AI-Driven Prediction of Medicinal Property Presence in Plants Cultivated with Nutrient-Enriched Manure

For thousands of years, medicinal plants have been used for treating a variety of ailments. Medicinal plants have the potential to provide natural and effective remedies for common health problems and are often cost-effective and less toxic as compared to synthetic drugs. Despite the multiple advantages of medicinal plants, their cultivation is still a result of inefficient rudimentary practices. The lack of standardisation in cultivation practices, harvesting and processing of medicinal plants has led to consistency in the final product. Moreover, many farmers need more knowledge and technical expertise to grow medicinal plants, resulting in unsuccessful cultivation operations. The quality of soil and the right amount of macronutrients an important factors determining the growth and quality of medicinal plants. Extensive use of chemical fertilisers and inconsistent levels of micronutrients may lead to loss or diminishing medicinal properties. The works present a hypothesis that emphasises the use of machine learning algorithms for the prediction of medicinal properties. The study presents ways in which machine learning and AI can be used to analyse data from various sources to identify patterns and make predictions regarding the cultivation of medicinal plants. The hypothesis proposed in this research framework was tested with prior tests and also validated against three different concept cases, which ultimately catered to the cultivation and production of different medicinal plants.