Exploring the microbiome of two uterine sites in cows.

Bacterial communities in the mammalian reproductive system can be rich and diverse, differing in structure and quantity depending on location. In addition, its microbiome is associated with the state of health of this tract and reproductive success. This study evaluated the microbiome composition of the uterine body (UB) and uterine horn mucosa (UH) samples using 16S rRNA sequencing of samples extracted from cows in the Amazon region. It was observed that four main phyla were shared between the uterine sites: Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. Linear discriminant analysis effect size and heat tree analysis showed that members of Lachnospiraceae (NK3A20 group) and Oscillospiraceae were significantly more abundant in the UB than in UH. In addition, there are more unique genera in the UB than in the UH. A higher bacterial load in UB than in UH is expected because of the exposure to external factors of UB. However, comparing the site's communities through beta diversity did not generate well-defined clustering. Thus, it can be attributed to the closeness of the sites, which would make the niches similar ecologically and microbiologically. Therefore, this research provides knowledge to understand biomarkers in the prior reproduction period.

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

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) presented unsustainable conditions. The environmental indicators based on animal quality and farm system show unsustainability in all farms the District of Moyobamba, as they fail to exceed the threshold of sustainability (5).