Data/hora: 21/09/2024 21:43:24

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	03/06/2022	
Data da última atualização: 	03/06/2022	
Autoria: 	SILVA, L. A. P. da; BOLFE, E. L.; FERREIRA, M. E.; VELOSO, G. A.; LAURENTINO, C. M. de M.; SILVA, C. R. da.	
Afiliação: 	LUCAS AUGUSTO PEREIRA DA SILVA, UFU; EDSON LUIS BOLFE, CNPTIA; MANUEL EDUARDO FERREIRA, UFG; GABRIEL ALVES VELOSO, UFPA; CARLA MILENA DE MOURA LAURENTINO, UNIMONTES; CLAUDIONOR RIBEIRO DA SILVA, UFU.	
Título: 	Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.	
Ano de publicação: 	2022	
Fonte/Imprenta: 	Caminhos de Geografia, v. 23, n. 87, p. 124-134, jun. 2022.	
DOI: 	https://doi.org/10.14393/RCG238759046	
Idioma: 	Inglês	
Conteúdo: 	ABSTRACT. 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 %.	
Palavras-Chave: 	Animal Unit; Dry Matter; Modelagem de produtividade de pastagem; Produtividade de pastagem; Unidade animal.	
Thesagro: 	Matéria Seca; Sensoriamento Remoto.	
Thesaurus Nal: 	Pastures; Remote sensing.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1143709/1/AP-Modelling-pastureland-2022.pdf	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (21215-1) - UPC - AP - DD -  -  -  - DIS