Abstract

BARDALES ESCALANTE, William; MAICELO QUINTANA, Jorge L.  and  CORROTO, Fernando. Plants used in traditional veterinary medicine of the montane forests in northern Peru: socioeconomic aspects and knowledge transmission. Rev. investig. vet. Perú [online]. 2020, vol.31, n.2, e16325. ISSN 1609-9117.  http://dx.doi.org/10.15381/rivep.v31i2.16325.

The veterinary use of medicinal plants practiced by the population of two cattle regions in the montane forests of northern Peru were compared. The objectives of the study were: (1) to collect information on veterinary uses and medicinal plants typical of two cattle regions in the Amazonas Department: Leimebamba and Molinopampa districts; (2) evaluate the influence of socioeconomic factors on veterinary knowledge about medicinal plants; (3) understand the transmission of traditional knowledge between age groups (18-30, 31-40, 41-50, 51-60, >60 years). Semi-structured interviews were carried out (n=120), complementing ethnobotanical questions on socioeconomic aspects. The weight of the socioeconomic factors in the knowledge about medicinal plants and veterinary uses of each basin was done through a multidimensional scaling. In addition, mixed linear models and Fisher’s LSD test were used to determine differences between age groups. It was recorded 72 species from 33 plant families. The number of species and veterinary uses mentioned was higher in the Molinopampa district, characterized by having a lower level of development than the Leimebamba district. The scatter plot separated the localities of each district between them. Traditional knowledge showed an increase according to age, with a decrease in the older group. In conclusion, traditional knowledge about medicinal plants for veterinary applications is widely used among the population of the montane forests of northern Peru, with a negative influence in terms of socio-economic improvements, with a transmission to young people, not uniform but constant.

Keywords : veterinary uses; medicinal plants; mixed models; multidimensional scaling; Amazonas.

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