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:
The study aims to categorize cattle production systems in the Peruvian high jungle using multivariate analysis. . Allowing us to identify three distinct production systems with significant socio-economic 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, which 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

Key words: Categorical principal component analysis; Cattle production systems; Farm stability and resilience; High tropical.