Characterization of goat production systems in the Amazonian dry tropical forest of Peru through multivariate analysis

Abstract

The study aimed to characterize goat production systems in the tropical dry forest of Peru through multivariate analysis of 25 socioeconomic and productive variables in 60 producers from Bagua Grande, El Milagro, Cajaruro, and Cumba. Descriptive analysis, multidimensional scaling (stress = 0.03272), categorical principal component analysis (CATPCA), and hierarchical clustering analysis (HCA) were applied. A predominance of extensive management (98.3%), with low technical assistance (81.7%), absence of irrigation (90%), and visual selection of animals (100%) was identified. Marketing responds to immediate economic needs (36.7%), while vaccination coverage is poor (88.3% not vaccinated). CATPCA explained 54.5% of the variance (Cronbach's alpha = 0.965), highlighting producer education, infrastructure, and access to water and energy as key factors for improving production efficiency and mitigating commercial seasonality. HCA identified two goat production systems: the improved extensive system (EES) and the traditional extensive system (TES). The EES grouped older and more experienced producers, with larger herds, higher sales weights, greater specialization, forage diversification, better infrastructure, and higher deworming frequency. In contrast, the TES included younger producers with smaller herds, lower sales weights, lower educational levels, agricultural dependence, less forage diversity, limited infrastructure, and limited sanitary measures. These differences highlight the impact of knowledge and technological development on productive sustainability. It is concluded that technological development, access to resources, and production experience are key to improving the efficiency and sustainability of goat systems in the tropical dry forests of Peru.