Multivariate characterization and typology of cattle production systems in the high jungle of Peru: Insights for improving sustainability and productivity

Abstract

Background: In Peru's high tropical region, cattle production systems exhibit low productivity, largely due to heterogeneous management practices influenced by diverse environmental and socioeconomic conditions. Aim: This study aims to categorize cattle production systems in the Peruvian high jungle using multivariate analysis. This allows us to identify three distinct production systems with significant socioeconomic and technological differences. Methods: A survey was conducted among 210 cattle producers from the districts of Oxapampa, Chontabamba, and Huancabamba, located in the Pasco department (Peru). Categorical principal component analysis (CATPCA) and hierarchical cluster analysis (HCA) were applied to group farms with similar productive features. This classification produced meaningful typologies that can inform tailored management practices and policy decisions. Results: CATPCA explained 22.46% of the total variance, identifying milk production, cattle dosing, and cow culling age as key factors. HCA revealed three distinct production systems that differed significantly (p < 0.05) across social, farm and pasture management, animal production, and economic-financial components: (1) Traditional Extensive System representing 17.14% of producers, characterized by low educational level and limited technology use. Farms are small, rely mainly on natural pastures, experience high pest incidence, and have low milk yield (36–50 L/day), with production primarily destined for self-consumption; (2) Improved Dual-Purpose Extensive System comprising 78.09% of producers, characterized by intermediate level of educational and technology adoption, diversified farm activities, effective pest control, moderate milk production (60–80 L/day), and varied milk marketing destination; and (3) Semi-Intensive System 4.77% of producers, characterized by higher education levels, mixed land use, aging pastures, high milk yield (140–150 L/day), and milk marketed mainly to dairy plants. Conclusion: The distinct characteristics of each system highlight the need for regional livestock extension programs that combine technical training, knowledge exchange, and participatory innovation with remote sensing and geospatial tools to monitor pastures, stocking rates, water resources, and land-use changes.