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Animals
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Intelligent Animal Husbandry
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Intelligent Animal Husbandry

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

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 8672

Special Issue Editors

Dr. Elena Kistanova

E-Mail Website
Guest Editor
Institute of Biology and Immunology of Reproduction, BAS, 73 Tzarigradsko shose, 1113 Sofia, Bulgaria
Interests: plant bioactives and reproduction; nutrigenomic effect on reproductive tissue; epigenetic of gametes; semen sexing
Prof. Dr. Stanimir Yotov

E-Mail Website
Guest Editor
Department of Obstetrics, Reproduction and Reproductive Disorders, Faculty of Veterinary Medicine, Student Campus, Trakia University, 6000 Stara Zagora, Bulgaria
Interests: reproduction and assisted reproductive technologies in farm animals; udder diseases
Dr. Darina Zaimova

E-Mail Website
Guest Editor
Department of Industrial Business and Entrepreneurship, Economic Faculty, Student Campus, 6000 Stara Zagora, Bulgaria
Interests: industrial business; entrepreneurship; rural development; bio-economic; eco-innovations; economic and management of farms

Special Issue Information

Dear Colleagues,

The Special Issue “Intelligent Animal Husbandry” aims to collect fundamental and applied scientific research articles that can provide the animal husbandry sector with innovative methods and means for intelligent and efficient animal breeding with fewer human resources and a reduced impact on the environment. It proposes to unite and discuss the scientific research in key areas such as animal breeding and bioinformatics; genetics (epigenetics) and breeding; reproductive biotechnologies (semen and embryo sexing, embryo transfer); ecology and biodiversity; food; transport; and energy efficiency, all of which are oriented towards applications of the obtained scientific results in modern farms. Additional topics may include the development of automatic and robotic animal husbandry operations such as breeding, feeding, milking, and cleaning, the economics and management of farms with the application of information and communication technologies; as well as modeling of the processes and phenomena in animal husbandry with the processing of large volumes of data and complex mathematical and computer models.

Dr. Elena Kistanova
Prof. Dr. Stanimir Yotov
Dr. Darina Zaimova
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

  • genetic progress in animals (semen and embryo sexing, embryo transfer)
  • epigenetics
  • bioinformatics in animal breeding
  • IT in management of animal husbandry
  • automation and robotization of breeding, feeding, milking, and cleaning in farms

Published Papers (7 papers)

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Research

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14 pages, 989 KiB  
Article
Milking Temperament and Its Association with Test-Day Milk Yield in Bulgarian Murrah Buffaloes
by Tihomira Stepancheva, Ivaylo Marinov and Zhivka Gergovska
Animals 2024, 14(7), 987; https://doi.org/10.3390/ani14070987 - 22 Mar 2024
Viewed by 639
Abstract
The goal of this research was to evaluate milking temperament and its relationship with test-day milk (TDMY0) yield in Bulgarian Murrah buffaloes. This study involved 90 buffalo cows reared under a tie-stall production system which were milked twice a day with a milking [...] Read more.
The goal of this research was to evaluate milking temperament and its relationship with test-day milk (TDMY0) yield in Bulgarian Murrah buffaloes. This study involved 90 buffalo cows reared under a tie-stall production system which were milked twice a day with a milking pipeline. The behavioral responses of the buffaloes were reported during preparation for milking and during actual milking. The average temperament score during preparation for milking was 1.83, and 1.93 during milking itself. The most common reaction was leg lifting (18.9%), followed by cows moving on the stall bed (10%), definite kicking (9.9%), and 13.3% managing to remove the milking cluster during milking. The frequency of buffaloes showing adverse reactions (scores 4 and 5) increased considerably during milking compared to preparation for milking. Repeated scoring of temperament during the same lactation did not show a significant difference in the frequency of temperament assessments both in preparation for milking and during milking. The minimal difference may be due to the accuracy of the assessment or a momentary change in the condition of the animals during the two scorings. Cows with the most unwanted milking behavior (scores 5 and 4) had the highest LS means for TDMY, 8.18 kg and 7.65 kg, respectively. The reasons for these buffaloes remaining until later lactations was their high milk yield and the injection of oxytocin before milking, which helps them to be fully milked. Full article
(This article belongs to the Special Issue Intelligent Animal Husbandry)
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14 pages, 3035 KiB  
Article
Integrated Analysis of Machine Learning and Deep Learning in Silkworm Pupae (Bombyx mori) Species and Sex Identification
by Haibo He, Shiping Zhu, Lunfu Shen, Xuening Chang, Yichen Wang, Di Zeng, Benhua Xiong, Fangyin Dai and Tianfu Zhao
Animals 2023, 13(23), 3612; https://doi.org/10.3390/ani13233612 - 22 Nov 2023
Viewed by 1115
Abstract
Hybrid pairing of the corresponding silkworm species is a pivotal link in sericulture, ensuring egg quality and directly influencing silk quantity and quality. Considering the potential of image recognition and the impact of varying pupal postures, this study used machine learning and deep [...] Read more.
Hybrid pairing of the corresponding silkworm species is a pivotal link in sericulture, ensuring egg quality and directly influencing silk quantity and quality. Considering the potential of image recognition and the impact of varying pupal postures, this study used machine learning and deep learning for global modeling to identify pupae species and sex separately or simultaneously. The performance of traditional feature-based approaches, deep learning feature-based approaches, and their fusion approaches were compared. First, 3600 images of the back, abdomen, and side postures of 5 species of male and female pupae were captured. Next, six traditional descriptors, including the histogram of oriented gradients (HOG), and six deep learning descriptors, including ConvNeXt-S, were utilized to extract significant species and sex features. Finally, classification models were constructed using the multilayer perceptron (MLP), support vector machine, and random forest. The results indicate that the {HOG + ConvNeXt-S + MLP} model excelled, achieving 99.09% accuracy for separate species and sex recognition and 98.40% for simultaneous recognition, with precision–recall and receiver operating characteristic curves ranging from 0.984 to 1.0 and 0.996 to 1.0, respectively. In conclusion, it can capture subtle distinctions between pupal species and sexes and shows promise for extensive application in sericulture. Full article
(This article belongs to the Special Issue Intelligent Animal Husbandry)
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18 pages, 5112 KiB  
Article
Algorithm for Autonomous Management of a Poultry Farm by a Cyber-Physical System
by Nayden Chivarov, Kristiyan Dimitrov and Stefan Chivarov
Animals 2023, 13(20), 3252; https://doi.org/10.3390/ani13203252 - 18 Oct 2023
Viewed by 902
Abstract
The article presents a Cyber-Physical System (CPS) for intelligent management of a poultry farm for broiler meat production, with a fully autonomous microclimate control. Innovative concepts have been introduced for automated management and changing parameters according to pre-set conditions and schedules, with the [...] Read more.
The article presents a Cyber-Physical System (CPS) for intelligent management of a poultry farm for broiler meat production, with a fully autonomous microclimate control. Innovative concepts have been introduced for automated management and changing parameters according to pre-set conditions and schedules, with the possibility that the parameters of the algorithm can be further adjusted by the operator. The proposed CPS provides for high productivity with minimal production waste, at optimized costs and with minimization of human errors. The CPS is built on the basis of cost-oriented components. A Raspberry Pi 4 8 GB is used as the server, and the free open-source software OpenHAB 3.0 is used to optimize the cost of building the system as much as possible. Full article
(This article belongs to the Special Issue Intelligent Animal Husbandry)
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16 pages, 886 KiB  
Article
Representative Survey for Evaluating Housing and Manure Handling Technologies of the Hungarian Pig Sector
by Zsuzsanna Benedek, Károly Dublecz, Ilona Anna Koltay, Gábor Fitos, Vanda Kisanna Várhelyi, Marianna Magyar, Béla Pirkó and Nóra Hegedűsné Baranyai
Animals 2023, 13(16), 2658; https://doi.org/10.3390/ani13162658 - 18 Aug 2023
Cited by 1 | Viewed by 856
Abstract
In Hungary, there is a lack of information on the pig production technologies in place in the base year of 2005 and changes since then, as well as a lack of information on the number of pigs kept in different age and production [...] Read more.
In Hungary, there is a lack of information on the pig production technologies in place in the base year of 2005 and changes since then, as well as a lack of information on the number of pigs kept in different age and production categories, which makes it difficult to calculate ammonia emissions and reductions in the national inventories. Our research team conducted a representative survey of pig farms to assess housing and manure management technologies in the Hungarian pig sector in 2005 and 2015. Novel expert-based calculation methods were developed to convert farm data on pig populations into daily average numbers (DAN) of animals in different statistical categories and feeding phases. The survey resulted in a representative database of housing, manure handling, storage and manure application practices in Hungarian pig production. The data and methodology from the survey helped to develop an ammonia emission calculator and knowledge transfer tool (AGEM-S) for use by farmers. Full article
(This article belongs to the Special Issue Intelligent Animal Husbandry)
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13 pages, 6480 KiB  
Article
MRI Anatomical Investigation of Rabbit Bulbourethral Glands
by Rosen Dimitrov and Kamelia Stamatova-Yovcheva
Animals 2023, 13(9), 1519; https://doi.org/10.3390/ani13091519 - 30 Apr 2023
Viewed by 1501
Abstract
Anatomical MRI is appropriate for the interpretation of soft tissue findings in the retroperitoneal part of the pelvic cavity. The aim of the current study was to use rabbits as an imaging model to optimize MRI protocols for the investigation of bulbourethral glands. [...] Read more.
Anatomical MRI is appropriate for the interpretation of soft tissue findings in the retroperitoneal part of the pelvic cavity. The aim of the current study was to use rabbits as an imaging model to optimize MRI protocols for the investigation of bulbourethral glands. The research was conducted on twelve clinically healthy, sexually mature male rabbits, eight months of age (New Zealand White), weighing 2.8 kg to 3.2 kg. Tunnel MRI equipment was used. The transverse MRI in the T2-weighted sequence obtained detailed images that were of higher anatomical contrast than those in T1-weighted sequences. The hyperintensity of the glandular findings at T2, compared to the adjacent soft tissues, was due to the content of secretory fluids. The quality of the anatomical tissue contrast has not shown much dependence on the choice of the sequence in dorsal MRI. The sagittal visualization of the rabbit bulbourethral glands corresponded to the localization of the research plane toward a median plane. The imaging results could be used as a morphological base for clinical practice and reproduction. Full article
(This article belongs to the Special Issue Intelligent Animal Husbandry)
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14 pages, 565 KiB  
Article
Influence of Ovarian Status and Steroid Hormone Concentration on Day of Timed Artificial Insemination (TAI) on the Reproductive Performance of Dairy Cows Inseminated with Sexed Semen
by Stanimir Yotov, Ivan Fasulkov, Anatoli Atanasov, Elena Kistanova, Branimir Sinapov, Boyana Ivanova, Dobri Yarkov and Darina Zaimova
Animals 2023, 13(5), 896; https://doi.org/10.3390/ani13050896 - 1 Mar 2023
Cited by 1 | Viewed by 1652
Abstract
This study aimed to evaluate the effect of the ovarian status and steroid hormone concentration on the day of TAI on the reproductive performance of dairy cows subjected to estrus synchronization treatment and timed artificial insemination with sexed semen. Seventy-eight cyclic Holstein cows [...] Read more.
This study aimed to evaluate the effect of the ovarian status and steroid hormone concentration on the day of TAI on the reproductive performance of dairy cows subjected to estrus synchronization treatment and timed artificial insemination with sexed semen. Seventy-eight cyclic Holstein cows pre-treated with PGF2α-GnRH were divided in two groups—I (Preselect-OvSynch, n = 38) and II (OvSynch+PRID-7-day+eCG, n = 40)—and inseminated with sexed semen. The presence of preovulatory follicle (PF) with or without corpus luteum (CL), the PF diameter, the estradiol (E2) and progesterone (P4) concentrations on the day of TAI, the pregnancy rate (PR) and embryo loss were determined. On the day of TAI, 78.4% of all the pregnant cows presented a PF (mean size 1.80 ± 0.12 cm) without CL, low P4 (0.59 ± 0.28 ng/mL) and high E2 (12.35 ± 2.62 pg/mg) concentrations. The positive correlation between the size of the PF and the level of E2 in the pregnant cows from group II was stronger than that of group I (R = 0.82 vs. R = 0.52, p < 0.05). The pregnancy rate on day 30 (57.5% vs. 36.8%) and day 60 (50% vs. 26.3%; p < 0.05) and the embryo losses (13% vs. 28.5%) showed better effects of treatment in group II. In conclusion, the ovarian status and the steroid hormone concentration on the day of TAI influence the pregnancy rates of dairy cows subjected to estrus synchronization and timed artificial insemination with sexed semen. Full article
(This article belongs to the Special Issue Intelligent Animal Husbandry)
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Review

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10 pages, 381 KiB  
Review
Assessing Decision Support Tools for Mitigating Tail Biting in Pork Production: Current Progress and Future Directions
by Sophia A. Ward, John R. Pluske, Kate J. Plush, Jo M. Pluske and Charles V. Rikard-Bell
Animals 2024, 14(2), 224; https://doi.org/10.3390/ani14020224 - 10 Jan 2024
Viewed by 857
Abstract
Tail biting (TB) in pigs is a complex issue that can be caused by multiple factors, making it difficult to determine the exact etiology on a case-by-case basis. As such, it is often difficult to pinpoint the reason, or set of reasons, for [...] Read more.
Tail biting (TB) in pigs is a complex issue that can be caused by multiple factors, making it difficult to determine the exact etiology on a case-by-case basis. As such, it is often difficult to pinpoint the reason, or set of reasons, for TB events, Decision Support Tools (DSTs) can be used to identify possible risk factors of TB on farms and provide suitable courses of action. The aim of this review was to identify DSTs that could be used to predict the risk of TB behavior. Additionally, technologies that can be used to support DSTs, with monitoring and tracking the prevalence of TB behaviors, are reviewed. Using the PRISMA methodology to identify sources, the applied selection process found nine DSTs related to TB in pigs. All support tools relied on secondary information, either by way of the scientific literature or expert opinions, to determine risk factors for TB predictions. Only one DST was validated by external sources, seven were self-assessed by original developers, and one presented no evidence of validation. This analysis better understands the limitations of DSTs and highlights an opportunity for the development of DSTs that rely on objective data derived from the environment, animals, and humans simultaneously to predict TB risks. Moreover, an opportunity exists for the incorporation of monitoring technologies for TB detection into a DST. Full article
(This article belongs to the Special Issue Intelligent Animal Husbandry)
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