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Application of Innovative Approaches for the Management of Farm Animals

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A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal System and Management".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 8827

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Special Issue Editors

Dr. Eloise S. Fogarty

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Guest Editor

School of Health Medical and Applied Sciences, CQUniversity Australia, Rockhampton, Australia
Interests: precision livestock management; animal welfare; animal behaviour sustainability

Dr. Jaime K. Manning

E-Mail Website
Guest Editor

School of Health Medical and Applied Sciences, CQUniversity Australia, Rockhampton, Australia
Interests: precision livestock management; agri-tech; animal behaviour; animal production

Special Issue Information

Dear Colleagues,

Emerging technologies and digital innovation are transforming the productivity, profitability, and sustainability of agriculture. There has been substantial research regarding the use of these technologies in managed systems. The key, therefore, is to take these findings and apply them in real-life contexts, across diverse farming systems where utility, effectiveness and practicality of application may differ. Furthermore, while much of the research has considered technologies in isolation, the complexity of individual farming systems will likely require integrated systems that consider the farm in its entirety.

This Special Issue will explore technology for innovative farm management across a broad range of contexts, both intensive and extensive animal industries, and for a broad range of purposes. A focus will be on the application of technology and digital innovation in farming systems, including improved animal management and welfare, environmental sustainability and the detection of disease or health issues.

Dr. Eloise S. Fogarty
Dr. Jaime K. Manning
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Animals is an international peer-reviewed open access semimonthly 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 2400 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

agricultural technology
animal behaviour
animal management
animal welfare
digital systems
extensive production systems
intensive production systems
livestock
precision livestock management
sustainability
technological innovation

Published Papers (6 papers)

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Research

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17 pages, 2997 KiB

Open AccessArticle

Diagnostic and Prognostic Value of Clinical Scoring and Lung Ultrasonography to Assess Pulmonary Lesions in Veal Calves

by Julia Hoffelner, Walter Peinhopf-Petz and Thomas Wittek

Animals 2023, 13(22), 3464; https://doi.org/10.3390/ani13223464 - 9 Nov 2023

Cited by 1 | Viewed by 853

Abstract

This study on veal calf respiratory disease assessed the association between an on-farm clinical scoring system and lung ultrasonography with the postmortem inspection of the lungs. The comparisons allowed the calculation of predictive values of the diagnostic methods. In total, 600 calves on an Austrian veal calf farm were examined at the beginning and the end of the fattening period. Overall, the area under the curve (AUC) for ultrasonographic scores was 0.90 (rsp = 0.78) with a sensitivity (Se) of 0.86. The specificity (Sp) was 0.78, and the positive predictive value (PPV) was 0.74. The AUC for the physical examination was 0.76 (rsp = 0.55) with a Se of 0.64, an Sp of 0.81, and a PPV of 0.69. For the combination of ultrasonography and physical examination, an AUC curve of 0.85 (rsp = 0.69) was calculated. A Se of 0.65 and a Sp of 0.88 with a PPV of 0.73 was calculated. This study concluded that both physical and ultrasonographic examination scoring are reliable examination methods for the detection of lung diseases in veal calves. Full article

(This article belongs to the Special Issue Application of Innovative Approaches for the Management of Farm Animals)

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17 pages, 1417 KiB

Open AccessArticle

A Pilot Study on the Feasibility of an Extended Suckling System for Pasture-Based Dairies

by Sandra Liliana Ospina Rios, Caroline Lee, Sarah J. Andrewartha and Megan Verdon

Animals 2023, 13(16), 2571; https://doi.org/10.3390/ani13162571 - 9 Aug 2023

Cited by 1 | Viewed by 1426

Abstract

This study investigated cow-calf productivity in a 10-week, pasture-based, extended suckling system featuring part-time cow-calf contact and once-a-day milking. A total of 30 dairy cows and their calves were assigned to two treatments: (1) cow and calf managed in an extended suckling system; or (2) cow and calf separated at birth and managed as usual. Cow-calf pairs grazed together during the day and spent the night separated by fence-line contact. The dams were reunited with the calves after once-a-day milking every morning. The commercial treatment pairs were separated after birth, and cows were milked twice a day and managed within the farm herd. Commercial calves were reared and managed as per commercial Australian practices. Cow-calf dams yielded 9 L/cow/day less saleable milk (p < 0.001), and their milk had lower fat (p = 0.04) but a higher protein percentage (p < 0.001) than commercial cows during pre-weaning. However, milk yield and composition were comparable post-weaning. Dam-suckled calves gained weight faster and were therefore weaned 2 weeks earlier than commercial calves, which were offered 8 L/day milk. This study has demonstrated a novel system of extended cow-calf suckling that could be practical to implement in pasture-based dairies. The long-term effects and scalability of the extended suckling system described here require further validation. Full article

(This article belongs to the Special Issue Application of Innovative Approaches for the Management of Farm Animals)

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20 pages, 5536 KiB

Open AccessArticle

Exploring ‘Wether’ Grazing Patterns Differed in Native or Introduced Pastures in the Monaro Region of Australia

by Danica Parnell, Jack Edwards and Lachlan Ingram

Animals 2023, 13(9), 1500; https://doi.org/10.3390/ani13091500 - 28 Apr 2023

Viewed by 1209

Abstract

Monitoring livestock allows insights to graziers on valuable information such as spatial distribution, foraging patterns, and animal behavior, which can significantly improve the management of livestock for optimal production. This study aimed to understand what potential variables are significant for predicting where sheep spent the most time in native (NP) and improved (IP) paddocks. Wethers (castrated male sheep) were tracked using Global Positioning System (GPS) collars on 15 sheep in the IP and 15 in the NP, respectively, on a property located in the Monaro region of Southern New South Wales, Australia. Trials were performed over four six-day periods in April, July, and November of 2014 and March in 2015. Data were analyzed to understand various trends that may have occurred during different seasons, using random forest models (RFMs). Of the factors investigated, Normalized Difference Vegetation Index (NDVI) was significant (p < 0.01) and highly important for wethers in the IP, but not the NP, suggesting that quality of pasture was key for wethers in the IP. Elevation, temperature, and near distance to trees were important and significant for predicting residency of wethers in the IP, as well as the NP. The result of this study highlights the ability of predictive models to provide insights on behavior-based modelling of GPS data and further enhance current knowledge about location-based choices of sheep on paddocks. Full article

(This article belongs to the Special Issue Application of Innovative Approaches for the Management of Farm Animals)

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15 pages, 984 KiB

Open AccessArticle

Systematic Evaluation of Different Fresh Cow Monitoring Procedures

by Felix König, Andrew Hancock, Christian Wunderlich, Marcus Klawitter, Thomas Breuer, Anne Simoni, Karina Weimar, Marc Drillich and Michael Iwersen

Animals 2023, 13(7), 1231; https://doi.org/10.3390/ani13071231 - 1 Apr 2023

Cited by 1 | Viewed by 1197

Abstract

Establishing fresh cow monitoring procedures is considered beneficial for cow health, welfare, and productivity. However, they are time consuming and require the cows to be locked up, which restricts their natural behavior. In this study, different fresh cow monitoring procedures were evaluated. Two experiments were conducted to determine: (1) the duration of various examinations and treatments; (2) the time cows remain locked up in headlocks; and (3) the proportion of examination and treatment times relative to the total headlock time. In advance, standard operating procedures were established. Three veterinarians conducted the examinations and treatments based on changes in milk yield, clinical symptoms, and alarms by an accelerometer system. The headlock time was evaluated for three workflow strategies, which differed in the order of examinations and treatments. To determine the duration, cameras were installed, and the video footage was analyzed. The examinations lasted between 1 and 227 s, and the cows were locked up in headlocks between 0.01 and 1.76 h. The lock-up times differed significantly among the three strategies, as well as the proportion. This study provides information that can be used as a basis for the development of time-efficient strategies, and to minimize the impact on cows’ time budgets. Full article

(This article belongs to the Special Issue Application of Innovative Approaches for the Management of Farm Animals)

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12 pages, 1869 KiB

Open AccessArticle

Impact Evaluation of Score Classes and Annotation Regions in Deep Learning-Based Dairy Cow Body Condition Prediction

by Sára Ágnes Nagy, Oz Kilim, István Csabai, György Gábor and Norbert Solymosi

Animals 2023, 13(2), 194; https://doi.org/10.3390/ani13020194 - 4 Jan 2023

Cited by 4 | Viewed by 2328

Abstract

Body condition scoring is a simple method to estimate the energy supply of dairy cattle. Our study aims to investigate the accuracy with which supervised machine learning, specifically a deep convolutional neural network (CNN), can be used to retrieve body condition score (BCS) classes estimated by an expert. We recorded images of animals’ rumps in three large-scale farms using a simple action camera. The images were annotated with classes and three different-sized bounding boxes by an expert. A CNN pretrained model was fine-tuned on 12 and 3 BCS classes. Training in 12 classes with a 0 error range, the Cohen’s kappa value yielded minimal agreement between the model predictions and ground truth. Allowing an error range of 0.25, we obtained minimum or weak agreement. With an error range of 0.5, we had strong or almost perfect agreement. The kappa values for the approach trained on three classes show that we can classify all animals into BCS categories with at least moderate agreement. Furthermore, CNNs trained on 3 BCS classes showed a remarkably higher proportion of strong agreement than those trained in 12 classes. The prediction precision when training with various annotation region sizes showed no meaningful differences. The weights of our trained CNNs are freely available, supporting similar works. Full article

(This article belongs to the Special Issue Application of Innovative Approaches for the Management of Farm Animals)

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18 pages, 2098 KiB

Open AccessFeature PaperSystematic Review

Exploration of Extension Research to Promote Genetic Improvement in Cattle Production: Systematic Review

by Patricia Menchon, Jaime K. Manning, Dave L. Swain and Amy Cosby

Animals 2024, 14(2), 231; https://doi.org/10.3390/ani14020231 - 11 Jan 2024

Viewed by 778

Abstract

In the cattle industry, tools for genetic improvement play a crucial role in animal selection. The changing circumstances faced by farmers and the significant part agricultural extension plays in these changes must be considered. Despite progress in genetic selection tools and the push for their adoption through extension services, a disconnect persists between the development of new strategies and tools for genetic improvement and their adoption by livestock farmers. This systematic review is designed to globally investigate the methodology and outcomes of extension research aimed at advancing genetic improvement in beef cattle. Adhering to PRISMA guidelines, a search was conducted across four databases for studies published from January 2012 to June 2023. Twenty-one articles were selected and reviewed. The research design in the articles predominantly employed mixed methods, utilizing both quantitative and qualitative approaches. While social factors are acknowledged as influencers in the adoption process, the application of theories or frameworks from social sciences is still in its early stages. To successfully implement extension activities that promote the use of genetic tools in cattle for a specific production region, more participatory research is required where farmers are actively involved. Full article

(This article belongs to the Special Issue Application of Innovative Approaches for the Management of Farm Animals)

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