Examinando por Autor "Paredes Chocce, Miguel Enrique"

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Characterization of dairy goat production systems in coastal valleys of the Lima region
(Springer, 2024-10-23) Paredes Chocce, Miguel Enrique; Ramírez Vergara, Raúl Omar; Trillo Zárate, Fritz Carlos; Cruz Luis, Juancarlos Alejandro
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.
Cross‑sectional study of gastrointestinal helminthosis in goats from three ecosystems in Peru: Prevalence and associated factors
(Springer Nature, 2025-11-03) Castillo Doloriert, Hugo; Paredes Chocce, Miguel Enrique; Vargas Calla, Ana; Robles Noriega, Katherine; Godoy Padilla, David; Coronel Berrospi, Sebastian; Ayala Roldan, Richard David; Acosta Granados, Irene Carol; Gomez Puerta, Luis A.
Gastrointestinal parasitism is a health issue in livestock, particularly in non-intensive farming systems. This research evaluated the prevalence and risk factors associated with gastrointestinal helminths in goats from three ecosystems in Peru: the Andean shrubland (Ancash), dry forest (Lambayeque), and coastal valley (Lima). The study used a cross-sectional design, with random sampling of goats from extensive production systems in each ecosystem. A total of 819 fecal samples were collected and analyzed using qualitative and quantitative parasitological methods. Additionally, coproculture was performed to identify infective larvae of nematodes. The FAMACHA© index was used to assess anemia levels, while body condition scores were recorded to evaluate the nutritional status of the animals. The highest prevalence was recorded in the Andean shrubland (74.2%), followed by the dry forest (63.1%), whereas the coastal valley had the lowest prevalence (59.3%). The most frequently identified helminths were strongyle-type eggs (49.9%) and Skrjabinema sp. (33.7%), while Moniezia sp. (5.4%) and Fasciola hepatica (1.1%) were detected at lower frequencies. The identification of L3 infective larvae of Haemonchus sp., Trichostrongylus sp., Cooperia sp., Strongyloides sp., Oesophagostomum sp., Bunostomum sp., and Teladorsagia sp. highlighted the diversity of gastrointestinal nematodes affecting goats in Peru. Multivariable analysis revealed that anemia (FAMACHA ≥ 3; PR = 1.14), poor body condition (BCS 1–2; PR = 1.03), and age (2–6 teeths or full dentition; PR = 1.12 and 1.08, respectively) were associated with increased infection risk. Males had lower prevalence than females (PR = 0.80), and goats raised in the dry forest and coastal valley had lower risk than those from the Andean shrubland. These findings highlight the influence of physiological status and environmental conditions on parasite burden in goat herds.
Short Communication: Prediction of body weight using morphometric measurements in Creole goats from Peru
(Society for Indonesian Biodiversity, 2025-07-15) Paredes Chocce, Miguel Enrique; Sessarego Davila, Emmanuel Alexander; Tafur Gutierrez, Lucinda; Temoche Socola, Victor Alexander; Salinas Marco, Jorge; Acosta Granados, Irene Carol; Ruiz Chamorro, Jose Antonio; Cruz Luis, Juancarlos Alejandro; Trillo Zarate, Fritz Carlos
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.
Using biometric analysis to estimate body weight in Creole goats
(Eldaghayes Publisher, 2025-09-30) Trillo Zárate, Fritz Carlos; Paredes Chocce, Miguel Enrique; Salinas Marcos, Jorge; Temoche Socola, Víctor Alexander; Tafur Gutiérrez, Lucinda; Sessarego Dávila, Emmanuel Alexander; Acosta Granados, Irene Carol; Palomino Guerrera, Walter; Cruz Luis, Juancarlos Alejandro; Ruiz Chamorro, Jose Antonio
Background: Creole goat husbandry for milk and meat improves food security in rural areas in Perú. Body weight (BW) is a key trait for selecting breeding stock, and it is estimated to be using algorithms. Likewise, BW is common in livestock farming. Aim: This study aimed to compare BW prediction models using a data mining algorithm in Creole goats, considering their biometric measurements. Methods: Data from 1,075 females aged between 1 and 4 years were used. Measurements of chest width, thoracic perimeter, wither height, sacrum height, rump width and length, body length, cannon bone perimeter, age, and region of the herd were recorded. The regression trees (classification and regression tree), support vector regression (SVR), and random forest regression (RFR) algorithms were used. Results: The SVR was better at predicting BWs in Creole goat herds. Similarly, the results were stable during training (R² = 0.765) and testing (R² = 0.707). However, it should be noted that RFR performed better with training data (R² = 0.942). Conclusion: The proposed predictive models have demonstrated significant potential for accurately predicting BW based on biometric data. Finally, it contributes to better selection, feeding, and sanitary management of Creole goats.