The dairy sector is facing an historical period of high milk demand. However, increasing feed prices continually reduces the economic margins for farms. Managerial strategies to increase economical and technical awareness of animal performance, support the decision chain and optimize the use of production inputs are increasingly necessary, especially in goat farms with intensive production systems. Among the scientific goals, there is a particular emphasis on increasing knowledge about nutrition partitioning between milk production and body reserves — a topic that not easily addressed by nutritional models, limiting the attempts at production forecasting. 

The paper by Gafsi et al (2024) presents an interesting approach to studying phenotypic traits and trajectories of goat performance. It assesses the diversity of phenotypic trajectories reflecting functions such as milk production, body weight and condition score. This approaches aims to describe, understand and explore the interactions among biological functions and potential trade-offs of phenotypic trajectories across current and successive lactations. The work significantly contributes to the literature, particularly because previous descriptions of lactation curves relied primarily on mathematical outputs lacking information about the relationship among physiologically related variables. 

The analysis retrieved data from about 1500 goats over more than 20 years and was conducted with a multiscale approach. Data were fitted considering different types of models, including description of perturbations for lactation curves and with multiphasic models for the body weight and body condition score. Synthetic indicators were then estimated with a multivariate approach to define fitted trajectories and changes in performance. 

The association among performance directly refers to nutrient partitioning, and the adaptive response of individual animals refers to nutrient availability and their aptitude to direct the metabolic effort toward milk production. In fact, the research shows that trajectories from the first lactation were often maintained in sequent ones. Positive associations among milk curve perturbations and the individual aptitude to drive nutrients to body reserves were also observed.

The multiscale approach developed in the paper may provide original insights both for describing  animal performance and for ranking individual animals within farm groups. Practically, the method could inform the development of algorithms to support culling policies and individual animal assessments. Additionally, the data are available to the scientific community  for further research and applications. 

I recommend this paper as a methodological example with high replicable approaches for both goats and other dairy species, with significant applicative opportunities at the farm level.

Reference

Gafsi N, Martin O, Bidan F, Grimard B, Puillet L (2024) Diversity of performance patterns in dairy goats: multi-scale analysis of the lactation curves of milk yield, body condition score and body weight. Zenodo. 10101318. ver.3 peer-reviewed and recommended by Peer Community In Animal Science. https://doi.org/10.5281/zenodo.10101318

The predominant form of agriculture in sub-Saharan Africa is mixed crop and livestock production, typically in extensive systems characterised by low productivity and little input (Tui et al., 2021). Such extensive systems experience many challenges, including access to rangeland and other sources of livestock feed, loss of soil quality, increasingly unpredictable climate but also operational constraints such as access to markets and veterinary care.

The work by Gobvu and collaborators (2025) addresses livestock farming sustainability specifically in the context of a Transfrontier Conservation Area (TFCA). A TFCA is defined as part of an ecological region reaching across boundaries of two or more countries and in which there are protected areas as well as resource use areas. TFCAs are founded to facilitate collective management of resources for the benefit of biodiversity as well as socio-economic development (SADC, 2025).

Livestock farming in TFCAs face additional challenges arising from the tension between biodiversity protection and resource use, such as wildlife predation on livestock, competition between livestock and wildlife for feed and water as well as spread of infections between livestock and wild animals (Matseketsa et al., 2019; Caron et al., 2013; Cumming, 2011).

The paper reports a study that was part of a larger project (EU-ProSuLi project, Caron et al.,  2022) aiming at promoting local development and well-being of residents in the Great Limpopo TFCA, with focus on the Sengwe Communal Area in Zimbabwe. The specific aim was to test a methodology for identifying interventions that are aligned with the needs of the local stakeholders (demand-driven interventions. Anticipatory scenario building in the context of workshops was used in combination with individual questionnaires.

Community representatives (n=31) were purposefully selected for their expected ability to act as knowledge brokers. A team of 10 facilitators supported the discussion through plenary and group work sessions. The participants were asked to identify factors of change with impact on local community livelihood, and subsequently to vote to select the most influential factors. Different future states for the year 2038, resulting from the impact of the factors of change, were discussed. In a follow-up workshop, participants were asked to propose activities that would support the development towards the most desirable scenario. In addition, a questionnaire was distributed through semi-structured/structured interviews to 126 households in nine villages.

Results were largely similar and complementary between the two approaches. Preferred interventions were: restocking herds with locally adapted breeds, training in livestock management, marketing support, feed development and value addition, loan schemes for investment in livestock production and support for animal health interventions to reduce the heavy disease burden. Whereas the participatory process is time consuming and requires considerable human resources, it is important to ensure locally relevant interventions are chosen, and it is in itself part of the process towards successful implementation of these interventions.

The study is thoughtfully designed based on previous work by the authors. The paper is well written and has been further improved through the reviewer feedback and revision process.

References

Caron, A., Miguel, E., Gomo, C., Makaya, P., Pfukenyi, D.M., Foggin, C., Hove, T. and de Garine-Wichatitsky, M., 2013. Relationship between burden of infection in ungulate populations and wildlife/livestock interfaces. Epidemiology & Infection, 141 (7), pp.1522-1535. https://doi.org/10.1017/S0950268813000204

Caron, A., Mugabe, P., Bourgeois, R., Delay, E., Bitu, F., Ducrot, R., Fafetine, J., Fynn, R., Guerbois, C., Motsholapheko, M. and Daré, W., 2022. Social-ecological System Health in  Transfrontier Conservation Areas to Promote the Coexistence Between People and Nature. One Health Cases. https://doi.org/10.1079/onehealthcases.2022.0005 

Cumming, D. H. M. 2011. Constraints to conservation and development success at the wildlife-livestock-human interface in southern African transfrontier conservation areas: a preliminary review. Wildlife Conservation Society, New York.  http://www.wcs-ahead.org/workinggrps_kaza.html

Gobvu, V. Ncube, S. Imbayarwo-Chikosi, V.E., Bourgeois, R. Mugabe, P.H. and Caron A. 2025. Preferred livestock interventions for small-scale farmers in the Great Limpopo Transfrontier Conservation Area: a demand-driven and participatory approach. HAL, ver.5 peer-reviewed and recommended by PCI Animal Science. https://hal.science/hal-04060712

Matseketsa, G., Muboko, N., Gandiwa, E., Kombora, D.M. and Chibememe, G., 2019. An assessment of human-wildlife conflicts in local communities bordering the western part of Save Valley Conservancy, Zimbabwe. Global Ecology and Conservation, 20, p.e00737. https://doi.org/10.1016/j.gecco.2019.e00737 

Tui, S.H.K., Descheemaeker, K., Valdivia, R.O., Masikati, P., Sisito, G., Moyo, E.N., Crespo, O., Ruane, A.C. and Rosenzweig, C., 2021. Climate change impacts and adaptation for dryland farming systems in Zimbabwe: a stakeholder-driven integrated multi-model assessment. Climatic Change, 168 (1-2), p.10. https://doi.org/10.1007/s10584-021-03151-8 

South African Development Community. 2025. Transfrontier Conservation Areas.  . Consulted 7 January 2025. https://www.sadc.int/pillars/transfrontier-conservation-areas

Farm animals differ in their ability to respond to the many environmental challenges they face. Such challenges include infectious diseases, metabolic diseases resulting from inadequate coverage of dietary needs, as well as the diverse consequences of climate change. Various concepts exist to characterise the responses of animals to different types of challenges. This article by Friggens et al. (2022) focuses on resilience, providing a conceptual definition and proposing a method to quantify resilience in dairy cows.

The first part of the paper provides a definition of resilience and highlights its differences and relations with the related concepts of robustness, and, to a lesser extent, resistance and tolerance. In essence, resilience is the ability of an animal to bounce back quickly after a challenge of limited duration. On the other hand, robustness is the ability of an animal to cope with conditions that are overall unfavourable. From these conceptual and intuitive definitions, there are several difficulties precluding the design of concrete methods to measure resilience. First, there is some degree of overlap between the concepts of resilience, robustness, resistance and tolerance. Secondly, resilience is a multidimensional concept whereby resilience to a given perturbation does not imply resilience to other types of perturbation, e.g. resilience to a challenge by a specific pathogen does not imply resilience to a nutritional challenge. A further difficulty in the measure of resilience is the fact that different animals may be exposed to challenges that are different in nature and in number. The authors argue that although resilience cannot be measured directly (it should be seen as a latent construct), it is possible to quantify it indirectly through its consequences.

In the second part of the paper, the authors propose a method to quantify resilience of individual dairy cows. The method is based on the premise that resilient animals should be kept longer in their herd than non-resilient animals. The main criterion in the evaluation is therefore the ability of cows to re-calve. Each cow that is calving receives a certain number of points, to  which, in each lactation, bonus points are added for higher milk production and penalty points are removed for each insemination after the first one, for each disease event and for each day of calving interval above some herd specific value. Therefore, cows have a resilience score in each lactation. They also have a lifetime resilience score obtained by summing the scores for all the lactations, that gets bigger as the cow has more calves, and that also takes the age at first calving into account. In a previous study, Adriaens et al. (2020) showed that higher resilience scores were associated with fewer drops in milk yield and more stable activity dynamics.

Starting from theoretical considerations on the notion of resilience, this paper describes a concrete method to quantify animal-level resilience on farm. Such quantification will be useful for breeding and culling decisions. Finally, the general framework to design resilience measures that is presented will be useful to researchers working on the quantification of farm animal resilience using new methods and data sources.

References

Adriaens I, Friggens NC, Ouweltjes W, Scott H, Aernouts B and Statham J 2020. Productive life span and resilience rank can be predicted from on-farm first-parity sensor time series but not using a common equation,  across farms. Journal of Dairy Science 103, 7155-7171.https://doi.org/10.3168/jds.2019-17826

Friggens, N.C. , Adriaens, I., Boré, R., Cozzi, G., Jurquet, J., Kamphuis, C., Leiber, F., Lora, I., Sakowski, T., Statham, J., De Haas, Y. (2022). Resilience: reference measures based on longer-term consequences are needed to unlock the potential of precision livestock farming technologies for quantifying this trait. Zenodo, 5215797, ver. 5 peer-reviewed and recommended by Peer community in Animal Science. https://dx.doi.org/10.5281/zenodo.5215797

Using on-farm sensors in dairy farming is known to help decision makings and farmer objectives in the monitoring and potential improvement of animal behaviour, health and production performance. However, in indoor positioning systems, data interpretation is complicated by the inaccuracy and noise in the time series, missing data caused not only by sensor failure or the harsh and changing farm environments in which they operate, but also by the animals' specific physiology itself. Thus, working with spatial data has proven challenging mainly due to their enormous heteroscedasticity, which depends on multiple factors such as the cow, the time of the day, the behaviour, factors interfering with the sensor system, etc., for which we cannot account mathematically. Applying purely black-box approaches generally results in insufficient robustness, interpretability and generalisability. 

With this work, Adriaens et al. (2022) developed a relatively simple and new methodology to monitor the lying behaviour of dairy cows by using noisy spatial positioning data, while combining time-series segmentation based on statistical changepoints and a machine learning classification algorithm. The two-step methodology identifies lying behaviour using an ultra-wide band indoor positioning system. Getting-up or lying-down events were indicated by the accelerometers. Overall classification and lying behaviour prediction performance was above 91% in independent test sets, with a very high consistency across cow-days. The robustness of the algorithm was demonstrated by the fact that both the cow identity-based split and the time-based split performed equally well. 

The article represents an original contribution for advancing the state of the art in the automated quantification of lying behaviour in dairy cows, aiming to monitor health or animal welfare issues. Future research must be considered however to validate the performance of the model when using different position-measuring technologies, in other farm settings and over a longer period of time.

Reference

Adriaens I, Ouweltjes W, Pastell M, Ellen E, Kamphuis C. 2022. Detecting dairy cows' lying behaviour using noisy 3D ultra-wide band positioning data. Zenodo, 6627251, ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.5281/zenodo.6627251 

One of the key questions in pig industry nowadays is how health and performance of piglets can be improved by sow nutrition and milk composition. The levels of dietary fibers in sow’s gestation diet have positive effects observed on the litters. However, the composition of dietary fibers and the organization of polysaccharides within the cell wall in the different plants determine their physicochemical properties and, thereby, their behaviour in the gut of the sows and the subsequent physiological response of the animals. Hemicelluloses are polysaccharides constituents of the cell walls of plants, which are fermented in the gut to produce volatile fatty acids (VFA). These VFA can serve as energy source for milk synthesis and can thereby influence the development of suckling piglets. Palumbo and colleagues (1) proposed an original experimental design to compare diets with similar fiber contents but different hemicellulose levels, thanks to varying the sources of fibers used in the dietary formulations. Effects were studied on performance and health of lactating sows and their piglets during suckling period and until post-weaning. The dietary treatments had no effect on the total number of piglets weaned and, consequently, on litter weight at weaning. Milk yield was not influenced by the dietary treatments, but milk composition (lactose content, copper and threonine proportions) was affected by the level of hemicellulose in the maternal diets. With a decreasing hemicellulose level in sow diet, milk lactose content linearly decreased, whereas the copper and threonine contents linearly increased. There was no effect on piglet performance during the lactation period. During the second week of post-weaning, a quadratic increase in the incidence of diarrhoea and the number of days with diarrhoea for suckling piglets was observed with decreasing hemicellulose level in diet. Interestingly, the observed effects were partly different for piglets born with a low body weight. Indeed, there was a linear decrease in the incidence of diarrhoea and days with diarrhoea with decreased hemicellulose level in the maternal diet for those piglets, together with increased growth performance from birth to two weeks post-weaning. The authors postulated that the improved growth performance and the lower incidence of diarrhoea observed in small piglets during post-weaning period may be related to the increased abundance of threonine and copper and increased concentration of total VFA in milk of sows fed a diet with reduced hemicellulose levels. This study confirms the importance of early-life interventions to improve the post-weaning development and health of this sub-population of piglets.

Reference

(1) Palumbo F, Bee G, Trevisi P, and Girard M. (2022). Decreasing the level of hemicelluloses in sow's lactation diet affects the milk composition and post-weaning performance of low birthweight piglets. agriRxiv 2022.00116, ver 4 (R3), peer-reviewed and recommended by PCI Animal Science.   https://doi.org/10.31220/agriRxiv.2022.00116