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- W4384077866 abstract "The methodological framework adopted for this study in general, the specific methodology used for the four scientific studies (Chaps. 3 – 6 ) related to plant health and banana productivity in Venezuela, as well as the research strategies that led to the results are developed searched results. This research was structured according to four ways of approaching the study in banana areas. This chapter describes the application of different machine learning algorithms in banana production systems in Venezuela through four different topics: (a) a systematic review and bibliometric analysis of the agro-environmental factors that determine the appearance of Fusarium oxysporum f. sp. cubense Tropical Race 4 (Foc TR4) and the risk analysis and climatic suitability maps for (syn. Fusarium odoratissimum) in Venezuela through the maximum entropy model; (b) the relationship between soil properties and the incidence of banana wilt (MB) through Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) and the random forest (RF) algorithm; (c) an analysis of the relationship between main physical, chemical, and biological soil properties most correlated to banana productivity; and (d) the potential use of soil morphological properties to differentiate banana productivity levels under Venezuelan conditions through a prediction model based on categorical soil properties with regularized optimal scaling regression." @default.
- W4384077866 created "2023-07-13" @default.
- W4384077866 creator A5018053142 @default.
- W4384077866 date "2023-01-01" @default.
- W4384077866 modified "2023-09-24" @default.
- W4384077866 title "Methodological Framework" @default.
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- W4384077866 doi "https://doi.org/10.1007/978-3-031-34475-6_2" @default.
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