ENHANCING ROSE PLANT GROWTH WITH MUTTON WASHED WATER: A MACHINE LEARNING APPROACH

The utilization of organic waste products for plant growth has gained attention as an eco-friendly and cost-effective fertilization method. This study explores the impact of mutton washed water on the growth and flowering of rose plants (Rosa spp.) through an analysis supported by a Large Language Model (LLM). The research focuses on evaluating the nutritional content of mutton washed water, its effects on soil properties, plant health, and potential risks associated with its usage. Mutton washed water contains essential nutrients such as proteins, fats, nitrogen, phosphorus, and trace minerals, which can enhance plant growth and flowering when applied correctly. However, improper application may lead to soil contamination, microbial imbalance, and nutrient toxicity. This study employs AI-driven data analysis to assess the effectiveness of mutton washed water as an organic fertilizer through controlled experiments involving different treatment groups. By integrating machine learning models, the study provides insights into the long-term impact of mutton washed water on soil health, microbial diversity, plant development, and disease resistance. Predictive modeling using LLM helps refine best practices for sustainable agricultural applications. The results indicate that diluted mutton washed water (1:10) or its combination with compost extract significantly improves rose plant growth, while undiluted application can lead to root stress and reduced flowering. The findings contribute to the sustainable farming movement by advocating for the optimized use of organic waste products and AI-driven agricultural strategies.