Azgp1 knockout changes mammary gland, adipose tissue and liver gene expression in lactating mice

Session 4: Nutrition to improve milk and meat qualityNational audienc

Azgp1 knockout changes mammary gland, adipose tissue and liver gene expression in lactating mice

Session 4: Nutrition to improve milk and meat qualityNational audienc

Comparison of the Potential Abilities of Three Spectroscopy Methods: Near-Infrared, Mid-Infrared, and Molecular Fluorescence, to Predict Carotenoid, Vitamin and Fatty Acid Contents in Cow Milk

International audienceThe objective of this work is to compare the ability of three spectroscopy techniques: molecular fluorescence, near-infrared (NIR), and mid-infrared with attenuated total reflectance (MIR-ATR) spectroscopy to predict the concentrations of 8 carotenoids, 6 vitamins and 22 fatty acids (FA) in cow’s milk. A dataset was built through the analysis of 242 frozen milk samples from different experiments. The milk compounds were analysed using reference methods and by NIR, MIR-ATR, and fluorescence to establish different predictive models. NIR spectroscopy allowed for better prediction of cis9-β-carotene, β-cryptoxanthin and the sum of carotenoids than the other techniques, with a coefficient of cross-validation in calibration (R2CV) > 0.60 and a coefficient of determination in validation (R2V) > 0.50. Their standard errors of prediction (SEP) were equal to 0.01, except for the sum of carotenoids (SEP = 0.15). However, MIR-ATR and fluorescence seem usable for the prediction of lutein and all-trans-β-carotene, respectively. These three spectroscopy methods did not allow us to predict (R2CV < 0.30) vitamin contents except, for vitamin A (the best R²CV = 0.65 with NIR and SEP = 0.15) and α-tocopherol (the best R²CV = 0.56 with MIR-ATR and SEP = 0.41), but all R²V were <0.30. NIR spectroscopy yielded the best prediction of the selected milk FA

Importance of interindividual interactions in eco‐evolutionary population dynamics: The rise of demo‐genetic agent‐based models

Corrigendum on: Volume 16, Issue 1, Evolutionary Applications, pages: 189-189, First Published online: January 18, 2023.International audienceThe study of eco-evolutionary dynamics, that is of the intertwinning between ecologi- cal and evolutionary processes when they occur at comparable time scales, is of grow- ing interest in the current context of global change. However, many eco-evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco-evolutionary framework: the demo- genetic agent-based models (DG-ABMs). Being demo-genetic, DG-ABMs consider the feedback loop between ecological and evolutionary processes. Being agent-based, DG-ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG-ABMs to take into account the genetic heterogeneity—that affects individual decisions/traits related to local and instantaneous conditions—differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco-evolutionary feed- back loops. Based on the review of studies employing DG-ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG-ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco-evolutionary processes on interindividual interactions and population dynamics, DG-ABMs are also effective prospective and decision support tools to evaluate the short- and long-term evolutionary costs and benefits of management strategies and to assess potential trade-offs. Finally, we provide a list of the recent practical advances of the ABM com- munity that should facilitate the development of DG-ABMs

Infrared spectroscopic methods for the discrimination of cow milk according to the feeding systems, cow breed and altitude of the dairy farms

Bulk milk samples were collected from four French regions to study the potential capability of mid-infrared (MIR) and near-infrared (NIR) spectroscopy data to differentiate milk according to the feeding system, breed of cow and altitude of the farm. The MIR method demonstrated an excellent capability to distinguish milk from hay- and pasture-based systems and those from maize silage- and pasture-based systems. The MIR method did not exhibit the same capability concerning the discrimination of milk from hay- and maize silage-based systems. A similar trend was observed with the NIR method but with lower efficiency. The two infrared methods did not satisfactorily discriminate milk from different cow breeds. Significant differences (P < 0.05) between methods in the proportion of correctly classified samples according to the feeding system and breed were reported, whereas no significant differences were found between the methods concerning the discrimination of lowland versus upland samples

Importance of interindividual interactions in eco‐evolutionary population dynamics: The rise of demo‐genetic agent‐based models

International audienceThe study of eco-evolutionary dynamics, that is of the intertwinning between ecologi- cal and evolutionary processes when they occur at comparable time scales, is of grow- ing interest in the current context of global change. However, many eco-evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco-evolutionary framework: the demo- genetic agent-based models (DG-ABMs). Being demo-genetic, DG-ABMs consider the feedback loop between ecological and evolutionary processes. Being agent-based, DG-ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG-ABMs to take into account the genetic heterogeneity—that affects individual decisions/traits related to local and instantaneous conditions—differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco-evolutionary feed- back loops. Based on the review of studies employing DG-ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG-ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco-evolutionary processes on interindividual interactions and population dynamics, DG-ABMs are also effective prospective and decision support tools to evaluate the short- and long-term evolutionary costs and benefits of management strategies and to assess potential trade-offs. Finally, we provide a list of the recent practical advances of the ABM com- munity that should facilitate the development of DG-ABMs