Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL

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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...

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Autores: Cruz-Castiblanco, Ginna, Pérez-Caro, Wilmer, Martínez-Lemus, Erika, Sandoval-Cáceres, Yuly, Wilches-Ortiz, Wilmar, Villa-Triana, Alba
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
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dc.title.none.fl_str_mv Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
Modelo de estimación para relacionar factores de suelo asociados con la presencia y ausencia de Fusarium oxysporum Schltdl en el cultivo de uchuva Physalis peruviana L
title Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
spellingShingle Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
Cruz-Castiblanco, Ginna
APC
árbol de decisiones
factores predisponentes
modelos supervisados
APC
decision tree
predisposing factors
supervised models
title_short Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
title_full Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
title_fullStr Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
title_full_unstemmed Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
title_sort Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaL
dc.creator.none.fl_str_mv Cruz-Castiblanco, Ginna
Pérez-Caro, Wilmer
Martínez-Lemus, Erika
Sandoval-Cáceres, Yuly
Wilches-Ortiz, Wilmar
Villa-Triana, Alba
author Cruz-Castiblanco, Ginna
author_facet Cruz-Castiblanco, Ginna
Pérez-Caro, Wilmer
Martínez-Lemus, Erika
Sandoval-Cáceres, Yuly
Wilches-Ortiz, Wilmar
Villa-Triana, Alba
author_role author
author2 Pérez-Caro, Wilmer
Martínez-Lemus, Erika
Sandoval-Cáceres, Yuly
Wilches-Ortiz, Wilmar
Villa-Triana, Alba
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv APC
árbol de decisiones
factores predisponentes
modelos supervisados
APC
decision tree
predisposing factors
supervised models
topic APC
árbol de decisiones
factores predisponentes
modelos supervisados
APC
decision tree
predisposing factors
supervised models
description 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.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-28
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95
url https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95/110
https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95/163
https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95/233
dc.rights.none.fl_str_mv Derechos de autor 2022 Revista Científica Dékamu Agropec
https://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2022 Revista Científica Dékamu Agropec
https://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
audio/mpeg
dc.publisher.none.fl_str_mv Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua (UNIFSLB)
publisher.none.fl_str_mv Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua (UNIFSLB)
dc.source.none.fl_str_mv Revista Científica Dékamu Agropec; Vol. 3 No. 2 (2022): Revista Científica Dékamu Agropec; 14-25
Revista Científica Dékamu Agropec; Vol. 3 Núm. 2 (2022): Revista Científica Dékamu Agropec; 14-25
2709-3190
2709-3182
10.55996/dekamuagropec.v3i2
reponame:Revistas - Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua
instname:Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua
instacron:UNIBAGUA
instname_str Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua
instacron_str UNIBAGUA
institution UNIBAGUA
reponame_str Revistas - Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua
collection Revistas - Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua
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spelling Estimation model to relate soil factors associated with the presence and absence of Fusarium oxysporumSchltdl in the cape gooseberry crop Physalis peruvianaLModelo de estimación para relacionar factores de suelo asociados con la presencia y ausencia de Fusarium oxysporum Schltdl en el cultivo de uchuva Physalis peruviana L Cruz-Castiblanco, GinnaPérez-Caro, Wilmer Martínez-Lemus, Erika Sandoval-Cáceres, Yuly Wilches-Ortiz, Wilmar Villa-Triana, AlbaAPCárbol de decisionesfactores predisponentesmodelos supervisadosAPCdecision treepredisposing factorssupervised modelsThe 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.El patógeno Fusarium oxysporum es la mayor limitante en la producción del cultivo de uchuva Physalis peruviana, a causa de la inexperiencia de los productores para identificarlo y manejarlo. En ese sentido el objetivo de esta investigación fue identificar la relación entre las características químicas del suelo, con la presencia y ausencia de Fusarium oxysporum. La recolección de muestras de suelo fue de 100 unidades productoras uchuva. Este proceso fue realizado en parcelas con plantas sanas y plantas afectadas por el patógeno Fusarium oxysporum Schltdl. Se empleó los análisis descriptivos, correlaciones de Pearson, componentes principales (APC) y modelos Machine Learning para analizar la información asociada a los elementos químicos del suelo, de fincas productoras de uchuva. El modelo Decision Tree Classifier mostró el mejor rendimiento predictivo con métricas de Accuracy de 0.58, Recall de 0.57, y el F1 Score de 0.51, permitiendo establecer que la presencia de F. oxysporum está asociada a elementos como: Ca, K, Capacidad de intercambio catiónico efectiva (CICE), pH y % Arena. Los hallazgos en esta investigación son de utilidad para perfilar modelos predictivos y que se podrían incluir en los planes de manejo de esta enfermedad.Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua (UNIFSLB)2022-12-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlaudio/mpeghttps://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95Revista Científica Dékamu Agropec; Vol. 3 No. 2 (2022): Revista Científica Dékamu Agropec; 14-25Revista Científica Dékamu Agropec; Vol. 3 Núm. 2 (2022): Revista Científica Dékamu Agropec; 14-252709-31902709-318210.55996/dekamuagropec.v3i2reponame:Revistas - Universidad Nacional Intercultural Fabiola Salazar Leguía de Baguainstname:Universidad Nacional Intercultural Fabiola Salazar Leguía de Baguainstacron:UNIBAGUAspahttps://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95/110https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95/163https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/95/233Derechos de autor 2022 Revista Científica Dékamu Agropechttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessoai:revista.unibagua.edu.pe:article/952024-08-13T17:11:08Z
score 13.02468
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