New Management Technologies for Precision Livestock Farming

A special issue of AgriEngineering (ISSN 2624-7402). This special issue belongs to the section "Livestock Farming Technology".

Deadline for manuscript submissions: 25 July 2026 | Viewed by 2053

Special Issue Editors


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Guest Editor
1. Graduate Program in Production Engineering, Paulista University, Sao Paulo, Brazil
2. College of Agricultural Engineering, State University of Campinas, Campinas 13083-970, Brazil
Interests: precision livestock farming; image analysis; data analysis; new technologies applied to management strategies; use of LLM in livestock management

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Guest Editor
College of Agricultural Engineering, State University of Campinas, Campinas 13083-970, Brazil
Interests: precision livestock farming; image analysis; data analysis; artificial Intelligence
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Special Issue Information

Dear Colleagues,

Driven by population growth and changing dietary preferences, the global demand for livestock products continues to rise and meeting it sustainably, efficiently, and ethically presents significant challenges and opportunities for agricultural engineering. This Special Issue aims to gather cutting-edge research and innovative solutions that are transforming livestock production systems through advanced management strategies and the integration of new technologies.

We invite original research articles, reviews, and case studies that explore the application of engineering principles and technological advancements to enhance productivity, improve animal welfare, reduce environmental impact, and optimize resource utilization in livestock farming. The focus is on interdisciplinary approaches that bridge the gap between engineering, animal science, and environmental sustainability.

This Special Issue will cover, but is not limited to, the following areas:

  • Sensor technologies (wearable, environmental, remote sensing) for real-time monitoring of animal health, behavior, and physiological parameters.
  • Automated animal identification and tracking.
  • Data analytics for disease early detection, prediction of production traits, and optimization of farm operations.
  • Image processing and computer vision for animal monitoring and welfare assessment.
  • Predictive modeling for feed conversion, growth rates, and environmental conditions.
  • Smart ventilation and climate control systems in animal housing.
  • Non-invasive diagnostic tools and early warning systems for diseases.
  • Automated systems for stress detection and welfare assessment.
  • Development of platforms for integrating diverse farm data.
  • Decision support tools for optimized management practices.

The livestock sector faces increasing pressure to produce more with fewer resources while simultaneously addressing concerns related to environmental impact, animal welfare, and food safety. Traditional management practices are often insufficient to meet these complex demands, and engineering solutions and new technologies offer transformative potential to overcome these challenges by enabling more precise, efficient, and sustainable production systems.

This Special Issue will serve as a timely platform to disseminate the latest advancements, highlight emerging trends, and foster interdisciplinary collaboration among researchers and practitioners. It will significantly contribute to the body of knowledge by showcasing how agriengineering principles drive innovation in livestock production, ultimately leading to improved profitability for farmers, enhanced animal well-being, and a reduced ecological footprint.

Prof. Dr. Irenilza De Alencar Nääs
Prof. Dr. Daniella Jorge De Moura
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AgriEngineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • precision livestock farming
  • agricultural engineering
  • animal welfare
  • sustainable livestock production
  • new management technologies

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Published Papers (2 papers)

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Research

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12 pages, 523 KB  
Article
Days in Milk, Parity and Milk Production Influence on the Hind Hoof Skin Surface Temperature in Dairy Cattle
by Antía Acción, Jacobo Álvarez, Raquel Holgado, Lucía Vidal, Renato Barrionuevo, Román González, Juan José Becerra, Ana Isabel Peña, Pedro García Herradón, Luís Ángel Quintela and Uxía Yáñez
AgriEngineering 2026, 8(1), 13; https://doi.org/10.3390/agriengineering8010013 - 1 Jan 2026
Viewed by 607
Abstract
Prompt identification of clinical signs and early treatment of hoof problems are essential to effectively manage and reduce lameness in dairy farms. This study aimed to evaluate the influence of days in milk (DIM), parity, and milk yield (MY) on the mean temperature [...] Read more.
Prompt identification of clinical signs and early treatment of hoof problems are essential to effectively manage and reduce lameness in dairy farms. This study aimed to evaluate the influence of days in milk (DIM), parity, and milk yield (MY) on the mean temperature (MT) of the hind hooves in healthy cows, with the perspective of implementing infrared thermography (IRT) as an automated tool for early lameness detection. Thermal images were collected from 156 milking cows, capturing both cranial and caudal surfaces of each hind foot. Significant differences were found between primiparous and multiparous cows across all analyzed surfaces. Moreover, cows with higher milk production exhibited significantly higher MT in the caudal left hoof and on both cranial surfaces. The variable DIM (group 1 = cows with ≤202 DIM; group 2 = cows with >202 DIM) did not significantly affect MT on caudal surfaces; however, on the cranial view, MT of the right hoof was higher in group 2, while group 1 tended to show higher MT in the left hoof (p = 0.051). In conclusion, hoof MT increases in multiparous and high-producing cows. Additionally, during the first 200 days of lactation, cranial hoof surface temperatures tend to rise. Future studies should include continuous monitoring using automated systems to record variations throughout the day. Full article
(This article belongs to the Special Issue New Management Technologies for Precision Livestock Farming)
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Review

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25 pages, 966 KB  
Review
Precision Livestock Farming for Dairy Sheep: A Literature Review of IoT and Decision-Support Systems for Enhanced Management and Welfare
by Maria Consuelo Mura, Othmane Trimasse, Vincenzo Carcangiu and Sebastiano Luridiana
AgriEngineering 2026, 8(2), 58; https://doi.org/10.3390/agriengineering8020058 - 6 Feb 2026
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Abstract
The dairy sheep, vital to the Mediterranean economy, struggles to balance productivity, sustainability, and animal welfare, especially in extensive, small-scale systems. Precision livestock farming (PLF) technologies offer new opportunities by enabling continuous, non-invasive, and data-driven monitoring across diverse farming conditions. Despite rapid progress [...] Read more.
The dairy sheep, vital to the Mediterranean economy, struggles to balance productivity, sustainability, and animal welfare, especially in extensive, small-scale systems. Precision livestock farming (PLF) technologies offer new opportunities by enabling continuous, non-invasive, and data-driven monitoring across diverse farming conditions. Despite rapid progress in sensors, computer vision, wearable devices, and artificial intelligence (AI), a comprehensive synthesis focused on dairy sheep remains limited. This review provides an updated overview of PLF applications in dairy sheep farming, based on a literature review. The 2018–2025 timeframe was chosen to capture recent advances in Internet of Things (IoT), AI, and sensor technologies that have achieved practical relevance only in recent years. The review identifies core technological domains such as automated weight and body condition monitoring, biometric identification, wearable and IoT-based sensors, localization systems, behavioral and thermal monitoring, virtual fencing, drone-assisted herding, and advanced decision-support tools. Innovations including lightweight deep-learning models, multimodal sensing frameworks, and digital twins highlight the growing potential for scalable, real-time applications. While technological progress is substantial, practical adoption is hindered by economic, technical, interoperability, and ethical barriers. This review consolidates current evidence and identifies future priorities to guide the development of integrated, welfare-focused PLF solutions for dairy sheep farming. Full article
(This article belongs to the Special Issue New Management Technologies for Precision Livestock Farming)
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