Determinants of Sustainable Cattle Farming to Guide Policy and Intervention in Perú - Tafur-Culqui, J.; Gómez-Fernández , D.; Tineo, D.; Cruz-Luis, J.; Taboada-Mitma, V. H.; Quichua-Baldeón, R.; Arce-Inga, M.; Anchayhua, J.; Rabanal-Oyarse, R.; Goñas, M. (Faculty of Animal Science, IPB University, 2025)
The absence of detailed knowledge about the factors that determine the sustainability of cattle farming has led, in many cases, to the formulation of policies and interventions that lack contextual relevance and sensitivity to the structural heterogeneity of livestock farms. The objective of this study was to identify the important factors that determine the sustainability of cattle farming systems through a three-dimensional analytical framework based on 16 key indicators. Based on these factors, this study recommends strategic interventions to improve the environmental stewardship, resilience, productivity, and overall household welfare of cattle farming. Using probability sampling, data were collected from 120 farmers and analyzed using cluster analysis, principal component analysis (PCA), ANOVA, and Spearman correlation. The results revealed five distinct groups of cattle farmers differentiated by the age of the producer, economic dependence on cattle farming, annual yield, land use specialization, water availability, and soil erosion. Of these groups, Group 2 is particularly notable, with the highest sustainability index (64.03%), higher economic income, and greater economic dependence on cattle farming. While older producers with larger farms had higher economic and environmental scores, they also faced challenges such as a greater risk of erosion. By contrast, younger producers had less active but more innovation potential. Agricultural training was moderately related to better water management. These discoveries emphasize the need to formulate public policy and intervention strategies that focus on improving rural areas, diversification, enhancing education and improving ecological practice, while recognizing the heterogeneity of production profiles.