Salinity-Stress Resilience of Crops Mediated by AI Models with Nanotechnology

Soil salinization poses a major challenge to global agriculture, affecting crop productivity, soil fertility, and food security. This chapter explores the integration of artificial intelligence (AI) and nanotechnology as a transformative approach to enhance crop resilience against salinity stress. It begins by outlining the physiological, molecular, and anatomical effects of salt stress on plants, emphasizing the dual impact of osmotic and ionic toxicity on growth, metabolism, and gene regulation. The limitations of conventional remediation methods underscore the need for precision technologies. Nanotechnology offers promising solutions through nano-fertilizers, soil remediation materials, and nanosensors that enable targeted delivery, improved nutrient use efficiency, and real-time monitoring. However, these technologies alone face challenges related to scalability, environmental safety, and data complexity. AI complements nanotechnology by providing predictive modeling, data analytics, and intelligent decision-making to optimize nano-interventions and accelerate breeding for salt-tolerant cultivars. The synergistic integration of AI-driven nanosensor networks and machine learning-based analytics enables the development of adaptive, autonomous systems capable of real-time stress detection and response. The chapter concludes with a discussion on implementation challenges and outlines strategies for sustainable deployment through open-source innovation, policy reform, and participatory research. Together, AI and nanotechnology represent a next-generation framework for achieving climate-resilient, resource-efficient, and sustainable agriculture in the face of expanding soil salinity.