Latest recommendations
Id | Title * | Authors * | Abstract * | Picture * ▲ | Thematic fields * | Recommender | Reviewers | Submission date | |
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20 Dec 2021
![]() Quantifying growth perturbations over the fattening period in swine via mathematical modellingManuel Revilla, Guillaume Lenoir, Loïc Flatres-Grall, Rafael Muñoz-Tamayo, Nicolas C Friggens https://doi.org/10.1101/2020.10.22.349985An innovative modelling approach to enhance the quality of the quantification of pig resilience during the entire fattening period: Towards an individual pig resilience indexRecommended by Mohammed GagaouaThe identification of reliable estimates of growth potential and resilience over the fattening period in large populations is a challenge in actual swine breeding conditions. To overcome this drawback, the study by Revilla et al. 2021 in the frame of precision livestock farming aimed to propose an innovative modelling approach, in addition to previous studies from the same group (Revilla et al. 2019), to enhance the quality of the quantification of pig resilience during the entire fattening period. The authors developed a model that quantifies an “individual pig resilience indicator” based on longitudinal data, for instance body weight, recorded routinely by a commercially available automatic feeding system. Revilla and co-workers considered in their study two mainly commercialised pure pig breeds these being Piétrain including Piétrain Français NN Axiom line (Pie NN) free from halothane-sensitivity (ryanodine receptor gene, RYR1) and Piétrain Français Axiom line positive to this gene and Duroc. Therefore, the authors investigated the potential of improving resilience of swine livestock through inclusion for the first time of an “individual pig resilience indicator” in breeding objectives. A database of 13 093 boars (approximately 11.1 million of weightings) belonging to Pie (n= 5 841), Pie NN (n = 5 032) and Duroc (n= 2 220) finished under ad libitum feeding, high sanitary level and controlled temperature was used to develop robust models. The authors checked the three datasets (for each pig breed) independently to explore the variation and gaps (a data pre-treatment procedure) to ensure high quality data for the modelling approach. Then, they applied the Gompertz model and linear interpolation on body weight data to quantify individual deviations from the expected production, allowing the creation of the ABC index. For the modelling, the authors applied a two-step mathematical model approach by first establishing a theoretical growth curve of each animal, while the second step aimed to build the actual perturbed growth curve. The heritability of the index ranged from 0.03 to 0.04, with similar heritability between Piétrain and Duroc breeds. Moreover, moderate genetic relationships were computed between the proposed index and important phenotypic traits in swine production likely BF100: backfat thickness at 100kg; LD100: longissimus dorsi thickness at 100kg; ADG: average daily gain during control and FCR: feed conversion ratio. Developing models able to capture perturbations during the fattening period is a challenge in swine breeding industry. The model and methodology proposed by the authors in this innovative work (although preliminary and with low heritabilities) would help overcome such limit and facilitate a real implementation at large scale in pig breeding system. The modelling approach further offers an opportunity to develop a selection criterion to improve resilience in swine breeding conditions. To explore the full potential of this modelling approach, a larger database and other factors such as breed, behaviour and feeding behaviour of the animals, rearing practices, management and environment conditions, age… etc. are worthy to consider. In the future, more in depth measurements of behaviour that can be computed for example using computer vision should be desirable to increase the robustness of the proposed model. References Revilla, M., Friggens, N.C., Broudiscou, L.P., Lemonnier, G., Blanc, F., Ravon, L., Mercat, M.J., Billon, Y., Rogel-Gaillard, C., Le Floch, N. and Estellé, J. (2019). Towards the quantitative characterisation of piglets’ robustness to weaning: a modelling approach. Animal, 13(11), 2536-2546. https://doi.org/10.1017/S1751731119000843 Revilla M, Lenoir G, Flatres-Grall L, Muñoz-Tamayo R, Friggens NC (2021). Quantifying growth perturbations over the fattening period in swine via mathematical modelling. bioRxiv, 2020.10.22.349985, ver. 5 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2020.10.22.349985 | Quantifying growth perturbations over the fattening period in swine via mathematical modelling | Manuel Revilla, Guillaume Lenoir, Loïc Flatres-Grall, Rafael Muñoz-Tamayo, Nicolas C Friggens | <p>Background: Resilience can be defined as the capacity of animals to cope with short-term perturbations in their environment and return rapidly to their pre-challenge status. In a perspective of precision livestock farming, it is key to create i... | ![]() | Animal genetics, Animal health, Farming systems, Mathematical modelling, Precision livestock farming | Mohammed Gagaoua | 2020-10-26 11:47:08 | View | |
20 Aug 2024
![]() Goats who stare at video screens – assessing behavioural responses of goats towards images of familiar and unfamiliar con- and heterospecificsJana Deutsch, Steve Lebing, Anja Eggert, Christian Nawroth https://doi.org/10.31219/osf.io/d4nzkGazing behaviour as a tool to study goat cognitionRecommended by Isabelle Veissier based on reviews by Richard Bon and 1 anonymous reviewerMany cognitive studies use paradigms based on active decision-making, that require that animals are motivated to participate and interested in the reward (e.g. Rivas-Blanco et al., 2023). By contrast, looking time paradigms, in which the visual attention of an animal to a stimulus is measured, requires little training and little action from the subject, and can be used without reinforcement (e.g. Wilson et al., 2023). In this methodological paper, Jana Deutsch and her collaborators investigated the possibility of using a looking time paradigm to study perception and cognition in goats. The advantage of such a paradigm would be that it requires little training and can be used with no reinforcement. Goats were observed in front of two video screens presenting pictures of goats (familiar or not), of humans (familiar or not), or remaining white. The authors hypothesised that goats would pay more attention to pictures than to a white screen, would pay more attention to goats than to humans, and would discriminate familiar vs. unfamiliar beings. The goats had received previous positive contacts with the familiar humans. The goats were extensively habituated to the experimental set-up so that stress did not interfere in responses to testing. The stimuli were presented on the screens in a pseudorandomized and counterbalanced order. As hypothesised, goats looked longer at screen with pictures, and longer when the picture was that of another goat (familiar or not) than of a human being. Goats however did not seem to discriminate between familiar and unfamiliar being, or were equally motivated by the two types of beings. Ear postures were also recorded but did not show a relation with looking time and were not related to the type of picture shown on screens. Therefore, the authors argue that looking time but not ear posture is considered appropriate to test discrimination abilities or preferences in goats. More studies are needed to check if goats can differentiate familiar vs. unfamiliar beings. The experimental design is sound. The statistical analyses are rigorous and very relevant. The paper is clearly written. I recommend the manuscript for publication for its originality and its quality; In addition, the paper bring findings – that looking time is an adequate paradigm in goats to analyse how they pay attention to stimuli – that have potential impacts on further studies in animal cognition. References Deutsch, J., Lebing, S., Eggert, A., Nawroth, C. (2024). Goats who stare at video screens – assessing behavioural responses of goats towards images of familiar and unfamiliar con- and heterospecifics. OSF, ver.4 peer-reviewed and recommended by Peer Community In Animal Science. https://doi.org/10.31219/osf.io/d4nzk Rivas-Blanco, D., Monteiro, T., Virányi, Z., Range, F. (2024). Going back to “basics”: Harlow’s learning set task with wolves and dogs. Learning & Behavior. https://doi.org/10.3758/s13420-024-00631-6 Wilson, V. A. D., Bethell, E. J., Nawroth, C. (2023). The use of gaze to study cognition: limitations, solutions, and applications to animal welfare. Frontiers in Psychology, 14:1147278. https://doi.org/10.3389/fpsyg.2023.1147278
| Goats who stare at video screens – assessing behavioural responses of goats towards images of familiar and unfamiliar con- and heterospecifics | Jana Deutsch, Steve Lebing, Anja Eggert, Christian Nawroth | <p>Many cognitive paradigms rely on active decision-making, creating participation biases (e.g. subjects may lack motivation to participate in the training) and once-learned contingencies may bias the outcomes of subsequent similar tests. We here ... | ![]() | Animal behaviour , Animal cognition, Animal welfare, Small ruminants | Isabelle Veissier | 2023-12-05 13:07:18 | View | |
06 Sep 2019
![]() Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming.Ben Abdelkrim Ahmed, Puillet Laurence, Gomes Pierre, Martin Olivier https://doi.org/10.1101/661249Developing smart fitting algorithms to identify random perturbations in time-series dataRecommended by Luis TedeschiThe ability to adequately characterize the lactation curve of livestock is important not only to ensure proper nutrition of the lactating animal but, among many other benefits, it can assist in diagnosing the incidence of diseases, predicting the quantity of milk production, and comparing animals within the herd for managerial strategies such as culling. Eventually, such smart fitting algorithms can lead to improved genetic selection of more productive animals after genetic-unrelated noises are removed from the data, systematically. References [1] Johansson, I. (1961). Genetic Aspects of Dairy Cattle Breeding. University of Illinois Press, Urbana, IL. [2] Nelder, J. A. (1966). Inverse polynomials, a useful group of multi-factor response functions. Biometrics. 22 (1):128-141. doi: 10.2307/2528220 | Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming. | Ben Abdelkrim Ahmed, Puillet Laurence, Gomes Pierre, Martin Olivier | <p>Background Understanding the effects of environment on livestock provides valuable information on how farm animals express their production potential, and on their welfare. Ruminants are often confronted with perturbations that affect their per... | ![]() | Lactation biology , Mathematical modelling, Precision livestock farming | Luis Tedeschi | 2019-06-07 09:38:26 | View | |
06 Jan 2025
![]() Understanding the implementation of antimicrobial resistance policies in Vietnam: a multilayer analysis of the veterinary drug value chainChloé Bâtie, Nguyen Van Duy, Nguyen Thi Minh Khue, Marisa Peyre, Marion Bordier, Nguyen Thi Dien, Vu Dinh Ton, Flavie Goutard https://doi.org/10.1101/2024.06.27.24309573Bridging the gap in antibiotic regulation within Vietnam's livestock sectorRecommended by François MeurensThe reduction of antibiotic use in livestock production, for the different species, has become a critical focus in national action plans across many countries, underscoring the urgent need to tackle this issue to preserve public health and combat antibiotic resistance (Xu et al., 2022; Jacobsen et al., 2023; Bava et al., 2024). Among these efforts, Vietnam's ambitious 2017 livestock plan is notable for its comprehensive regulatory framework aimed at controlling antibiotic use. This framework includes a phased ban on prophylactic antibiotics in animal feed and requires mandatory prescriptions for antibiotic access. Despite these promising regulations, their actual implementation poses significant challenges, with limited data available on their practical application. A recent study led by Batie and collaborators attempts to fill this knowledge gap by examining how these regulations are understood, accepted, and applied by stakeholders in the veterinary drug value chain in both northern and southern Vietnam (Batie et al., 2024). The study employed an interesting iterative stakeholder mapping and analysis approach, organizing a focus group in Hanoi with 12 participants and conducting 39 in-depth semi-structured interviews with a diverse range of stakeholders. These included government authorities, national research bodies, international partners, and private sector representatives. The qualitative analysis aimed to map the veterinary drug value chain, assess stakeholders' technical and social capital regarding regulations, and identify key factors influencing regulatory compliance. This research convincingly unveiled a complex network of 30 stakeholder categories and identified ten crucial factors that affect the implementation of regulations. These factors include stakeholders’ perceptions and understanding of the regulations, the availability of technical guidance, economic conflicts of interest, management inconsistencies, and hurdles such as technical and financial constraints, informal distribution channels, international influence, and consumer demand for safety. Additionally, the collective drive to reduce antibiotic resistance emerged as an influential factor. The comprehensive analysis reveals a pressing insight: although Vietnam's regulatory measures are essential for reducing antibiotic usage, their effectiveness is compromised by barriers such as inadequate local stakeholder involvement and various resource limitations. The study emphasizes the necessity for deeper engagement of local stakeholders in developing and refining these regulations. Furthermore, incorporating innovations from small producers into mainstream practices could be vital in overcoming current challenges. Nonetheless, the study acknowledges several limitations. Most interviews were conducted online owing to the health crisis—a much-needed format for time and budget constraints, albeit with some drawbacks such as reduced direct observations and potential information loss (Namey et al., 2019). The sensitivity of the subject may have led participants to withhold their true opinions, although the researchers attempted to mitigate this bias by interviewing multiple respondents from each category and gathering diverse perspectives. Notably, the study struggled to engage informal stakeholders, which could have enriched the description of the informal value chain. Constraints of time and resources meant that only a single representative from some stakeholder categories was interviewed, suggesting that interviewing additional parties, such as another veterinary district station, might have clarified roles within the drug value chain. The stakeholder identification was initially influenced by the researchers’ familiarity with the Vietnamese context; however, the iterative process helped address this limitation by recruiting new participants based on existing participants' knowledge. Additionally, translation issues may have introduced misunderstandings, potentially leading to an incomplete representation of the veterinary drug value chain, which reflects the situation as of data collection in 2021. For Vietnam to meet its policy objectives and contribute to the global endeavor against antibiotic resistance, it is crucial to reconcile stakeholder discrepancies and promote collaborative innovation. By fostering an inclusive environment for all parties, Vietnam can not only enhance regulatory adherence but also strengthen its commitment to sustainable and responsible livestock farming practices. The study is thoughtfully designed and skillfully executed. Additionally, the authors have made further improvements based on feedback from the journal. Readers will find the article both informative and engaging, providing valuable insights. I highly recommend this original article on the regulatory framework for controlling antibiotic use in Vietnam's livestock production systems. References Batie, C., Duy, N. V., Khue, N. T. M., Peyre, M., Bordier, M., Dien, N. T., et al. (2024). Understanding the implementation of antimicrobial resistance policies in Vietnam: a multilayer analysis of the veterinary drug value chain. medRxiv, 2024.06.27.24309573, ver. 2 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2024.06.27.24309573 Bava, R., Castagna, F., Lupia, C., Poerio, G., Liguori, G., Lombardi, R., et al. (2024). Antimicrobial Resistance in Livestock: A Serious Threat to Public Health. Antibiotics 13, 551. https://doi.org/10.3390/antibiotics13060551 Jacobsen, A. B. J. E., Ogden, J., and Ekiri, A. B. (2023). Antimicrobial resistance interventions in the animal sector: scoping review. Front. Antibiot. 2. https://doi.org/10.3389/frabi.2023.1233698 Namey, E., Guest, G., O’Regan, A., Godwin, C. L., Taylor, J., and Martinez, A. (2019). How Does Mode of Qualitative Data Collection Affect Data and Cost? Findings from a Quasi-experimental Study. Field Methods. https://doi.org/10.1177/1525822X19886839 Xu, C., Kong, L., Gao, H., Cheng, X., and Wang, X. (2022). A Review of Current Bacterial Resistance to Antibiotics in Food Animals. Front Microbiol 13, 822689. https://doi.org/10.3389/fmicb.2022.822689
| Understanding the implementation of antimicrobial resistance policies in Vietnam: a multilayer analysis of the veterinary drug value chain | Chloé Bâtie, Nguyen Van Duy, Nguyen Thi Minh Khue, Marisa Peyre, Marion Bordier, Nguyen Thi Dien, Vu Dinh Ton, Flavie Goutard | <p>Reducing antibiotic use in livestock production has been a target for national action plans worldwide. The Vietnamese livestock plan issued in 2017 has, among other objectives, strengthened the regulatory framework for antibiotic use. While a p... | ![]() | Animal epidemiology, Animal health, Farming systems, Veterinary epidemiology , Veterinary science | François Meurens | 2024-07-15 10:47:33 | View |
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