Sustainability of livestock farms: The case of the district of Moyobamba, Peru

• Autores: Durand Chávez, Luz Marlene, Quispe Ccasa, Hurley Abel, Linares Rivera, Jaime Lizardo, Segura Portocarrero, Gleni Tatiana, Calderón Tito, René, Vásquez Pérez, Héctor Vladimir, Maicelo Quintana, Jorge Luis, Ampuero Trigoso, Gustavo, Robles Rodríguez, Rafael René, Saucedo Uriarte, José Américo
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:null:20.500.12955/2091
• Enlace del recurso: https://hdl.handle.net/20.500.12955/2091; https://doi.org/10.1016/j.heliyon.2023.e13153
• Nivel de acceso: acceso abierto
• Materia: Amazon region; Conglomerates; Livestock; Soil quality; Sustainable development; https://purl.org/pe-repo/ocde/ford#4.02.01; Amazonia; sustainable development

The Peruvian Amazon is a geographical area with great biodiversity, where the main economic activities are agricultural crops and grazing animals. The evaluation of sustainability in production systems is based on the analysis of economic, environmental and social components, which are variable between production units or livestock farms. The classification of livestock farms based on their characteristics of similarity and differences can contribute to the most appropriate assessment of their level of sustainability. The objective of this research was to determine the level of sustainability of livestock farms in the district of Moyobamba, San Martín, Peru, based on environmental, economic and social criteria. The research was carried out from November 2018 to February 2019 with a survey of a sample of 60 livestock farms out of a population of 2220. A survey-type form and data collection in the field were applied, adapting a methodology that proposes inferring on 33 indicators grouped into six criteria: three environmental criteria (soil quality, pasture health and animal quality), two economic criteria (farm system and farm economy), and a social criterion of the farm. A scale from 1 to 10 was used to assess the condition of each indicator. The typification of farms was carried out through a Conglomerate Analysis. To analyze the level of sustainability, Amoeba graphs were constructed for each defined farm group. Qualitative variables were analyzed with contingency tables and quantitative variables using the T test (p < 0.05). Three types of livestock farms were identified, differentiated by level of education, farm size, years in cattle raising and number of cattle heads (p < 0.05), where Group 1 is less experienced, Group 1 has more area and cattle, and Group 3 only have older years in livestock. There were significant differences between the evaluated criteria and the sustainability index. From the typification of livestock farms, Group 2 (13 farms) presented a higher level of sustainability as did Group 3 (16 farms), while Group 1 (31 farms).