Coffee is a crop of great relevance in socioeconomic terms for Brazilian agribusiness, which is the world’s largest producer in cultivated areas. The implementation of precision agriculture in the coffee culture has provided countless benefits to its development, which over the years has been cultivated in the same area. However, there is a lack of studies that address the impact of the application of variable-rates inputs in soil on the energy efficiency and sustainability of these systems. This study aimed to analyze how variable-rate fertilization influences energy efficiency in coffee growing. A production area subjected to variable and fixed rates of fertilizer in alternating rows was evaluated. Geo-referenced yield data was collected to assess yield response for fixed and variable rate applications. The energy assessment was combined with the Geographic Information System (GIS) to determine site-specific energy indicators. To determine the energy flow, only NPK fertilizer applications were considered as inputs and the yield as output. The results obtained indicated that the variable rate fertilizer application has a small difference, indicating greater energy efficiency concerning the applied fertilizer and coffee production per crop season. It was observed in the 06/07 crop, the incorporated energy was 10.7 MJ kg⁻¹ for VR and 10.2 MJ kg⁻¹ for UR and for the 07/08 crop it was 30.7 MJ kg⁻¹ for VR and 34.9 MJ kg⁻¹ for UR. The energy balance was more efficient at variable rates, as it provided fertilizer savings without compromising yield. However, the difference between the embodied energy per mass of coffee produced was very small compared to the fixed rate.

Studies on the environmental footprints of agricultural production have strong links with 4 out of the 17 Sustainable Development Goals (SDG) established by the United Nations. Irrigation systems are essential tools for increasing agricultural yields, particularly in arid regions. However, the production and assembly of these systems can have significant environmental impacts, including excessive water consumption and greenhouse gas emissions. Although studies have approached biomass production, few of them have provided data about asset depreciation, such as irrigation systems, machinery, etc. Trying to fill this gap, this study aimed at determining the water and carbon footprints of two commonly used irrigation systems: center pivot and drip. Several variables, including the irrigated area, pump power, filter type, system flow, and pipe length, were analyzed to determine the carbon and water footprints of each component of the irrigation systems. The results reveal that the materials used for pipes and filters had the most significant impact on the water and carbon footprints, with galvanized steel pipes and sand filters having the highest footprints. Additionally, the irrigated area affected the center pivot and drip systems differently, with the depreciation of the irrigation systems being a significant variable for both water and carbon footprints. These results can support the development of sustainable irrigation practices that reduce environmental impacts while enhancing agricultural yields. Decision-makers can use this information to establish a life-cycle database and evaluate the impact of irrigation systems on water and carbon footprints.

The recognition of bioethanol as a key strategy for mitigating greenhouse gas (GHG) emissions is closely linked to the accuracy of N₂O emission factors (EF) used in life cycle assessments. However, previous studies have shown that the default N₂O EF values recommended by the IPCC do not accurately reflect the diverse edaphoclimatic conditions found in Brazil, leading to uncertainties in GHG inventories. Therefore, establishing regional N₂O EF is essential for improving the precision of bioethanol emission estimates. In this study, we conducted a systematic literature review compiling 293 measurements from 45 field studies across different regions of Brazil. This study focuses on sugarcane (20 studies) and corn (25 studies), which are the primary crops used for bioethanol production in Brazil. Our findings indicate that the average N₂O EF for these crops is 0.72%, lower than the value reported for the tropics and sub‐tropics (1.6%). When analyzed separately, sugarcane showed an average N₂O EF of 0.65%, with higher emissions from the combined use of mineral and organic N fertilizers (0.79%) compared to mineral (0.55%) or organic fertilizers alone (0.77%). For corn, the average N₂O EF was 0.84%, with mineral N fertilizers presenting the lowest EF (0.40%), while emissions increased with the combination of mineral and organic sources (0.82%), reaching the highest levels with pig slurry application (1.72%). These variations highlight the limitations of using IPCC default values for mineral and organic N fertilizers in Brazil. Our results reinforce the need for Tier 2 methodologies incorporating region‐specific data to enhance GHG inventory accuracy and support targeted mitigation strategies. Although Brazil's latitudinal range spans tropical and subtropical zones, regional stratification was not applied due to the limited number of studies within each climate category, especially when further disaggregated by crop type and N fertilizer source. Despite covering key crops, fertilizer types, and multiple biomes, the current dataset still lacks representation for important agricultural regions such as Brazil's midwest, north, and northeast regions. This study represents a significant step toward refining N₂O EF estimates for bioethanol crops, contributing to more precise assessments of the sector's climate impact. However, further research is needed to cover underrepresented areas, understand long‐term field dynamics, and evaluate other crop systems and management practices. Future studies should also incorporate modeling tools and real‐time monitoring to reduce uncertainties and support the development of Tier 3 estimates.