Agriculture, forestry, and other land use (AFOLU) have a substantial impact on the global carbon cycle. It can be source as well as sink of greenhouse gases (GHGs), such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). About 12% of anthropogenic GHG emissions come from agriculture, primarily from enteric fermentation and rice farming for CH4 and fertilizer and manure use for nitrous oxide. Accurate measurement and mitigation of these gases are crucial for climate action because of their high potential for global warming. In this study we examined methods for quantifying agricultural GHG emissions that includes Intergovernmental panel on climate change (IPCC) tiered approach, chamber methods, eddy covariance systems and modeling. While chamber and eddy covariance methods provide detailed, high-resolution flux data that are essential for model validation and comprehending environmental controls, the IPCC framework allows emissions estimates at multiple detail levels. Field data and remote sensing are combined in modeling approaches, such as empirical, process-based, and integrated assessment models, to project emissions under various conditions and simulate biogeochemical processes. According to the findings, enteric fermentation is responsible for roughly 40% of agricultural emissions. In upland soils, N2O emissions range from 2 to 5 kg N2O-N/ha/year, while CH4 emissions from rice paddies average 270 kg CH4/ha/year. Temperature, carbon content, soil moisture, and management techniques all affect emissions. Nearly 30% of global agricultural emissions come from regional hotspots like Brazil, Indonesia, and India, underscoring the need for focused interventions. Improved livestock feeding, conservation agriculture, precision farming, agroforestry, mid-season drainage in rice, better nutrient management, and soil restoration are all suggested mitigation techniques. These methods maintain productivity while lowering emissions and increasing soil carbon storage. Advanced modeling, measurement, and emerging technologies must be integrated to improve emission estimates and advance climate-smart agriculture in accordance with global climate goals.