Fuzzy logic indicators for the assessment of farming sustainability strategies in a tropical agricultural frontier

Assessing the sustainability of agricultural systems encompasses complex and interchanging economic, environmental and social issues, and requires multi-criteria decision-analysis approaches. Various models have been proposed to assess agricultural sustainability considering these issues, based for example on programs for multi-attribute decision making or Fuzzy Interference Systems. However, we identify a lack of comprehensive models applicable to broad agricultural conditions in different environments and socioeconomic contexts. To fill this gap, we propose a novel, indicator-based fuzzy logic model for assessing the sustainability of agricultural systems. To test the model’s suitability, we conducted twenty-two case studies over the 2018/19 cropping season in the Brazilian agricultural-forest frontier region; the farms chosen represent the three most common farming systems there: (i) pure crop farming (crop rotation only: soybean - corn), (ii) pure livestock, and (iii) integrated farming (crop - livestock and livestock - forest). Partial indicators were built to assess the economic, environmental, and social performances of those farming systems, then were further integrated in a sustainability index. The results show higher and better-balanced performance for integrated farms, which displayed the highest sustainability index values. In contrast, livestock farms performed poorly in all dimensions and showed the lowest sustainability index. Crop farms showed higher economic, but lower social and environmental performances. These results are in contrast to the oft-perceived trade-offs among different pillars of sustainability and show that integrated systems have the potential to balance multiple sustainability objectives, by leveraging multiple subsystem synergies. The innovative fuzzy inference model proposed is suitable to deal with information at the farm level, handling different types of farming systems, and applicable to different environmental or socioeconomic contexts. Moreover, the proposed indicators and associated indices offer relevant information to policy-makers to foster the sustainable intensification of farming systems, while promoting environmental protection and the coexistence of biodiversity and the agricultural sector.