Integrating Modern and Intelligent Approaches with Efficiency for Soil Nutrient Deficiency Detection - Raj, Pranav (Agricultural Sciences: Techniques and Innovations Vol. 1, 2025)
The essentiality of soil health to the vitality of our planet cannot be overstated. This complex ecosystem teems with microscopic organisms and vital nutrients that foster the growth of plants, feeding into the cycle of life that sustains us all. The application of intelligent technologies, particularly artificial intelligence (AI) and machine learning (ML), in detecting soil nutrient deficiencies is revolutionising modern agriculture. While traditional soil nutrient analysis methods are effective, they are often costly, time-consuming, and lack real-time insights. Emerging intelligent approaches overcome these limitations by providing rapid, accurate assessments, enabling precise and timely fertilisation. Case studies, such as those of Indian startups CropIn and Fasal, illustrate the successful implementation of AI-driven solutions, leading to improved crop yields, optimised fertiliser use, and enhanced sustainability. This article explores current advancements, ongoing research, and future prospects, emphasising AI’s role not only in detection but also in predictive nutrient management. Additionally, it outlines a roadmap for farmers and stakeholders, guiding them in adopting these technologies by understanding their potential, selecting appropriate tools, and fostering a culture of innovation. Overall, integrating intelligent approaches into soil nutrient management paves the way for a more efficient, sustainable, and economically viable agricultural future. For successful adoption, farmers and stakeholders must embrace change, leverage available resources, and seek continuous learning and collaboration.