Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly Control

Lalguard C99 WP, based on the <i>Cordyceps javanica</i> BRM 27666 strain, is registered in Brazil for whitefly control. Spatial prediction is crucial for optimizing its field use and efficacy. In this study, the optimal temperature for mycelial growth and conidial production of <i>...

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Main Authors: Heloiza A. Boaventura, Lidiane A. Queirós, José Francisco A. Silva, Tarryn A. Goble, Kelly Pazolini, Allan F. Marciano, Eliane D. Quintela
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Journal of Fungi
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Online Access:https://www.mdpi.com/2309-608X/11/2/125
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author Heloiza A. Boaventura
Lidiane A. Queirós
José Francisco A. Silva
Tarryn A. Goble
Kelly Pazolini
Allan F. Marciano
Eliane D. Quintela
author_facet Heloiza A. Boaventura
Lidiane A. Queirós
José Francisco A. Silva
Tarryn A. Goble
Kelly Pazolini
Allan F. Marciano
Eliane D. Quintela
author_sort Heloiza A. Boaventura
collection DOAJ
description Lalguard C99 WP, based on the <i>Cordyceps javanica</i> BRM 27666 strain, is registered in Brazil for whitefly control. Spatial prediction is crucial for optimizing its field use and efficacy. In this study, the optimal temperature for mycelial growth and conidial production of <i>C. javanica is</i> 25–30 °C, with no growth at 33–35 °C. The highest nymphal mortality occurred at 25 and 30 °C, showing lower LT<sub>50</sub> values at 30 °C. Mycelial growth was similar at 15, 20, 25, 30, and 35 °C when the fungus was exposed for 6 h and then transferred to a 27.4 °C environment; however, growth was slower at 35 °C with daily 6 h exposure alternating over 18 h at room temperature (mean of 28.5 °C). When the second instar whitefly nymphs were exposed for 6 h or 6 h daily at 15, 20, 25, 30, and 35 °C, followed by 7 days at fluctuating temperatures (mean of 28.4–30.2 °C), nymphal mortality was similar across temperatures. Although other abiotic factors (solar radiation, humidity, rainfall, etc.) must be considered for fungal efficacy, spatial predictions based on fluctuating temperatures indicated that <i>C. javanica</i> is suitable for use throughout Brazil, though its performance varied at constant temperatures in different locations.
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spelling doaj-art-180e1d86bfcc4884883ec9045ede90eb2025-08-20T02:45:00ZengMDPI AGJournal of Fungi2309-608X2025-02-0111212510.3390/jof11020125Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly ControlHeloiza A. Boaventura0Lidiane A. Queirós1José Francisco A. Silva2Tarryn A. Goble3Kelly Pazolini4Allan F. Marciano5Eliane D. Quintela6Escola de Agronomia, Universidade Federal de Goiás, Goiânia 74690-900, BrazilEscola de Agronomia, Universidade Federal de Goiás, Goiânia 74690-900, BrazilEmbrapa Arroz e Feijão, Santo Antônio de Goiás 75375-000, BrazilLallemand Plant Care, Patos de Minas 38706-420, BrazilLallemand Plant Care, Patos de Minas 38706-420, BrazilLallemand Plant Care, Patos de Minas 38706-420, BrazilEscola de Agronomia, Universidade Federal de Goiás, Goiânia 74690-900, BrazilLalguard C99 WP, based on the <i>Cordyceps javanica</i> BRM 27666 strain, is registered in Brazil for whitefly control. Spatial prediction is crucial for optimizing its field use and efficacy. In this study, the optimal temperature for mycelial growth and conidial production of <i>C. javanica is</i> 25–30 °C, with no growth at 33–35 °C. The highest nymphal mortality occurred at 25 and 30 °C, showing lower LT<sub>50</sub> values at 30 °C. Mycelial growth was similar at 15, 20, 25, 30, and 35 °C when the fungus was exposed for 6 h and then transferred to a 27.4 °C environment; however, growth was slower at 35 °C with daily 6 h exposure alternating over 18 h at room temperature (mean of 28.5 °C). When the second instar whitefly nymphs were exposed for 6 h or 6 h daily at 15, 20, 25, 30, and 35 °C, followed by 7 days at fluctuating temperatures (mean of 28.4–30.2 °C), nymphal mortality was similar across temperatures. Although other abiotic factors (solar radiation, humidity, rainfall, etc.) must be considered for fungal efficacy, spatial predictions based on fluctuating temperatures indicated that <i>C. javanica</i> is suitable for use throughout Brazil, though its performance varied at constant temperatures in different locations.https://www.mdpi.com/2309-608X/11/2/125<i>Bemisia tabaci</i>entomopathogenic fungimathematical modelscontrolIPM
spellingShingle Heloiza A. Boaventura
Lidiane A. Queirós
José Francisco A. Silva
Tarryn A. Goble
Kelly Pazolini
Allan F. Marciano
Eliane D. Quintela
Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly Control
Journal of Fungi
<i>Bemisia tabaci</i>
entomopathogenic fungi
mathematical models
control
IPM
title Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly Control
title_full Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly Control
title_fullStr Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly Control
title_full_unstemmed Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly Control
title_short Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly Control
title_sort temperature dependent modeling and spatial predictions for identifying geographical areas in brazil suitable for the use of i cordyceps javanica i in whitefly control
topic <i>Bemisia tabaci</i>
entomopathogenic fungi
mathematical models
control
IPM
url https://www.mdpi.com/2309-608X/11/2/125
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