Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil

Evaluating and characterizing production systems using farm characteristics allows the diagnosis of failing points. This diagnosis can be used to improve the productive and zootechnical indices. Little is known about the milk production systems in the state of Rio Grande do Sul, therefore, the aim of this study was to characterize the milk production systems of the Northwest, Center Western and Southwest mesoregions of Rio Grande do Sul, considering the infrastructure, milk handling, milk quantity and composition, and nutritional intake of the cattle. To conduct this study, 38 Milk Production Units (MPUs) registered at the Municipal Secretaries of Agriculture and Emater/Ascar-RS were randomly selected. After being randomly selected, the dairy farms were visited and a semi-structured guide questionnaire was applied and milk samples were collected from expansion tanks. The milk was analyzed for somatic cell counts (SCC) and total bacterial counts (TBC). Data were evaluated through principal component analysis and cluster analysis. Multivariate analysis allowed the investigated variables to be reduced into two main components (CP1 and CP2). These two showed eigenvalues ​​greater than 1 (alpha> 1) and together explained 55.05% of the characteristics variability of the 38 MPUs studied. CP1 contemplated productive capacity and factors related to nutritional management of the MPUs, interfering directly with reproductive performance. CP2 comprised milk handling and daily production. Using these main variables, the data set generated from the 38 MPUs studied were adjusted and classified into five groups (G1, G2, G3, G4, and G5). The characteristics of these groups differed statistically especially in infrastructure and nutritional management of the cattle. Due to their particularities, each of these five groups of MPUs requires strategic technical interventions to improve their productive indexes