Abstract
Abstract: Artificial Intelligence (AI) is at the forefront of a digital revolution in livestock farming, enabling enhanced decision-making, automation, and predictive capabilities across the dairy production system. Techniques such as supervised learning, deep learning, and ensemble methods integrate diverse data sources, including wearable sensor inputs, environmental metrics, and genetic information, to support early disease detection, reproductive monitoring, and behavioral assessment. These innovations, central to Precision Livestock Farming (PLF), offer promising pathways to optimize productivity, improve animal welfare, and reduce the environmental footprint of animal agriculture. AI-driven tools such as facial recognition, computer vision, and Internet of Things (IoT) enabled devices facilitate non-invasive, real-time monitoring, supporting individualized care and proactive management. In dairy systems, the integration of PLF with Industry 4.0 frameworks, coined “Dairy 4.0,” enables smart milking, automated feeding, and continuous health surveillance. However, the adoption of ML and PLF technologies remains uneven, constrained by high implementation costs, inadequate digital infrastructure, limited farmer training, and ethical concerns around data privacy and reduced human-animal interaction. Interoperability issues, poor sensor durability, and lack of standardization further hinder scalability, particularly in smallholder and developing contexts. Overcoming these challenges will require interdisciplinary collaboration, inclusive design, regulatory innovation, and targeted investments in digital infrastructure and farmer capacity-building. When thoughtfully implemented, ML and PLF technologies have the potential to transform livestock farming into a more efficient, ethical, and sustainable enterprise. By aligning technological innovation with the needs of diverse farming systems and ensuring equitable access, the livestock industry can move toward a future defined by resilience, transparency, and data-driven animal care.
Thanks
Thanks to TJVR
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Details
| Primary Language | English |
|---|---|
| Subjects | Animal Health Economics and Management |
| Journal Section | Review |
| Authors | |
| Submission Date | June 10, 2025 |
| Acceptance Date | January 29, 2026 |
| Publication Date | March 29, 2026 |
| DOI | https://doi.org/10.47748/tjvr.1716448 |
| IZ | https://izlik.org/JA83YP73TS |
| Published in Issue | Year 2026 Volume: 10 Issue: 1 |
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Prof. Dr. İsmail Hakkı Ekin, 1971 Yılında Siirt'te doğdu. İlk ve ortaöğrenimini Van'da tamamladı. 1989 yılında Van Teknik Lisesi Motor Bölümünü birincilikle bitirdi. 1990 yılında girdiği Van Yüzüncü Yıl Üniversitesi Veteriner Fakültesinden 1995 yılında mezun oldu. Aynı yıl kısa dönem askerlik görevini yerine getirerek, Temmuz 1996’da terhis oldu. 1997’de Van Yüzüncü Yıl Üniversitesi Veteriner Fakültesi’nde Araştırma Görevliliğine atandı. Van Yüzüncü Yıl Üniversitesi Sağlık Bilimleri Enstitüsü Veteriner Mikrobiyoloji Anabilim Dalında başladığı Yüksek Lisans öğrenimini 1998 yılında, Doktora öğrenimini ise 2004 yılında bitirerek Bilim Doktoru (PhD) unvanını aldı. Dr. Araştırma görevlisi olarak 2 yıl süreyle görev yaptıktan sonra Şubat 2006’da Dr. Öğretim Üyesi (Yrd. Doç. Dr.) kadrosuna atandı. Van Yüzüncü Yıl Üniversitesi Sağlık Bilimleri Enstitüsü Besin Hijyeni ve Teknolojisi Anabilim Dalındaki ikinci Doktora eğitimini de 2022 yılında bitirerek ikinci Bilim Doktoru (PhD) unvanını aldı. 2013 yılında Doçentlik unvanını alan Ekin, 2018 yılında Van Yüzüncü Yıl Üniversitesi Veteriner Fakültesi Mikrobiyoloji Anabilim Dalında Profesörlük kadrosuna atandı. Halen bu birimde Anabilim Dalı Başkanı olarak görevini sürdürmekte olup evli ve üç çocuk babasıdır.
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