Lessons learned from the root and crown rot associated with Neopestalotiopsis rosae epidemics in Mexican strawberry production systems: A retrospective analysis based on data science

Abstract Background : The emergence of Neopestalotiopsis rosae , causing root rot, crown rot, and leaf spot of strawberry, resulted in a major phytosanitary crisis in Mexico, with yield losses reaching 70%. This study reconstructs how growers in central Mexico responded to and managed the epidemic, synthesizing survey data from the 2019–2020, 2021–2022, and 2022–2023 growing seasons. Methods : Observational data from regional surveys of commercial fields, plant-propagation fields, and nurseries were integrated and analyzed using linear discriminant analysis with sequential feature selection, linear mixed-effects models (meta-analysis), and spatial statistics (Getis-Ord Gi* and kernel density estimation). This combination established a rapid, reproducible framework for plant disease epidemiology in production systems requiring immediate, evidence-based responses, enabling pattern detection across successive epidemic stages despite heterogeneous data sources. Results : Nurseries, particularly bare-root propagation systems, were identified as a primary source of N. rosae inoculum into commercial fields. Symptomatic plants harboring multiple co-occurring fungal and oomycete genera reached mortality of up to 40%, versus below 10% with a single genus. Strawberry variety factor was the dominant driver of mortality (random-effect variance = 0.69; marginal R 2 = 0.13, conditional R 2 = 0.42), triggering a shift from high-susceptibility to more tolerant varieties. In Tangancícuaro, the only site surveyed across all three seasons, mortality fell from severe early levels to below 5% by 2022–2023, tracking the transition from reactive interventions toward targeted, data-based management. Conclusions : Integrating data science and meta-analysis converted multi-year, multi-source observational data into actionable knowledge. Two priorities emerged directly: phytosanitary certification of bare-root and plug plants as the critical control point, and replacement of highly susceptible cultivars (e.g., ‘Festival’, ‘Camino Real’, ‘Albion’) with less-susceptible ones (e.g. ‘Adelanto’, ‘Victor’). This transferable framework supports epidemic management in short-cycle, high-risk cropping systems when classical experimental approaches are not yet feasible.

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Journal
CABI Agriculture and Bioscience
Published
2026-08-27
DOI
https://doi.org/10.1079/ab.2026.0057
Primary Topic
Berry genetics and cultivation research
Type
article
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article

Lessons learned from the root and crown rot associated with Neopestalotiopsis rosae epidemics in Mexican strawberry production systems: A retrospective analysis based on data science

Laura A. Valbuena-Gaona, Joaquin Guillermo Ramirez-Gil, Hilda Silva-Rojas, José L. Zárate-Valdez et al.
CABI Agriculture and Bioscience
Berry genetics and cultivation research
article

Lessons learned from the root and crown rot associated with Neopestalotiopsis rosae epidemics in Mexican strawberry production systems: A retrospective analysis based on data science

Laura A. Valbuena-Gaona, Joaquin Guillermo Ramirez-Gil, Hilda Silva-Rojas, José L. Zárate-Valdez, Felipe de J. González-García, Martínez-Ruiz Merari, Santos Gerardo Leyva-Mir, Uriel Acosta González, Angel Rebollar-Alviter
article en

Abstract

Abstract Background : The emergence of Neopestalotiopsis rosae , causing root rot, crown rot, and leaf spot of strawberry, resulted in a major phytosanitary crisis in Mexico, with yield losses reaching 70%. This study reconstructs how growers in central Mexico responded to and managed the epidemic, synthesizing survey data from the 2019–2020, 2021–2022, and 2022–2023 growing seasons. Methods : Observational data from regional surveys of commercial fields, plant-propagation fields, and nurseries were integrated and analyzed using linear discriminant analysis with sequential feature selection, linear mixed-effects models (meta-analysis), and spatial statistics (Getis-Ord Gi* and kernel density estimation). This combination established a rapid, reproducible framework for plant disease epidemiology in production systems requiring immediate, evidence-based responses, enabling pattern detection across successive epidemic stages despite heterogeneous data sources. Results : Nurseries, particularly bare-root propagation systems, were identified as a primary source of N. rosae inoculum into commercial fields. Symptomatic plants harboring multiple co-occurring fungal and oomycete genera reached mortality of up to 40%, versus below 10% with a single genus. Strawberry variety factor was the dominant driver of mortality (random-effect variance = 0.69; marginal R 2 = 0.13, conditional R 2 = 0.42), triggering a shift from high-susceptibility to more tolerant varieties. In Tangancícuaro, the only site surveyed across all three seasons, mortality fell from severe early levels to below 5% by 2022–2023, tracking the transition from reactive interventions toward targeted, data-based management. Conclusions : Integrating data science and meta-analysis converted multi-year, multi-source observational data into actionable knowledge. Two priorities emerged directly: phytosanitary certification of bare-root and plug plants as the critical control point, and replacement of highly susceptible cultivars (e.g., ‘Festival’, ‘Camino Real’, ‘Albion’) with less-susceptible ones (e.g. ‘Adelanto’, ‘Victor’). This transferable framework supports epidemic management in short-cycle, high-risk cropping systems when classical experimental approaches are not yet feasible.

CABI Agriculture and Bioscience
Chapingo Autonomous University (MX), Universidad Nacional de Colombia (CO), Colegio de Postgraduados (MX)
Reduced inequalities
Openalex Percentile: Top 12%
Berry genetics and cultivation research
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