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Timm,Luís Carlos; Gomes,Daniel Takata; Barbosa,Emanuel Pimentel; Reichardt,Klaus; Souza,Manoel Dornelas de; Dynia,José Flávio. |
The study of soil property relationships is of great importance in agronomy aiming for a rational management of environmental resources and an improvement of agricultural productivity. Studies of this kind are traditionally performed using static regression models, which do not take into account the involved spatial structure. This work has the objective of evaluating the relation between a time-consuming and "expensive" variable (like soil total nitrogen) and other simple, easier to measure variables (as for instance, soil organic carbon, pH, etc.). Two important classes of models (linear state-space and neural networks) are used for prediction and compared with standard uni- and multivariate regression models, used as reference. For an oat crop... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil attributes; Prediction models; Spatial transect; Latent variables. |
Ano: 2006 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000400010 |
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