MODELLING THE PASTURELAND PRODUCTIVITY IN AREAS OF SAVANNA IN NORTHERN MINAS GERAIS – BRAZIL

• Autor(a) principal: da Silva, Lucas Augusto Pereira
• Data de Publicação: 2022
• Outros Autores: Bolfe, Édson Luís, Ferreira, Manuel Eduardo, Veloso, Gabriel Alves, Laurentino, Carla Milena de Moura, da Silva, Claudionor Ribeiro
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Caminhos de Geografia
• Texto Completo: https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59046
• topic: Remote Sensing; Animal Unit; Dry Matter; Dry Matter; Animal Unit; Remote Sensing

Accurate information on the quality of pastures is essential for the Brazilian economy, as livestock is relevant to the country's Gross Domestic Product (GDP); in addition, well-managed pastures are a necessary step to mitigate the emission of greenhouse gases (GHG). In this work, the productivity of pastures in savanna areas in northern Minas Gerais (Brazil) was analyzed using remote sensing techniques. It was found that dry biomass varied according to climatic seasonality, on the monthly time scale, with the highest values in the rainy season (68.79%) and the lowest in the dry period (31.21%). To observe the importance of well-managed pastures for the studied region, a correlation of environmental parameters that assume the quality of these pasturelans was carried out. We observed a more significant correlation between Gross Primary Production (GPP)), Leaf Area Index/Photosynthetically Active Radiation Absorbed (IAF/RFAA) and altitude with the dry biomass capacity of the Animal Unit (UA / Hectare). We observed that the pastures in the study region do not have enough inputs to meet the needs of the animals, thinking about the intensification logic, mainly when comparing the annual average of AU/ha of this study with the Brazilian median, with a difference of 86.37 %.