Applications of Artificial Intelligence for Heat Stress Management in Ruminant Livestock.

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.

Novel Insights to Assess Climate Resilience in Goats Using a Holistic Approach of Skin-Based Advanced NGS Technologies.

A novel study was conducted to elucidate heat-stress responses on a number of hair- and skin-based traits in two indigenous goat breeds using a holistic approach that considered a number of phenotypic and genomic variables. The two goat breeds, Kanni Aadu and Kodi Aadu, were subjected to a simulated heat-stress study using the climate chambers. Four groups consisting of six goats each (KAC, Kaani Aadu control; KAH, Kanni Aadu heat stress; KOC, Kodi Aadu control; and KOH, Kodi Aadu heat stress) were considered for the study. The impact of heat stress on caprine skin tissue along with a comparative assessment of the thermal resilience of the two goat breeds was assessed. The variables considered were hair characteristics, hair cortisol, hair follicle quantitative PCR (qPCR), sweating (sweating rate and active sweat gland measurement), skin histometry, skin-surface infrared thermography (IRT), skin 16S rRNA V3-V4 metagenomics, skin transcriptomics, and skin bisulfite sequencing. Heat stress significantly influenced the hair fiber characteristics (fiber length) and hair follicle qPCR profile (Heat-shock protein 70 (HSP70), HSP90, and HSP110). Significantly higher sweating rate, activated sweat gland number, skin epithelium, and sweat gland number (histometry) were observed in heat stressed goats. The skin microbiota was also observed to be significantly altered due to heat stress, with a relatively higher alteration being noticed in Kanni Aadu goats than in Kodi Aadi goats. Furthermore, the transcriptomics and epigenetics analysis also pointed towards the significant impact of heat stress at the cellular and molecular levels in caprine skin tissue. The higher proportion of differentially expressed genes (DEGs) along with higher differentially methylated regions (DMRs) in Kanni Aadu goats due to heat stress when compared to Kodi Aadu goats pointed towards the better resilience of the latter breed. A number of established skin, adaptation, and immune-response genes were also observed to be significantly expressed/methylated. Additionally, the influence of heat stress at the genomic level was also predicted to result in significant functional alterations. This novel study thereby highlights the impact of heat stress on the caprine skin tissue and also the difference in thermal resilience exhibited by the two indigenous goat breeds, with Kodi Aadu goats being more resilient.

Molecular, Physiological and Hematological Responses of Crossbred Dairy Cattle in a Tropical Savanna Climate.

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 (IFNß), 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.

Heat Stress and Goat Welfare: Adaptation and Production Considerations.

This review attempted to collate and synthesize information on goat welfare and production constraints during heat stress exposure. Among the farm animals, goats arguably are considered the best-suited animals to survive in tropical climates. Heat stress was found to negatively influence growth, milk and meat production and compromised the immune response, thereby significantly reducing goats' welfare under extensive conditions and transportation. Although considered extremely adapted to tropical climates, their production can be compromised to cope with heat stress. Therefore, information on goat adaptation and production performance during heat exposure could help assess their welfare. Such information would be valuable as the farming communities are often struggling in their efforts to assess animal welfare, especially in tropical regions. Broadly three aspects must be considered to ensure appropriate welfare in goats, and these include (i) housing and environment; (ii) breeding and genetics and (iii) handling and transport. Apart from these, there are a few other negative welfare factors in goat rearing, which differ across the production system being followed. Such negative practices are predominant in extensive systems and include nutritional stress, limited supply of good quality water, climatic extremes, parasitic infestation and lameness, culminating in low production, reproduction and high mortality rates. Broadly two types of methodologies are available to assess welfare in goats in these systems: (i) animal-based measures include behavioral measurements, health and production records and disease symptoms; (ii) resources based and management-based measures include stocking density, manpower, housing conditions and health plans. Goat welfare could be assessed based on several indicators covering behavioral, physical, physiological and productive responses. The important indicators of goat welfare include agonistic behavior, vocalization, skin temperature, body condition score (BCS), hair coat conditions, rectal temperature, respiration rate, heart rate, sweating, reduced growth, reduced milk production and reduced reproductive efficiency. There are also different approaches available by which the welfare of goats could be assessed, such as naturalistic, functional and subjective approaches. Thus, assessing welfare in goats at every production stage is a prerequisite for ensuring appropriate production in this all-important species to guarantee optimum returns to the marginal and subsistence farmers.