Doutoramento em Ciências Agrárias
Inputs and yield optimization on irrigated maize
Anabela Dias Ramalho Vale Leitão Grifo

Orientação:  José Rafael Silva, Maria Manuela Oliveira e Carlos Alberto Alexandre

This dissertation describes efforts to move toward the study of soil and the management of yield variability through research that explored and evaluated the potential of some techniques to provide greater under- standing and know-ledge of an agricultural parcel, even in situations where there is no prior knowledge of its behavior. The first experiment used a principal components analysis (PCA) in the study of the spatial and temporal variability of maize grain yield. The results of this experiment demonstrated that the 1^st  and 2^nd  principal components could be used to identify parcel zones with different spatial and temporal behaviors. The second experiment applied stochastic and sequential Gaussian simulation techniques to spatially and temporally forecast and model maize productivity. This technique enabled the modeling of spatial uncertainty in maize productivity based on probabilistic maps with different confidence levels. The third experiment examined different fertilization input scenarios based on marginal productivity inputs and break-even yields to optimize agronomic, economic and environmental support decisions. According to the results, it is possible to reduce agricultural production costs through the differential management of inputs. The outcomes showed that differential management decisions can maximize returns and reduce activity risk without having to implement major changes on the farm.