Himanshu Tiwari

One of the main challenges in accurately assessing greenhouse gas emissions under conservation agriculture practices is the complexity of interactions between factors such as soil types, climatic conditions, crop species, and tillage methods, making emissions quantification very difficult. Many factors, such as microbial activity in the soil, which significantly influence emissions, are not easily measurable by traditional methods, while temporal and spatial variations in emissions, such as those of nitrous oxide (N₂O), further complicate estimation. Current measurement techniques also have limitations, being costly, time-consuming, and often inefficient for long-term monitoring in large agricultural systems. To improve quantification, advancements in measurement techniques are needed, such as automated real-time emission monitoring systems, the use of drones, wireless sensors, and satellite technologies. Additionally, the development of advanced models that integrate various factors, including microbial activity and climatic conditions, can enable more precise data synthesis and better emission prediction. The introduction of models that track the carbon dioxide cycle throughout the entire crop cycle, including dormancy and post-harvest periods, is crucial for accurately assessing emissions and managing them effectively.