To limit the use of antibiotics in the few days after hatching, it is necessary to improve the robustness of chicks during the early post-hatch period. This can be achieved by ensuring immediate access to feeds, optimizing the implantation and maturation of the microbiota and immune system of each chick, and minimizing exposure of stressors such as transportation. The study conducted by Guilloteau and colleagues (2024) compared the performance and health of chicks raised in conventional hatching systems with those raised in on-farm hatching systems. The authors showed that both systems yielded similar hatching percentage of eggs. Chicks from on-farm hatching systems exhibited higher body weights during the post-hatch period compared to those from conventional hatching, whereas health parameters were not affected by the system. An originality of the study was the examination of the benefits of the presence of an adult hen in hatching systems. The effects on chick traits were interpreted in relation to the hen behavior at hatching and a classification according to maternal or agonistic activities towards the chicks. However, the experimental design did not allow to make statistical correlations between hen behavior pattern and chick traits. Importantly, the presence of a hen decreased the hatching percentage, and this was likely associated with hen aggressiveness in the pen. The presence of the hen deteriorated the quality scores of the chicks in the on-farm hatching system, and increased mortality of chicks at hatching, negatively impacting chick weight gain and feed efficiency during the few days after hatching in both conventional and on-farm hatching systems. Thereafter, the effect of the presence of a hen on chick body weight was different according to the sex of the chicks and the type of hatching system. The presence of a hen did not reduce the parasitic load of the chicks nor improved clinical signs. No specific characterization of the fecal microbiota of the chicks was conducted, preventing the testing whether or not the presence of the hen affected the early implantation and maturation of the chick microbiome. Altogether, the data indicate that on-farm hatching systems are at least equivalent (in terms of health traits, feed efficiency) or even favorable (for faster growth in the early period after hatching) for chicks. Training the hens (considered as foster adults) to the presence of eggs and chicks or selecting hens according to specific activity behavioral patterns could be ways to establish better interactions between hens and chicks. Although the number and type of environmental stressors tested in the experiment differ from those in commercial farms, the article opens new perspectives for alternative hatching and farming practices.

Reference

Guilloteau LA, Bertin A, Crochet S, Bagnard C, Hondelatte A, Ravon L, Schouler C, Germain K, Collin A (2024) On-farm hatching and contact with adult hen post hatch induce sex-dependent effects on performance, health and robustness in broiler chickens. bioRxiv, 2023.05.17.541117. ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2023.05.17.541117. 

A correct execution of feeding plan for growing rabbit decreases the possibility of post-weaning digestive disorders, thus enhancing the feed efficiency in the animals. However, a limitation of feed daily quantity is required between 10 weeks of age and the first artificial insemination. This limitation causes energy deficiency with a consequent reduction in fertility. Beauvais et al. (2022) studied the impact of feed restriction strategies in female rabbits. Four feed restriction strategies were applied in two distinct periods (post-weaning and puberty) and evaluated by different physiological parameters (growth rate, metabolic profiles, reproductive parameters and mammary gland development). In the first part of the paper, the authors evaluated the association between weight slopes and feeding strategies in the late post-weaning and peripartum period in the four groups. As revealed by the authors, a significant difference was observed during the late post-weaning period, which remained significant between the pubertal and fattening phases. Probably these differences are related to the restriction feeding pattern. The results indicated that restrictive feeding changes in the first step of post-weaning period is associated with a significant difference in body weight. This difference occurs from the third week of diet, highlighting the high sensitivity of growing rabbit to nutrition during the post-weaning period.

In the second part of the paper, the authors evaluated the expression of genes involved in the lipid metabolism. During the mid-pregnancy, was revealed a significant higher expression of lipogenic genes, which may be considered as useful markers for the mammary epithelial development in less restrictive strategies during early life period.

The results proposed by Beauvais et al. (2022) enlighten the important role played by the feeding conditions of young female rabbits in the early life rearing. In particular, this activity provides specific recommendations for optimizing lactation and thus preventing neonatal mortality of the offspring. Moreover, the authors provide indications about the effect of feeding strategies on the mammary development and gene expression with absolute consequences on the development of offspring. Mammary lipid metabolism affects the milk profile and therefore the growth performance of the young animals.

Reference

Hue-Beauvais C, Bebin K, Robert R, Gardan-Salmon D, Maupin M, Brun N, Aujean E, Jaffrezic F, Simon S, Charlier M, Le Provost F (2022). Impact of pre-breeding feeding practices on rabbit mammary gland development at mid-pregnancy. biorXiv, 2022.01.17.476562, ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2022.01.17.476562 

In genetic selection, simplistic model of single-trait selection is usually considered, and the response to such approach is estimated using simple models. In practice, however, plant and animal breeders always deal with the selection of several traits, hence making the selection process very complex. Therefore, the simultaneous genetic improvement of several traits has always been one of the goals of livestock, including poultry breeding (Falconer, 1972). Studies that examine the indirect effects of selection on economic traits are eagerly awaited. In this context, the results of the study by Bédère et al., (2023) gives new insights about phenotypic and genotypic relationships between body reserves traits in laying hens. The authors aimed to propose novel data about the genetic architecture of traits related to body fat by measuring a series of phenotypic traits with relatively an easy approach. The authors further aimed to test and validate the phenotyping of backfat thickness as an indicator of the overall fatness of laying hens. Thus, the study allowed providing new evidence regarding the genetic determination of the backfat trait in chicken breeds.

The authors first estimated the effect of selection on the residual feed intake (trait x) on the trait of body reserves (trait y). In fact, divergent selection experiments are a fundamental research tool that allow revealing significant amount of data related to the possible span of genetic improvement for traits of interest. Consequently, by analyzing data from a divergent selection experiment, associations have been estimated between a number of feed-dependent traits that have practical use for chicken breeders. Estimation of the correlations between traits is under question in terms of the theory of genetics and their application in multi-trait selection. As a major finding of the study, the observation of a bimodal distribution of backfat in both lines and the heterogeneity of the variances between families allowed suggesting a possible major gene, which could be investigated in future studies using for instance quantitative genetics. Body composition is continually studied in broilers chicken, but this aspect of chicken genetic is more detailed in laying hens.

The current findings are worthy to validate using several approaches. In fact, one of the limitations of the study can be related to other statistical models that can be built. For example, the study revealed high correlations between egg production and body weight, thus body weight could be considered as a covariate in regression models. Moreover, the principal trait of selection (based on the residual feed intake) could be considered. 

References:

Falconer, D. S. (1972). Introduction to Quantitative Genetics. Publisher: Ronald Press Company. pp 365.

Bédère, N., Dupont, J., Baumard, Y., Staub, C., Gourichon, D., Elleboudt, F., Le Roy, P., Zerjal, T. (2023).  Genetic background of body reserves in laying hens through backfat thickness phenotyping. HAL ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://hal.inrae.fr/hal-04172576 

The 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 

Epidemics such as PRRSv-like virus in pig farms has tremendous impact on the competitiveness of swine production. However, its control requires an understanding of the complex interaction between pathogen transmission, disease impact, population dynamics and management. By using mechanistic epidemiological modelling, Sicard et al. (2023) open up a very interesting field of possibilities. This article describes work aimed at assessing the consequences of infections, taking into account the interaction between clinical outcomes and population dynamics. This study shows how this interaction can influence transmission dynamics at the herd level. It highlights the need to further explore this direction, integrating both disease impacts in breeding practices and structural changes in population dynamics, such as pig crossbreeding and grouping methodologies.
The provision of a new tool making it possible to model herd management practices and the transmission of a virus, such as PRRS, in time and space is a major contribution to understanding the dynamics of this category of diseases. It opens up the possibility of being able to represent specific herd structures and evaluate transmission dynamics using real data. This work improves our understanding of disease spread across herds, taking into account herd management.

Reference

Sicard V, Picault S, Andraud M (2023) Pig herd management and infection transmission dynamics: a challenge for modellers. bioRxiv, 2023.05.17.541128. ver. 2 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2023.05.17.541128