Characterization of Wool Fiber Diameter and Growth Rate in Merino Sheep under High-Altitude Grazing

Abstract

The production of high-quality wool in Merino sheep is significantly influenced by environmental conditions, particularly in high-altitude grazing systems where climatic stress and forage variability affect fiber development. This study presents the characterization of wool fiber diameter and growth rate in Merino sheep under high-altitude grazing to evaluate the impact of environmental and nutritional factors on wool quality and productivity. The proposed methodology involves field-based observations and controlled measurements across different grazing conditions at varying altitudes. Key parameters, including wool fiber diameter, staple length, growth rate, fleece weight, and animal physiological responses, are measured using standard fiber analysis and livestock monitoring techniques. Additional variables such as pasture composition, temperature, humidity, and altitude-related stress indicators are recorded to assess their influence on wool traits. The collected data are preprocessed through cleaning, normalization, and statistical validation to ensure consistency and reliability. Advanced analytical and machine learning models, including regression analysis, Random Forest, and Artificial Neural Networks, are employed to analyze the relationships between environmental factors and wool characteristics. Experimental results indicate that high-altitude conditions, characterized by lower temperatures and variable forage quality, influence fiber diameter by promoting finer wool under moderate stress conditions. However, excessive environmental stress can reduce wool growth rate and overall fleece yield. The study identifies optimal grazing conditions and management strategies that balance fiber quality and growth performance. The findings highlight the importance of adaptive grazing and nutritional management in high-altitude sheep farming. The study concludes that integrating environmental monitoring with data-driven analysis provides a scalable and sustainable approach for improving wool quality, enhancing growth rate, and supporting profitable Merino sheep production.