Overview of Sustainable Agricultural Systems: Enhancing Efficiency and Reducing Environmental Impact

In recent decades, globally, consumers, society, and policymakers have increased their awareness of environmental issues. The need to feed the increasing population has also highlighted the inefficiencies in agricultural and livestock management and their consequences [1]. The environmental context is frequently used as a barrier to international trade and as a promoter of new market niches [2,3]. Biosystems have been identified as sources of environmental impact, which has led to the constant aim for improvement, including the adoption of rational input use in decision-making, technology, and waste reduction [4,5].

Based on this context, this Special Issue titled “Sustainable Agricultural Systems: Enhancing Efficiency and Reducing Environmental Impact” was launched in 2024, successfully gathering studies that contribute to environmental awareness through systemic approaches focused on viable production chains or their components. The eleven articles cover topics from agricultural practices and the rationalization of input use to the circular economy through wastewater reuse, greenhouse gas (GHG) mitigation, carbon footprint consideration, energy efficiency, and precision agriculture.

1. 

Agricultural Practices and the Rationalization of Input Use

Boros et al. (2025) presented a systematic literature review of 291 studies on the progress and future opportunities of “sustainable agricultural practices”. The research classified the most promising practices into three groups:

• Agroecological Practices: Integrating ecological principles such as crop diversification and organic fertilizers.
• Sustainable Agricultural Intensification: Focusing on increasing the productivity per unit area through genetic improvement and resource efficiency.
• Technological Innovations: Using cutting-edge technologies including AI, biotechnology, drones, and big data to optimize resources.

This framework was corroborated in [6], where researchers evaluated integrated crop–livestock systems (ICLS) effects on crop yields and soil fertility. They concluded that an intermittent pasture system for legume crops in sequence is an alternative that can maintain or improve soil chemical composition and highlighted that conventional tillage systems should be avoided for tropical sandy soils.

In another study, Yoo et al. (2025) analyzed the effects of combining pesticides and amino acids in South Korean rice fields, finding that this practice sustains productivity while mitigating the environmental impact by reducing GHG emission intensity and the amount of pesticide applied. Their findings complement studies that approached amino acids as tools for toxicity mitigation [7].

2. 

Circular Economy: Water and Waste Reuse

Several studies evaluated the application of wastewater for irrigation, due to its economic and environmental impacts, in addition to its technological requirements [8,9]. To address freshwater scarcity—with agriculture consuming about 70% of the world’s supply—Carvalho et al. (2025) proposed a method to identify ideal areas for treated wastewater reuse in Brazil. The study concluded that using wastewater from industries such as dairies and sugar mills provides a stable supply of nutrients, reducing the dependence on synthetic fertilizers.

Additionally, Murad Lima et al. (2025) researched the use of treated slaughterhouse effluent (TSE) in soybean cultivation. The authors indicated that TSE is a viable and sustainable strategy for soybean production, but it requires the longer-term monitoring of soil sodium levels to avoid salinization. Regarding environmental safety, Fabiani et al. (2025) found that using anaerobic digestate in corn fertigation is safe, as long as there is an adequate interval (21 days) between application and harvest to allow the plant’s natural microbiota to recover.

3. 

Greenhouse Gas (GHG) Mitigation and Carbon Footprint (CF)

Studies considering GHG emissions and the CF of crops determined the equivalence of carbon dioxide or the amounts of carbon, respectively [10], and considered the energy provided by the mitigation routes [11]. Both ways help to map the production systems’ components, to both enable effective decision-making and consider the energy nexus, since energy is the main reason mitigation is necessary.

In their research in Southern Brazil, Silva et al. (2025) demonstrated that replacing winter fallow with cover crops (legumes or grasses) in no-till corn systems is highly effective. These practices increase carbon sequestration in the soil and drastically reduce the crop’s climate footprint.

More broadly, Xiao et al. (2025) analyzed China’s agricultural carbon footprint from 2000 to 2020. While the total emissions increased by 21.32% due to chemical fertilizers and energy consumption, the carbon intensity (emissions per value generated) decreased, indicating more economically efficient production over time.

4. 

Technological Intensification and Energy Efficiency

Technology adoption either for assets or for their management through data science can provide more benefits than traditional methods for controlled cultivation [12]. Kalkušová et al. (2025) challenged the idea that high electricity consumption is always environmentally harmful by using Life Cycle Assessment (LCA) on indoor hemp cultivation. They determined that high-intensity systems are more environmentally efficient, because the drastic increase in productivity offsets the additional energy expenditure.

In their study on arid regions, Al-Helal et al. (2025) investigated how the orientation of ventilation openings in greenhouses can improve natural cooling. This “intelligent design” serves as a powerful tool to reduce the reliance on costly mechanical cooling systems and lower the carbon footprint.

5. 

Precision Agriculture and Digitalization (Waste Reduction)

The digitalization of crop production has high potential for monitoring environmental impacts. Since the input utilization determines both the production cost and environmental footprints, two-thirds of sustainability issues are addressed when the material flows of production systems are determined [13].

Peccinelli et al. (2025) integrated Lean Thinking with digital technologies to reduce waste in sugarcane crop protection. By using digital maps and variable rate applications, they reduced pesticide overlap and improved operational efficiency. Tools from total quality management (TQM), similar to those used in technological adoption, supported efficiency improvements and, consequently, reduced the environmental impacts [14].

Finally, Lazar et al. (2025) used hyperspectral cameras and machine learning (with over 94% accuracy) to differentiate tomato plants from weeds. The study identified that using only 10 to 20 specific spectral bands is sufficient, allowing faster data processing, which is essential for real-time robotic field decisions. This study highlights how data science can support decision-making through remote sensing to promote sustainability [15].

Over the next 20 years, biobased production systems, including agriculture, forestry, and livestock, will likely face a paradox. Global food production will need to increase to supply a population of around 10 billion, and it will need to reduce its carbon footprint, water usage, and chemical dependency. There will be room for technology adoption, such as precision agriculture, autonomous and robotic farming, and real-time IoT sensing. Niche markets, either locally or internationally, may rely on natural ecosystem restoration, regenerative agriculture, and carbon-based farming. Further, the search for biological options to replace the chemical control of pests and diseases may pose changes in input management. Water may also benefit from data science to support decision-making in irrigation systems.