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Heat stress impacts ruminant livestock production on varied levels in this alarming climate breakdown scenario. The drastic effects of the global climate change-associated heat stress in ruminant livestock demands constructive evaluation of animal performance bordering on effective monitoring systems. In this climate-smart digital age, adoption of advanced and developing Artificial Intelligence (AI) technologies is gaining traction for efficient heat stress management. AI has widely penetrated the climate sensitive ruminant livestock sector due to its promising and plausible scope in assessing production risks and the climate resilience of ruminant livestock. Significant improvement has been achieved alongside the adoption of novel AI algorithms to evaluate the performance of ruminant livestock. These AI-powered tools have the robustness and competence to expand the evaluation of animal performance and help in minimising the production losses associated with heat stress in ruminant livestock. Advanced heat stress management through automated monitoring of heat stress in ruminant livestock based on behaviour, physiology and animal health responses have been widely accepted due to the evolution of technologies like machine learning (ML), neural networks and deep learning (DL). The AI-enabled tools involving automated data collection, pre-processing, data wrangling, development of appropriate algorithms, and deployment of models assist the livestock producers in decision-making based on real-time monitoring and act as early-stage warning systems to forecast disease dynamics based on prediction models. Due to the convincing performance, precision, and accuracy of AI models, the climate-smart livestock production imbibes AI technologies for scaled use in the successful reducing of heat stress in ruminant livestock, thereby ensuring sustainable livestock production and safeguarding the global economy. [ABSTRACT FROM AUTHOR]

Extensive research has been conducted globally on the impact of heat stress (HS) on animal health and milk production in dairy cows. In this article, we examine the possible reasons for the decrease in milk production in Brown Swiss (BS) cows during the autumn season, known as the autumn low milk yield syndrome (ALMYS). This condition has been extensively studied in high-yielding Holstein Friesian (HF) cattle and has also been observed in BS cows with a daily milk yield of around 30 kg. Our hypothesis is that the drop in milk yield and the increased prevalence of mastitis in autumn, as found in our recent studies, may be a long-term consequence of summer HS. We re-evaluate our previous findings in light of the possible manifestation of an HS-related form of ALMYS in BS cows. As milk yield, mastitis spread, and reproductive function of cows are interrelated and have seasonal dependence, we examine the consistency of our hypothesis with existing data. The significant drop in milk yield in BS cows in autumn (by 2.0–3.2 kg), as well as the threshold of milk yield decrease (temperature-humidity index of 70.7), may point in favour of the manifestation of ALMYS in BS cows, similar to HF cows. Only the percentage effect of seasonal factor (59.4%; p < 0.05) on milk yield of BS cows was significant. HS-related ALMYS provides a robust conceptual framework for diverse sets of productive and animal health data in BS cows, similar to observations in high-yielding HF cattle. However, the limitations associated with the lack of additional data (e.g. immunological indicators) suggest the need for further research to confirm ALMYS in BS breed. [ABSTRACT FROM AUTHOR]

Simple Summary: The effects of seasonal transition and temperature humidity index (THI) on a number of variables representing physiological, hematological and molecular responses of lactating dairy cows reared under natural environmental conditions were assessed. The study revealed significant impact of seasonal transition and THI on most of these variables. The physiological, hematological and molecular alterations highlight adaptive responses of bovine traits to climatic stressors. The results of this study contribute to a deeper understanding of the adaptive mechanisms of dairy cows under challenging environmental conditions, indicating their potential as heat stress biomarkers. A comprehensive study was conducted to assess the effects of seasonal transition and temperature humidity index (THI) on the adaptive responses in crossbred dairy cows reared in a tropical savanna region. A total of 40 lactating dairy cattle reared by small-scale dairy farmers in Bengaluru, India, were selected for this study. The research period comprised the transitioning season of summer to monsoon, wherein all traits were recorded at two points, one representing late summer (June) and the other early monsoon (July). A set of extensive variables representing physiological responses (pulse rate, respiration rate, rectal temperature, skin surface temperature), hematological responses (hematological profile), production (test day milk yield, milk composition) and molecular patterns (PBMC mRNA relative expression of selective stress response genes) were assessed. A significant effect of seasonal transition was identified on respiration rate (RR), skin surface temperature, mean platelet volume (MPV), platelet distribution width (PDWc), test day milk yield and on milk composition variables (milk density, lactose, solids-not-fat (SNF) and salts). The THI had a significant effect on RR, skin surface temperature, platelet count (PLT), plateletcrit (PCT) and PDWc. Lastly, THI and/or seasonal transition significantly affected the relative PBMC mRNA expression of heat shock protein 70 (HSP70), interferon beta (IFNβ), IFNγ, tumor necrosis factor alpha (TNFα), growth hormone (GH) and insulin-like growth factor-1 (IGF-1) genes. The results from this study reveal environmental sensitivity of novel physiological traits and gene expressions to climatic stressors, highlighting their potential as THI-independent heat stress biomarkers. [ABSTRACT FROM AUTHOR]

Animal husbandry serves as a source of provision of high-quality animal protein to the entire world population. Farm animals are exposed to different types of stressors at various stages of their life cycle. The climate change phenomenon also imposes additional stress on the animals due to extreme temperature (heat and cold) and unavailability of feed, etc. Such stress stimuli induce the release of stress hormones such as epinephrine, norepinephrine and cortisol in animals. These stress hormones reduce the host's production, reproduction and also influence the immune mechanisms. Recent researches revealed the stress hormone responsiveness of micro-organisms. Stress hormones were shown to increase the bacterial growth and virulence mechanisms, and the infectious disease process. This concept gains significance in the stress-related disease outbreaks in animals. Therefore, a brief discussion of important stressors affecting farm animals, their influence on the host immune system and disease pathogenesis was done in this review. Abbreviations: ACTH: Adrenocorticotropic hormone; CA: Catecholamine; cAMP: cyclic Adenosine monophosphate; CD80: Cluster of Differentiation 80; CD83: Cluster of Differentiation 83; CD86: Cluster of Differentiation 86; CRH: Corticotrophin Releasing Hormone; DC: Dendritic cells; DNA: Deoxy Ribo Nucleic acid; EHEC: Enterohaemorrhagic E.coli; EPI: Epinephrine; ETEC: Enterotoxigenic E.coli; GH: Glucocorticoid; GIS: Geographic Information System; GPS: Global Positioning System; HPA: Hypothalamo-pituitary-adrenal; ICT: Information and Communication technology; IFN-β: Interferon-β; IFN-γ: Interferon-γ; IL-10: Interleukin-10; IL-13: Interleukin-13; IL-4: Interleukin-4; IL-6: Interleukin-6; IL-8: Interleukin-8; IMH: Intermediate hosts; IPCC: Intergovernmental Panel on Climate Change; K99: Fimbrial 99; LPS: Lipopolysaccharide; LTA: Lipoteichoic acid; MAPK: Mitogen Activated Protein Kinase; NE: Norepinephrine; NK: Natural killer cells; PAMP: Pathogen Associated Molecular Pattern; PRR: Pattern Recognition Receptor; QseB/QseC: sensor histidine kinase/a response regulator; S layers: Slime layers; SAM: Sympathetic-adrenal-medullary; Th0: T helper0; Th1: T helper 1; Th2: T-helper 2; THI: Temperature-Humidity Index; TLR: Toll Like receptor; TNF-α: Tumour Necrosis Factor –α; TNF-β: Tumour Necrosis Factor-β [ABSTRACT FROM AUTHOR]

This study aimed to assess the effect of the insulin-like grow factor 1 (IGF-1) treatment during in vitro maturation on the gene expression and developmental ability of ovine oocytes. Ovine cumulus-oocyte complexes (COC) were matured in vitro without (control) or with the supplementation of IGF-1 (100 ng/ml) and then subjected to in vitro fertilization and culture. The rate of oocyte maturation and embryo development was recorded and expression of the selected genes (involved in the PI3K/Akt and apoptosis signaling) was assessed in the matured oocytes. The IGF-1 treatment significantly (p <.05) improved the oocyte maturation rate (%) as compared to the control (81.5 ± 2.40 vs. 73.6 ± 0.94). Similarly, as compared to the control, the IGF-1 treatment significantly (p <.05) improved the rate (%) of cleavage (54.7 ± 1.58 vs. 67.2 ± 3.65) and the formation of 4–8 cell embryos (30.7 ± 2.89 vs. 44.1 ± 4.01) and morula (20.7 ± 2.08 vs. 32.8 ± 2.78). The IGF-1 treatment significantly (p <.05) upregulated the expression of IGF1R, PI3KR1, AKT1 and BCL2 and downregulated the expression of GSK3β, FOXO3 and CASP9 in the matured oocytes. In conclusion, the IGF-1 treatment significantly improved the developmental competence of ovine oocytes through the regulation of the PI3K/Akt and apoptosis signaling. [ABSTRACT FROM AUTHOR]