. Khan, S. Soren, R. Jas, et al., “Effects of Saccharomyces cerevisiae fermentation (SCFP) and phytogenic feed additive as alternatives to antibiotic growth promoters on pathogen mitigation, immunomodulation and production performance in commercial broiler chickens,” Poultry Science, vol. 104, no. 11, 105743, 2025. DOI: https://doi.org/10.1016/j.psj.2025.105743
B. N., J. B. Li, F. Y. Liang, et al., “Analysis of major epidemic trends, distribution patterns, and optimization of precision prevention and control measures for chicken diseases,” Friend of Farmers for Getting Rich, no. 35, pp. 126-128, 2025. (in Chinese)
A. Sarma, P. Suri, M. Justice, et al., “An emphasis on the role of long non-coding RNAs in viral gene expression, pathogenesis, and innate immunity in viral chicken diseases,” Non-coding RNA, vol. 11, no. 3, 42, 2025. DOI: https://doi.org/10.3390/ncrna11030042
A. Rosenbaum, S. Rautenschlein, and A. Jung, “Differences in lesion development of slow- and fast-growing meat-type chickens after experimental challenge with Enterococcus cecorum,” Avian Pathology, vol. 54, no. 5, pp. 1-10, 2025. DOI: https://doi.org/10.1080/03079457.2025.2485109
M. V. Gomez, M. P. A. Shaw, K. Abdykerimov, et al., “Economic impact of chicken diseases and other causes of morbidity or mortality in backyard farms in low-income and middle-income countries: A systematic review and meta-analysis,” BMC Veterinary Research, vol. 21, no. 1, 151, 2025. DOI: https://doi.org/10.1186/s12917-025-04549-7
E. A. A. H. Almremdhy, K. A. G. Neamha, A. B. Z. Hilli, et al., “Pathological, hematological, and biochemical alteration in broiler chickens infected with mycotoxin in Babylon province,” Open Veterinary Journal, vol. 14, no. 11, pp. 2848-2859, 2024. DOI: https://doi.org/10.5455/ovj.2024.v14.i11.13
Y. G. Dong, “Main characteristics of chicken disease epidemics and prevention strategies for avian influenza,” China Animal Health, vol. 27, no. 10, pp. 86-88, 2025. (in Chinese)
I. Khalil, A. M. Sayeed, M. Sarkar, et al., “Web-based passive surveillance: Multifactorial assessment of Sonali chicken diseases and antimicrobial prescription pattern in Bangladesh,” Veterinary Sciences, vol. 11, no. 12, 662, 2024. DOI: https://doi.org/10.3390/vetsci11120662
E. A. A. H. Almremdhy, K. A. G. Neamha, A. B. Z. Hilli, et al., “Pathological, hematological, and biochemical alteration in broiler chickens infected with mycotoxin in Babylon province,” Open Veterinary Journal, vol. 14, no. 11, pp. 2848-2859, 2024. DOI: https://doi.org/10.5455/ovj.2024.v14.i11.13
K. Ngongolo, “Awareness and perceptions of poultry keepers about the prevalence of Fowl typhoid in chickens kept in Dodoma, Tanzania,” BMC Veterinary Research, vol. 20, no. 1, 453, 2024. DOI: https://doi.org/10.1186/s12917-024-04299-y
X. Wang, C. Peng, Q. Li, et al., “A Chinese nested named entity recognition model for chicken disease based on multiple fine-grained feature fusion and efficient global pointer,” Applied Sciences, vol. 14, no. 18, 8495, 2024. DOI: https://doi.org/10.3390/app14188495
R. P. Torgerson and M. V. Gomez, “Prevalence data on chicken diseases in low-resource settings,” Revue Scientifique et Technique, vol. 43, pp. 39-47, 2024. DOI: https://doi.org/10.20506/rst.43.3516
G. Zhou, J. Zhang, S. Liu, et al., “Potential of exogenous melatonin administration to mitigate heat stress induced pathophysiology of chicken,” Journal of Thermal Biology, vol. 122, 103883, 2024. DOI: https://doi.org/10.1016/j.jtherbio.2024.103883
G. Zirintunda, J. Kateregga, S. Nalule, et al., “An inventory of ethnoveterinary knowledge for chicken disease control in Soroti district, Uganda,” Journal of Medicinal Plants for Economic Development, vol. 8, no. 1, pp. e1-e12, 2024. DOI: https://doi.org/10.4102/jomped.v8i1.248
H. H. Luong and M. T. Nguyen, “Improving chicken disease classification based on Vision Transformer and combine with integrated gradients explanation,” International Journal of Advanced Computer Science and Applications, vol. 15, no. 4, 2024. DOI: https://doi.org/10.14569/ijacsa.2024.01504124
H. H. Luong and M. T. Nguyen, “Improving chicken disease classification based on Vision Transformer and combine with integrated gradients explanation,” International Journal of Advanced Computer Science and Applications, vol. 15, no. 4, 2024. DOI: https://doi.org/10.14569/ijacsa.2024.01504124
Z. Jingyi, S. Feng, L. Juan, et al., “DNAZyme@CuSNPs dual mimic enzyme probe-amplified chemiluminescent imaging array immunosensor for multiple chicken cytokines detection,” Chinese Chemical Letters, vol. 34, no. 12, 2023. DOI: https://doi.org/10.1016/j.cclet.2023.108791
H. M. S. H., Z. Rasha, E. H., et al., “Anticoccidial activity of Aloe Vera leaves’ aqueous extract and vaccination against Eimeria tenella: Pathological study in broilers,” Veterinary Research Communications, vol. 48, no. 1, pp. 403-416, 2023. DOI: https://doi.org/10.1007/s11259-023-10222-x
W. Guoshuai, H. Yaqi, Y. Xiaomin, et al., “Virome profiling of chickens with hepatomegaly rupture syndrome reveals coinfection of multiple viruses,” Viruses, vol. 15, no. 6, 2023. DOI: https://doi.org/10.3390/v15061249
K. E. T., N. T., and C. M., “Utilisation of Aloe ferox in the treatment and control of chicken ailments in rural communities,” Animal – Science Proceedings, vol. 14, no. 2, pp. 308-309, 2023. DOI: https://doi.org/10.1016/j.anscip.2023.01.414
R. M. Peter, “The role of feeds in the transmission of chicken pathogens in Dodoma Urban District, Tanzania,” Poultry Science, vol. 102, no. 4, 102558, 2023. DOI: https://doi.org/10.1016/j.psj.2023.102558
L. S. D., B. Jeffrey, S. Cameron, et al., “H7N9 bearing a mutation in the nucleoprotein leads to increased pathology in chickens,” Frontiers in Immunology, vol. 13, 974210, 2022. DOI: https://doi.org/10.3389/fimmu.2022.974210
N. Kelvin and C. Andrew, “Effect of sex, age, diseases, and control intervention on chickens’ mortality and its financial implications in Dodoma, Tanzania,” Poultry Science, vol. 101, no. 5, 101785, 2022. DOI: https://doi.org/10.1016/j.psj.2022.101785
S. G. M., S. Olfat, W. A. M. S., et al., “The modulatory effect of carvacrol on viral shedding titer and acute phase response in broiler chickens experimentally infected with infectious bronchitis virus,” Microbial Pathogenesis, 105410, 2022. DOI: https://doi.org/10.1016/j.micpath.2022.105410
G. H. D., H. H., F. H. M. M., et al., “Evaluation of viral load and expression level of apoptotic genes in selected tissues of two hybrids of commercial broiler chickens challenged with infectious bronchitis virus: A comparative study,” Iranian Journal of Veterinary Research, vol. 23, no. 1, pp. 18-23, 2022. DOI: https://doi.org/10.22099/ijvr.2021.35894.5261
A. Ghufran, M. Shams A. R., A. Adnan, et al., “An approach towards IoT-based predictive service for early detection of diseases in poultry chickens,” Sustainability, vol. 13, no. 23, 13396, 2021. DOI: https://doi.org/10.3390/su132313396
A. E. M. E., E. T. M., E. R. A., et al., “Necrotic enteritis in broiler chickens: Disease characteristics and prevention using organic antibiotic alternatives—a comprehensive review,” Poultry Science, vol. 101, no. 2, 101590, 2021. DOI: https://doi.org/10.1016/j.psj.2021.101590
T. Anushri, S. Madhu, D. Amita, et al., “Pathological alterations in commercial chicken affected with salmonella infection,” Indian Journal of Veterinary Pathology, vol. 45, no. 2, pp. 109-115, 2021. DOI: https://doi.org/10.5958/0973-970X.2021.00020.1
S. Mingyan, L. Chen, D. Nuo, et al., “The isolation of high-affinity ssDNA aptamer for the detection of ribavirin in chicken,” Analytical Methods, vol. 13, no. 27, 2021. DOI: https://doi.org/10.1039/d1ay00606a
H. Mbelwa, J. Mbelwa, and D. Machuve, “Deep convolutional neural network for chicken diseases detection,” International Journal of Advanced Computer Science and Applications, vol. 12, no. 2, 2021. DOI: https://doi.org/10.14569/ijacsa.2021.0120295
K. Hye-Ryoung, K. Yong-Kuk, J. Il, et al., “Viral metagenomic analysis of chickens with runting-stunting syndrome in the Republic of Korea,” Virology Journal, vol. 17, no. 1, 53, 2020. DOI: https://doi.org/10.1186/s12985-020-01307-z
A. E. Hussein, H. M. Bejo, A. Omar, et al., “Scoring system for lesions induced by different strains of infectious bursal disease virus in chicken,” International Journal of Poultry Science, vol. 19, no. 4, pp. 153-160, 2020. DOI: https://doi.org/10.3923/ijps.2020.153.160
H. R. Razooqi, A. B. Nasrullah, K. H. Shakeer, et al., “Effect of oxygenated water alone or with vaccines and antibiotics on immune response against viral diseases and intestinal microflora community in broiler chickens,” Indian Journal of Forensic Medicine & Toxicology, vol. 13, no. 4, pp. 1257-1261, 2019. DOI: https://doi.org/10.5958/0973-9130.2019.00474.2