Modeling the Airborne Inoculum of Polystigma amygdalinum to Optimize Fungicide Programs Against Almond Red Leaf Blotch
Red leaf blotch (RLB) of almond, caused by the ascomycete Polystigma amygdalinum, is a severe foliar disease endemic in the Mediterranean Basin and Middle East. Airborne ascospores of P. amygdalinum were monitored from 2019 to 2021 in two almond orchards in Lleida, Spain, and a Bayesian beta regress...
| Main Authors: | , , , , , , |
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| Format: | article |
| Language: | Inglés |
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APS
2024
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| Online Access: | https://hdl.handle.net/20.500.11939/8980 https://apsjournals.apsnet.org/doi/abs/10.1094/PDIS-08-23-1540-RE |
| _version_ | 1855032889757925376 |
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| author | Pons-Solé, Gemma Torguet, Laura Marimon, Neus Miarnau, Xavier Lázaro, Elena Vicent, Antonio Luque, Jordi |
| author_browse | Luque, Jordi Lázaro, Elena Marimon, Neus Miarnau, Xavier Pons-Solé, Gemma Torguet, Laura Vicent, Antonio |
| author_facet | Pons-Solé, Gemma Torguet, Laura Marimon, Neus Miarnau, Xavier Lázaro, Elena Vicent, Antonio Luque, Jordi |
| author_sort | Pons-Solé, Gemma |
| collection | ReDivia |
| description | Red leaf blotch (RLB) of almond, caused by the ascomycete Polystigma amygdalinum, is a severe foliar disease endemic in the Mediterranean Basin and Middle East. Airborne ascospores of P. amygdalinum were monitored from 2019 to 2021 in two almond orchards in Lleida, Spain, and a Bayesian beta regression was used to model its seasonal dynamics. The selected model incorporated accumulated degree-days (ADD), ADD considering both vapor pressure deficit and rainfall as fixed effects, and a random effect for the year and location. The performance of the model was evaluated in 2022 to optimize RLB fungicide programs by comparing the use of model predictions and action thresholds with the standard program. Two variants were additionally considered in each program to set the frequency between applications, based on (i) a fixed frequency of 21 days or (ii) specific meteorological criteria (spraying within 7 days after rainfalls greater than 10 mm, with daily mean temperatures between 10 and 20°C, and with a minimum frequency of 21 days between applications). Programs were evaluated in terms of RLB incidence and number of applications. The program based on the model with periodic fungicide applications was similarly effective as the standard program, resulting only in a 2.6% higher RLB incidence but with fewer applications (three to four, compared with seven in the standard program). When setting the frequency between applications by using the meteorological criteria, a higher reduction in the number of applications (two to three) was observed, while RLB incidence increased by roughly 16% in both programs. Therefore, the model developed in this study may represent a valuable tool toward a more sustainable fungicide schedule for the control of almond RLB in northeast Spain. |
| format | article |
| id | ReDivia8980 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | APS |
| publisherStr | APS |
| record_format | dspace |
| spelling | ReDivia89802025-04-25T14:49:42Z Modeling the Airborne Inoculum of Polystigma amygdalinum to Optimize Fungicide Programs Against Almond Red Leaf Blotch Pons-Solé, Gemma Torguet, Laura Marimon, Neus Miarnau, Xavier Lázaro, Elena Vicent, Antonio Luque, Jordi Decision support system Disease control Modeling Polystigma amygdalinum Red leaf blotch H20 Plant diseases Epidemiology Prunus dulcis Red leaf blotch (RLB) of almond, caused by the ascomycete Polystigma amygdalinum, is a severe foliar disease endemic in the Mediterranean Basin and Middle East. Airborne ascospores of P. amygdalinum were monitored from 2019 to 2021 in two almond orchards in Lleida, Spain, and a Bayesian beta regression was used to model its seasonal dynamics. The selected model incorporated accumulated degree-days (ADD), ADD considering both vapor pressure deficit and rainfall as fixed effects, and a random effect for the year and location. The performance of the model was evaluated in 2022 to optimize RLB fungicide programs by comparing the use of model predictions and action thresholds with the standard program. Two variants were additionally considered in each program to set the frequency between applications, based on (i) a fixed frequency of 21 days or (ii) specific meteorological criteria (spraying within 7 days after rainfalls greater than 10 mm, with daily mean temperatures between 10 and 20°C, and with a minimum frequency of 21 days between applications). Programs were evaluated in terms of RLB incidence and number of applications. The program based on the model with periodic fungicide applications was similarly effective as the standard program, resulting only in a 2.6% higher RLB incidence but with fewer applications (three to four, compared with seven in the standard program). When setting the frequency between applications by using the meteorological criteria, a higher reduction in the number of applications (two to three) was observed, while RLB incidence increased by roughly 16% in both programs. Therefore, the model developed in this study may represent a valuable tool toward a more sustainable fungicide schedule for the control of almond RLB in northeast Spain. 2024-09-10T08:32:13Z 2024-09-10T08:32:13Z 2024 article publishedVersion Pons-Solé, G., Torguet, L., Marimon, N., Miarnau, X., Lázaro, E., Vicent, A., & Luque, J. (2024). Modeling the airborne inoculum of Polystigma amygdalinum to optimize fungicide programs against almond red leaf blotch. Plant Disease, 108(3), 737-745. 0191-2917 https://hdl.handle.net/20.500.11939/8980 10.1094/PDIS-08-23-1540-RE https://apsjournals.apsnet.org/doi/abs/10.1094/PDIS-08-23-1540-RE en INIA/Programa Estatal de I+D+I orientada a los retos de la sociedad/RTA2017-00009-C04-01/ES/Estrategias de control de enfermedades fúngicas del almendro basadas en la epidemiología, en la genética de la resistencia y en las prácticas de cultivo/ MCIN/Programa Estatal de generación del conocimiento y fortalecimiento científico y tecnológico del sistema I+D+I y Programa Estatal de I+D+I orientada a los retos de la sociedad/PID2020-114648RR-C31/ES/DESARROLLO Y APLICACIÓN DE MODELOS PREDICTIVOS, AGENTES DE BIOCONTROL Y MANEJO DE LA RESISTENCIA EN EL CONTROL INTEGRADO DE ENFERMEDADES DEL ALMENDRO/NEW4ALMOND Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ openAccess APS electronico |
| spellingShingle | Decision support system Disease control Modeling Polystigma amygdalinum Red leaf blotch H20 Plant diseases Epidemiology Prunus dulcis Pons-Solé, Gemma Torguet, Laura Marimon, Neus Miarnau, Xavier Lázaro, Elena Vicent, Antonio Luque, Jordi Modeling the Airborne Inoculum of Polystigma amygdalinum to Optimize Fungicide Programs Against Almond Red Leaf Blotch |
| title | Modeling the Airborne Inoculum of Polystigma amygdalinum to Optimize Fungicide Programs Against Almond Red Leaf Blotch |
| title_full | Modeling the Airborne Inoculum of Polystigma amygdalinum to Optimize Fungicide Programs Against Almond Red Leaf Blotch |
| title_fullStr | Modeling the Airborne Inoculum of Polystigma amygdalinum to Optimize Fungicide Programs Against Almond Red Leaf Blotch |
| title_full_unstemmed | Modeling the Airborne Inoculum of Polystigma amygdalinum to Optimize Fungicide Programs Against Almond Red Leaf Blotch |
| title_short | Modeling the Airborne Inoculum of Polystigma amygdalinum to Optimize Fungicide Programs Against Almond Red Leaf Blotch |
| title_sort | modeling the airborne inoculum of polystigma amygdalinum to optimize fungicide programs against almond red leaf blotch |
| topic | Decision support system Disease control Modeling Polystigma amygdalinum Red leaf blotch H20 Plant diseases Epidemiology Prunus dulcis |
| url | https://hdl.handle.net/20.500.11939/8980 https://apsjournals.apsnet.org/doi/abs/10.1094/PDIS-08-23-1540-RE |
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