Machine learning (ML) algorithms have transformed data analysis across various sectors, providing powerful tools to derive insights, make predictions, and automate complex processes. This review explores the fundamental classifications of ML algorithms, including supervised, unsupervised, semi-supervised, reinforcement, and deep learning methods, each offering unique capabilities for addressing diverse data-driven challenges. In the field of livestock farming, ML applications are proving to be particularly impactful, helping to enhance productivity, optimize resource use, and improve animal health and welfare. By leveraging data from sensors, imaging, and environmental inputs, ML models can detect diseases, monitor animal behaviors, forecast production yields, and manage feeding schedules more precisely than ever before. Despite significant advancements, challenges remain, including data quality issues, model interpretability, and ethical considerations surrounding animal welfare. This paper provides an overview of key ML algorithms and examines current applications and future prospects of ML in the livestock sector, aiming to highlight its potential for innovation and sustainable development in modern agriculture.

One of the stressful situations for livestock and poultry is heat stress (HS), which has a detrimental effect on animal physiology, production, and product quality. Because of their quick development and metabolism, high production, and species-specific characteristics including decreased sweating, the protective layer of skin, and rumen fermentation, some varieties of livestock are more vulnerable to heat stress than others. Muscle that is pale, soft and exudative (PSE) and lacks the ability to retain water can be produced by short-term heat stress that occurs pre-slaughter. This stress increases muscle glycogenolysis. In contrast, animals that experience prolonged heat stress have lower muscle glycogen reserves, which results in meat that is dark, firm, and dry (DFD), has a high final pH and water retention capacity. Moreover, HS causes shortened shelf life, oxidative stress. According to a recent study, HS might plausibly modify the rate and amount of postmortem muscle glycolysis and the resulting pH, which can impact the physiological and metabolic disturbances that occur in live animals as well as the features of carcasses and meat quality. This review reflects the effect of heat stress on meat quality.

Consumers' increasing demand for high-quality and safe meat products has led the food industry to explore advanced analytical techniques, such as artificial intelligence and nearinfrared reflectance spectroscopy to assess and monitor the quality and safety of meat. The quality and safety of meat products have become increasingly important considerations for consumers, driven by concerns over health implications and the need for transparency in the meat supply chain. The meat industry faces increasing demands from consumers for higher quality and safer products, driven by concerns over food-borne illnesses and the nutritional value of meat. Addressing these growing consumer expectations has become a priority, prompting researchers to actively investigate the potential of innovative nondestructive techniques, including near-infrared spectroscopy and others in combination with advanced data analysis methodologies to enable rapid, objective, and environmentally-friendly assessment of diverse meat quality and safety attributes. This review examines the current state of research on the application of these technologies in the meat industry. Additionally, it explores the integration of artificial intelligence algorithms with near-infrared spectroscopy data to enhance the accuracy and reliability of meat quality prediction and authentication.

The utilization of probiotics in animal husbandry has garnered significant attention as a natural and effective strategy to enhance production performance and meat quality. This review synthesizes current research on the impact of probiotics on various livestock, including poultry, swine, and cattle. Probiotics, which are live microorganisms that confer health benefits to the host, have been shown to improve growth rates, feed conversion ratios, and overall health status of animals. Furthermore, they contribute to enhanced meat quality by influencing factors such as muscle composition, fat content, and oxidative stability. Mechanistically, probiotics exert their effects through modulation of gut microbiota, enhancement of nutrient absorption, and stimulation of the immune system. Studies also indicate a reduction in the incidence of diseases and a decrease in the need for antibiotic growth promoters, addressing concerns over antibiotic resistance. Despite promising results, variability in outcomes suggests that probiotic efficacy is influenced by factors such as strain specificity, dosage, and administration methods. Future research should focus on optimizing probiotic formulations and understanding the underlying mechanisms to maximize their benefits in animal production. This review highlights the potential of probiotics as a sustainable approach to improve animal performance and meat quality, contributing to more efficient and health-conscious animal agriculture.

Assessing the food quality is essential to confirm the safety, nutritional value, and sensory attractiveness of the food we ingest. Due to the globalization of food industry and concerns over food security have resulted to a greater demand from consumers for safe and nutritious food. As a result, there is a need for manufacturers to develop cutting edge technologies for recognizing and determining food quality. Presently, stakeholders in the food industry encounter the challenge of ensuring food quality and safety. Producers need to meet sustainable and environmentally robust food production standard, extended shelf life, sensory quality, nutritional value, and functional properties. The general analytical practices identify the primary metabolites for whole food quality which solely verifies the total composition of nutritional metrics. In present days consumers concentrate of functional quality of food items. So, it is essential to examine secondary metabolite compounds, enzymes and other functional quality, authenticity of food items, sources that are critical for health, development, safety, and other aspects of consumer well-being. This review paper seeks to examine the different aspects of evaluating food quality and the methods used to ensure that the food we consume meets the required criteria. Furthermore, it discusses cutting edge technologies for assessing especially secondary metabolites, enzyme functions, functional quality of food items, verifying food authenticity to optimize food manufacturing processes.