Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
Descripción del Articulo
The pathogen Fusarium oxysporum is the major limiting factor in the production of the cape gooseberry crop Physalis peruviana, due to the inexperience of growers to identify and manage it. The objective of this research was to identify the relationship between the chemical characteristics of the soi...
Autores: | , , , , , |
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Formato: | artículo |
Fecha de Publicación: | 2022 |
Institución: | Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua |
Repositorio: | Revistas - Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua |
Lenguaje: | español |
OAI Identifier: | oai:revista.unibagua.edu.pe:article/95 |
Enlace del recurso: | https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95 |
Nivel de acceso: | acceso abierto |
Materia: | APC árbol de decisiones factores predisponentes modelos supervisados decision tree predisposing factors supervised models |
Sumario: | The pathogen Fusarium oxysporum is the major limiting factor in the production of the cape gooseberry crop Physalis peruviana, due to the inexperience of growers to identify and manage it. The objective of this research was to identify the relationship between the chemical characteristics of the soil and the presence and absence of Fusarium oxysporum. Soil samples were collected from 100 cape gooseberry production units. This process was carried out in plots with healthy plants and plants affected by the pathogen Fusarium oxysporum Schltdl. Descriptive analysis, Pearson correlations, principal components (PCA) and Machine Learning models were used to analyze the information associated with the chemical elements of the soil of cape gooseberry farms. The Decision Tree Classifier model showed the best predictive performance with Accuracy metrics of 0.58, Recall of 0.57, and F1 Score of 0.51, allowing to establish that the presence of F. oxysporum is associated with elements such as: Ca, K, Effective Cation Exchange Capacity (ETC), pH and % Sand. Finally, the development of this work is intended to outline predictive models as a tool that can be included in management plans for this disease. |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).