Operations research for environmental assessment of crop-livestock production systems

Abstract CONTEXT Agricultural crop and livestock production systems are complex, essential to human well-being, and fraught with sustainability challenges. In light of intrinsic variability in agricultural production systems and the high number of decision variables, decision support for optimization of sustainability outcomes should be supported by rigorous operations research. OBJECTIVE Several operations research (OR) methods such as evolutionary algorithms, multi-objective optimization, and data envelopment analysis (DEA) have been applied to optimization in agricultural contexts, taking into account different objective functions and decision variables, and life cycle-based evaluation of environmental outcomes in agriculture have become widespread. The current review evaluates the methods used for optimization of agricultural and livestock systems for life cycle-based environmental sustainability goals. METHODS A Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) systematic review method and three complementary search strategies were used to identify relevant articles. Strengths, weaknesses, and performance issues for each method are considered and compared. RESULTS AND CONCLUSIONS Farm benchmarking, output prediction and resource use management are the three most commonly considered decision types in crop-livestock production systems. To guide selection and implementation of appropriate OR methods, a framework (decision tree) is proposed. SIGNIFICANCE The proposed decision tree provides an indication of necessary method-specific methodological choices. Methodological choices with respect to each method are discussed.