Goat farming in Peru is a husbandry activity that, although it is considered secondary in the country, has a great economic and social impact on the rural population, that is why government efforts to develop is so important. The objective of this study was to characterize dairy goat rearing systems in the coastal valleys of the Lima region to identify gaps and opportunities for improvement. This cross-sectional research was conducted in four provinces located in the Lima region, Peru. A total of 62 goat farmers participated in the trial. For data collection, a standard survey was prepared with open and closed questions distributed across two components (socioeconomic and productive). The surveys were processed for qualitative variables using a multiple correspondence analysis (MCA) followed by a hierarchical cluster analysis (HCA) to differentiate the types of farming systems prevalent based on the survey population. The hierarchical cluster analysis resulted in the formation of three separate groups of goat farmers, which can be classified as extensive systems differentiated by management practices and their production and marketing objectives. The test showed a significant difference; therefore, it can be affirmed that they are associated with the groups or clusters formed. These results will allow actors related to goat farming, such as state and regional entities, to focus efforts on addressing specific demands of the different types of goat farmers found in this study.

Peruvian Creole goats (PCGs) represent a unique genetic resource shaped by adaptation to diverse environments and traditional breeding practices. In this study, we performed a genomic analysis of six regional populations (Ancash, Ica, Lambayeque, Lima, Piura, and Tumbes) using high-density SNP genotype data. Principal component analysis revealed a moderate genetic structure, with the Ica population showing clear separation and northern populations exhibiting overlap. Runs of homozygosity were predominantly short, and specific regions on chromosome 6 were shared across populations. Inbreeding coefficients were generally low, with Ancash showing the highest values. Linkage disequilibrium decayed rapidly over genetic distance, especially in Piura, indicating higher genetic diversity. Estimates of effective population size revealed decreasing trends across populations, with Piura maintaining the largest recent population size. These findings offer valuable insights into the population structure of Peruvian Creole goats, providing guidance for conservation and sustainable breeding efforts.

Paredes-Chocce M, Sessarego E, Tafur L, Temoche V, Salinas J, Acosta I, Ruiz J, Cruz J, Trillo F. 2025. Short Communication: Prediction of body weight using morphometric measurements in Creole goats from Peru. Biodiversitas 26: 3193-3198. Goats are an important component of smallholder family farms along the coast and highlands of Peru. The weight of an animal is an important indicator of the production and economy of farmers in rural areas. Therefore, this study aimed to develop predictive models for Body Weight (BW) using Morphometric Measurements (MM) of Creole goats (Capra hircus) in Perú. BW and five MM were collected from 356 goats from the coast and highlands of Peru. Variables were analyzed using correlation and stepwise regression analysis to select the best model based on the coefficient of determination (r2), adjusted r2, Residual Standard Error (RSE), and Akaike Information Criterion (AIC) using the RStudio statistical software. The highest correlation was found between BW and TG (0.76), followed by RW (0.67), and RH (0.65). The combinations of MM selected as predictors of BW by stepwise regression were TG, RH, and RW, with r2: 0.640. The selected candidate model met all established tests and, upon validation, reached an r2 of 0.66 (p<0.001), indicating that the model can adequately predict the BW of Peruvian Creole goats and serve as a practical tool to support selection programs, feeding strategies, and market decision-making in smallholder systems.