The growing interest in rotational crossbreeding in Western countries is due to its potential to improve reproductive and health performances of cows. Although a large amount of research focuses on assessing crossbred cows’ performances, how to manage the transition from purebred to rotational crossbred herds is under-explored. Based on a retrospective analysis of French dairy herd case studies, we aimed to identify and characterise technical pathways to make such a transition. In 2018, we performed semi-directive interviews on 26 commercial dairy farms. Data were collected to describe changes in breeding, replacement and culling management practices from the first crossbred mating with purebred cows to the management of a mainly crossbred herd in 2018. Based on a multivariate analysis, we identified two main guidelines structuring technical pathways to move towards rotational crossbred herds: (i) the depth and scale of change (i.e. farm v. herd) associated with the introduction of rotational crossbreeding in the whole-farm dynamics and (ii) the changes in herd replacement and breeding practices to adapt to the evolution of herd demographics induced by the evolution of the dairy crossbred mating rate over time (high from the beginning v. distributed over time). Hierarchical clustering discriminated three groups of farmers differing in their technical pathway to move towards a rotational crossbred herd. In pathway 1, farmers customised one or several rotational crossbreeding schemes to support whole-farm transition towards an organic or grass-based system. Once the scheme stabilised, they quickly implemented it and had to readjust replacement and culling practices to regulate imbalance in herd demographics induced by the improvement in cow fertility. In pathway 2, farmers also customised one or several rotational crossbreeding schemes to support whole-farm redesign but they implemented it more gradually in the herd, which induced no major imbalance in herd demographics. In pathway 3, farmers predefined a relatively well-known rotational crossbreeding scheme to correct fertility issues of purebred cows without any changes at the farm level. They implemented it quickly from the beginning and had to adapt herd replacement and culling to regulate imbalance in herd demographics induced by the improvement in cow fertility. These first empirical evidences on how dairy farmers manage the transition from a purebred to rotational crossbred herd provide original scientific and operational contributions.

Worldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to change in the hours prior to parturition, for example, less time ruminating and eating and increased activity level and tail-raise events. These behaviours can be monitored non-invasively using animal-mounted sensors. Thus, behavioural traits are ideal variables for the prediction of calving. This study explored the potential of two sensor technologies for their capabilities in predicting when calf expulsion should be expected. Two trials were conducted at separate locations: (i) beef cows (n = 144) and (ii) dairy cows (n = 110). Two sensors were deployed on each cow: (1) Afimilk Silent Herdsman (SHM) collars monitoring time spent ruminating (RUM), eating (EAT) and the relative activity level (ACT) of the cow, and (2) tail-mounted Axivity accelerometers to detect tail-raise events (TAIL). The exact time the calf was expelled from the cow was determined by viewing closed-circuit television camera footage. Machine learning random forest algorithms were developed to predict when calf expulsion should be expected using single-sensor variables and by integrating multiple-sensor data-streams. The performance of the models was tested using the Matthew’s correlation coefficient (MCC), the area under the curve, and the sensitivity and specificity of predictions. The TAIL model was slightly better at predicting calving within a 5-h window for beef cows (MCC = 0.31) than for dairy cows (MCC = 0.29). The TAIL + RUM + EAT models were equally as good at predicting calving within a 5-h window for beef and dairy cows (MCC = 0.32 for both models). Combining data-streams from SHM and tail sensors did not substantially improve model performance over tail sensors alone; therefore, hour-by-hour algorithms for the prediction of time of calf expulsion were developed using tail sensor data. Optimal classification occurred at 2 h prior to calving for both beef (MCC = 0.29) and dairy cows (MCC = 0.25). This study showed that tail sensors alone are adequate for the prediction of parturition and that the optimal time for prediction is 2 h before expulsion of the calf.

Brominated flame retardants (BFR) are primarily used as flame retardant additives in insulating materials. These lipophilic compounds can bioaccumulate in animal tissues, leading to human exposure via food ingestion. Although their concentration in food is not yet regulated, several of these products are recognised as persistent organic pollutants; they are thought to act as endocrine disruptors. The present study aimed to characterise the occurrence of two families of BFRs (hexabromocyclododecane (HBCDD) and polybrominated diphenyl ethers (PBDE)) in hen eggs and broiler or pig meat in relation to their rearing environments. Epidemiological studies were carried out on 60 hen egg farms (34 without an open-air range, 26 free-range), 57 broiler farms (27 without an open-air range, 30 free-range) and 42 pig farms without an open-air range in France from 2013 to 2015. For each farm, composite samples from either 12 eggs, five broiler pectoral muscles or three pig tenderloins were obtained. Eight PBDE congeners and three HBCDD stereoisomers were quantified in product fat using gas chromatography–high-resolution mass spectrometry, or high-performance liquid chromatography–tandem mass spectrometry, respectively. The frequencies of PBDE detection were 28% for eggs (median concentration 0.278 ng/g fat), 72% for broiler muscle (0.392 ng/g fat) and 49% for pig muscle (0.403 ng/g fat). At least one HBCDD stereoisomer was detected in 17% of eggs (0.526 ng/g fat), 46% of broiler muscle (0.799 ng/g fat) and 36% of pig muscle (0.616 ng/g fat). Results were similar in concentration to those obtained in French surveillance surveys from 2012 to 2016. Nevertheless, the contamination of free-range eggs and broilers was found to be more frequent than that of conventional ones, suggesting that access to an open-air range could be an additional source of exposure to BFRs for animals. However, the concentration of BFRs in all products remained generally very low. No direct relationship could be established between the occurrence of BFRs in eggs and meat and the characteristics of farm buildings (age, building materials). The potential presence of BFRs in insulating materials is not likely to constitute a significant source of animal exposure as long as the animals do not have direct access to these materials.

The fatty acid composition of chicken’s meat is largely influenced by dietary lipids, which are often used as supplements to increase dietary caloric density. The underlying key metabolites and pathways influenced by dietary oils remain poorly known in chickens. The objective of this study was to explore the underlying metabolic mechanisms of how diets supplemented with mixed or a single oil with distinct fatty acid composition influence the fatty acid profile in breast muscle of Qingyuan chickens. Birds were fed a corn-soybean meal diet supplemented with either soybean oil (control, CON) or equal amounts of mixed edible oils (MEO; soybean oil : lard : fish oil : coconut oil = 1 : 1 : 0.5 : 0.5) from 1 to 120 days of age. Growth performance and fatty acid composition of muscle lipids were analysed. LC-MS was applied to investigate the effects of CON v. MEO diets on lipid-related metabolites in the muscle of chickens at day 120. Compared with the CON diet, chickens fed the MEO diet had a lower feed conversion ratio (P < 0.05), higher proportions of lauric acid (C12:0), myristic acid (C14:0), palmitoleic acid (C16:1n-7), oleic acid (C18:1n-9), EPA (C20:5n-3) and DHA (C22:6n-3), and a lower linoleic acid (C18:2n-6) content in breast muscle (P < 0.05). Muscle metabolome profiling showed that the most differentially abundant metabolites are phospholipids, including phosphatidylcholines (PC) and phosphatidylethanolamines (PE), which enriched the glycerophospholipid metabolism (P < 0.05). These key differentially abundant metabolites – PC (14:0/20:4), PC (18:1/14:1), PC (18:0/14:1), PC (18:0/18:4), PC (20:0/18:4), PE (22:0/P-16:0), PE (24:0/20:5), PE (22:2/P-18:1), PE (24:0/18:4) – were closely associated with the contents of C12:0, C14:0, DHA and C18:2n-6 in muscle lipids (P < 0.05). The content of glutathione metabolite was higher with MEO than CON diet (P < 0.05). Based on these results, it can be concluded that the diet supplemented with MEO reduced the feed conversion ratio, enriched the content of n-3 fatty acids and modified the related metabolites (including PC, PE and glutathione) in breast muscle of chickens.