Journal of Energy Bioscience 2025, Vol.16, No.1, 1-12 http://bioscipublisher.com/index.php/jeb 8 In China, the spatial-temporal dynamics of carbon footprints in crop production revealed that practices such as straw return and improved fertilization efficiency significantly mitigated greenhouse gas emissions. However, the primary drivers of emissions varied across regions, with fertilization, machinery operation, and rice paddy methane flux being the main contributors in different areas (Liu et al., 2018). This highlights the importance of implementing region-specific management practices to effectively reduce emissions and enhance carbon sequestration. Table 1 Average organic carbon stock in soil collected at 0-30 cm in the different fields of the I Rodi (IR) farm, Tassinari Carla (BT) farm, and Maccanti Vivai (MV) farm. The respective bulk densities for each investigated area are also reported (Adopted from Brombin et al., 2020) Field Bulk Density (g/cm3) OC Stock (Mg/ha) IR farm 1.24 Grassland 85.9 Low-yield 84.1 Productive 159.6 BTfarm 1.40 Turfed orchard (since 1992) 40.3 Vegetable garden (since 1992) 48.3 Turfed orchard (since 2007) 43.7 Vegetable garden (since 2007) 41.4 Vegetable garden (since 1996) 40.4 Harrowed 1.13 33.0 Strawberry (since 1996) 37.4 MVfarm 1-year-old pear orchard nursery 267.3 2-year-old pear orchard nursery 248.0 3-year-old pear orchard nursery 228.6 8 Future Perspectives in Low-Carbon Agriculture 8.1 Technological innovations Precision agriculture technologies are pivotal in optimizing resource use and enhancing carbon sequestration in agricultural systems. By employing tools such as remote sensing, GPS, and data analytics, precision agriculture can tailor inputs like water, fertilizers, and pesticides to the specific needs of crops, thereby reducing waste and emissions. For instance, simulation models have demonstrated that precision agriculture can significantly reduce soil organic carbon (SOC) losses and greenhouse gas (GHG) emissions by optimizing tillage practices and input management (Cillis et al., 2018). Additionally, precision agriculture can help in monitoring and managing soil health, which is crucial for maintaining high levels of SOC and ensuring sustainable crop production (Bai et al., 2019; Tiefenbacher et al., 2021). Smart farming technologies, including the use of sensors, drones, and autonomous machinery, offer innovative solutions for reducing the carbon footprint of agriculture. These technologies enable real-time monitoring and management of farm operations, leading to more efficient use of resources and lower emissions. For example, the integration of conservation tillage with precision agriculture technologies has been shown to reduce carbon emissions by up to 56% compared to conventional tillage practices (Cillis et al., 2018). Moreover, advancements in digital agriculture and crop genetics have the potential to significantly reduce GHG emissions from row-crop farming, although widespread adoption remains a challenge due to economic and infrastructural barriers (Amundson, 2022). 8.2 Education and capacity building Effective training programs are essential for equipping farmers with the knowledge and skills needed to adopt low-carbon agricultural practices. These programs should focus on the benefits and implementation of practices
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