Detalhes bibliográficos
Ano de defesa: |
2023 |
Autor(a) principal: |
Gasparotto, Letícia Gonçalves |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Tese
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
eng |
Instituição de defesa: |
Biblioteca Digitais de Teses e Dissertações da USP
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: |
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Link de acesso: |
https://www.teses.usp.br/teses/disponiveis/11/11152/tde-05012024-105912/
|
Resumo: |
Maize is one of the main crops in the world, being the main source of food in Africa, representing 30% of the total production area and 30% of the calories and proteins consumed. Despite Sub-Saharan Africa\'s dependence on maize grain, the crop yield is low compared to its potential, with an average yield of approximately 2 Mg ha-1, which represents 27% of water-limited productivity (Yw). In Brazil, the difference in yield is approximately 50% of Yw. Thus, the objective of this study was to carry out a case study, using rainfed maize as a reference, to identify a set of agricultural areas with similar soils and climates in Brazil and Sub-Saharan Africa (SSA) and then compare the response agronomy between the two producing regions. For this, we identified the similarity of SSA between Brazil and the SSA countries, looking for both occurrences as regions. The Yw data used for this study were estimated by Hybrid Maize crop model and simulations were performed using the local climate data, soil and practices of both continents, such as sowing data and cultivar cycle. Six SSA countries were selected: Ghana, Uganda, Kenya, Nigeria, Zambia and Ethiopia. Actual yields (Ya) were determined by including yields of at least 3 years and were taken from the official databases of the National Statistical Institutes of each country. Climatic data from SSA showed that rainfall and temperature was well distributed at the time, as well as in Brazil. However, the incident radiation was lower than in Brazil, but enough to ensure high Yw. Yw averaged 11.3 and 7.4 Mg ha-1 for Brazil and SSA, respectively. The Ya of maize in SSA was 1.4 Mg ha-1, while in Brazil the Ya was 5.2 Mg ha-1. Ya represented approximately 9% of Yw in SSA. Low Ya explained the large yield gap (Yg) found in SSA. With this, it is evident that the management technologies used and the way of cultivation are largely responsible for the difference in yield between countries. |