Smart agriculture improves nitrogen use efficiency yield prediction and sustainability in dryland mixed crop livestock systems
Abstract
Mixed crop-livestock systems in dryland regions play a critical role in ensuring food security in the Global South; however, they are confronted with several challenges, including unpredictable rainfall patterns, nutrient depletion, and low productivity levels. The integration of advanced agricultural technologies, such as artificial intelligence (AI), the Internet of Things (IoT), and remote sensing, presents transformative opportunities for enhancing the efficacy of these systems. This paper investigates how intelligent agricultural tools can improve nitrogen management, boost productivity in both crops and livestock, and promote overall farm sustainability. Strategies such as intercropping alfalfa with corn silage, utilizing remote sensing for real-time monitoring, and implementing precision fertilization techniques directly address fundamental issues such as nitrogen use efficiency (NUE), soil health, and feed quality. Additionally, the application of intelligent yield estimation models and nutrient recovery methods further optimizes resource utilization. The integration of machine learning algorithms with satellite data enhances the accuracy of yield predictions, thereby facilitating informed decision-making and bolstering economic resilience. Despite these promising advancements, various barriers including limited digital accessibility, data deficiencies, and socio-economic constraints impede the widespread adoption of these technologies. Therefore, it is essential to implement policy support, develop necessary infrastructure, and promote farmer-centered co-innovation to scale these solutions effectively. This study concludes that the incorporation of smart agriculture within integrated crop-livestock systems can significantly enhance sustainability, productivity, and resilience in dryland regions. The integration of smart agricultural tools significantly enhances nitrogen use efficiency and overall productivity in crop-livestock systems. The practices of intercropping and intelligent monitoring contribute to improved sustainability and favorable economic outcomes. Addressing data gaps and overcoming digital barriers are critical factors for the widespread adoption of advanced agricultural technologies. The integration of smart agricultural tools significantly enhances nitrogen use efficiency and overall productivity in crop-livestock systems. The practices of intercropping and intelligent monitoring contribute to improved sustainability and favorable economic outcomes. Addressing data gaps and overcoming digital barriers are critical factors for the widespread adoption of advanced agricultural technologies.