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Evaluation of a physiologically based model to predict Dalbulus maidis occurrence in maize crops: validation in two different subtropical areas of South America
The maize leafhopper, Dalbulus maidis (DeLong) (Hemiptera: Cicadellidae), is a specialist herbivore that develops on maize plants (Zea mays L., Poaceae). Every year, it is responsible for considerable reductions in yields of the maize fields of the Americas, because alongside its direct damages it i...
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Published in: | Entomologia experimentalis et applicata 2021-07, Vol.169 (7), p.597-609 |
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description | The maize leafhopper, Dalbulus maidis (DeLong) (Hemiptera: Cicadellidae), is a specialist herbivore that develops on maize plants (Zea mays L., Poaceae). Every year, it is responsible for considerable reductions in yields of the maize fields of the Americas, because alongside its direct damages it is also a vector of three relevant plant pathogens. The transmitted diseases come to have a high incidence, resulting in significant yield losses, thereby forcing farmers and technicians to attempt a tight control of the fields mostly using non‐specific insecticides. Decision support systems based on mathematical models may be valuable in helping to reduce the use of agrochemicals in this regard, as they can provide a projection of the future situation based on past and present data. With this precondition, this work aims to apply and validate a physiologically based model to describe populations of D. maidis developing in two experimental fields located in Argentina, which are characterised by different climatic conditions. Experimentation in the two fields involved a 3‐year survey during the growing seasons 2009, 2010, and 2011, where the adult populations of maize leafhoppers were monitored from the sowing of maize plants to the end of the phenological stage at which they are most susceptible to D. maidis activity. Results showed a good response of the model in describing maize leafhopper populations, also allowing the possibility of setting a threshold for intervention and a projection of the situation if any control action is applied.
Dalbulus maidis (Hemiptera: Cicadellidae) is one of the major pests of maize crops, a vector of relevant plant pathogens, and responsible for considerable reductions in yields. To support integrated pest management control strategies, a physiologically based model was identified as a valuable candidate for decision‐making programmes. The model was validated in two experimental fields located in Argentina during a 3‐year survey. Results showed a good response of the model in describing maize leafhopper populations. |
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Dalbulus maidis (Hemiptera: Cicadellidae) is one of the major pests of maize crops, a vector of relevant plant pathogens, and responsible for considerable reductions in yields. To support integrated pest management control strategies, a physiologically based model was identified as a valuable candidate for decision‐making programmes. The model was validated in two experimental fields located in Argentina during a 3‐year survey. Results showed a good response of the model in describing maize leafhopper populations.</description><identifier>ISSN: 0013-8703</identifier><identifier>EISSN: 1570-7458</identifier><identifier>DOI: 10.1111/eea.13066</identifier><language>eng</language><publisher>Amsterdam: Wiley Subscription Services, Inc</publisher><subject>Agrochemicals ; Artificial intelligence ; Cereal crops ; Cicadellidae ; Climatic conditions ; Corn ; corn leafhopper ; Dalbulus maidis ; decision support system ; Decision support systems ; Disease transmission ; Experimentation ; Forecasting ; forecasting models ; Growing season ; Hemiptera ; Insecticides ; integrated pest management ; IPM ; maize leafhopper ; Mathematical models ; Poaceae ; Populations ; Technicians ; Von Foerster’s equation ; Zea mays</subject><ispartof>Entomologia experimentalis et applicata, 2021-07, Vol.169 (7), p.597-609</ispartof><rights>2021 The Netherlands Entomological Society</rights><rights>Entomologia Experimentalis et Applicata © 2021 The Netherlands Entomological Society</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2976-df16c77ffc4727b837ed82b927b5dcd22ad24110de76de5d297156a428867d5e3</citedby><cites>FETCH-LOGICAL-c2976-df16c77ffc4727b837ed82b927b5dcd22ad24110de76de5d297156a428867d5e3</cites><orcidid>0000-0003-2558-7111</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Rossini, Luca</creatorcontrib><creatorcontrib>Virla, Eduardo G.</creatorcontrib><creatorcontrib>Albarracín, Erica Luft</creatorcontrib><creatorcontrib>Van Nieuwenhove, Guido A.</creatorcontrib><creatorcontrib>Speranza, Stefano</creatorcontrib><title>Evaluation of a physiologically based model to predict Dalbulus maidis occurrence in maize crops: validation in two different subtropical areas of South America</title><title>Entomologia experimentalis et applicata</title><description>The maize leafhopper, Dalbulus maidis (DeLong) (Hemiptera: Cicadellidae), is a specialist herbivore that develops on maize plants (Zea mays L., Poaceae). Every year, it is responsible for considerable reductions in yields of the maize fields of the Americas, because alongside its direct damages it is also a vector of three relevant plant pathogens. The transmitted diseases come to have a high incidence, resulting in significant yield losses, thereby forcing farmers and technicians to attempt a tight control of the fields mostly using non‐specific insecticides. Decision support systems based on mathematical models may be valuable in helping to reduce the use of agrochemicals in this regard, as they can provide a projection of the future situation based on past and present data. With this precondition, this work aims to apply and validate a physiologically based model to describe populations of D. maidis developing in two experimental fields located in Argentina, which are characterised by different climatic conditions. Experimentation in the two fields involved a 3‐year survey during the growing seasons 2009, 2010, and 2011, where the adult populations of maize leafhoppers were monitored from the sowing of maize plants to the end of the phenological stage at which they are most susceptible to D. maidis activity. Results showed a good response of the model in describing maize leafhopper populations, also allowing the possibility of setting a threshold for intervention and a projection of the situation if any control action is applied.
Dalbulus maidis (Hemiptera: Cicadellidae) is one of the major pests of maize crops, a vector of relevant plant pathogens, and responsible for considerable reductions in yields. To support integrated pest management control strategies, a physiologically based model was identified as a valuable candidate for decision‐making programmes. The model was validated in two experimental fields located in Argentina during a 3‐year survey. Results showed a good response of the model in describing maize leafhopper populations.</description><subject>Agrochemicals</subject><subject>Artificial intelligence</subject><subject>Cereal crops</subject><subject>Cicadellidae</subject><subject>Climatic conditions</subject><subject>Corn</subject><subject>corn leafhopper</subject><subject>Dalbulus maidis</subject><subject>decision support system</subject><subject>Decision support systems</subject><subject>Disease transmission</subject><subject>Experimentation</subject><subject>Forecasting</subject><subject>forecasting models</subject><subject>Growing season</subject><subject>Hemiptera</subject><subject>Insecticides</subject><subject>integrated pest management</subject><subject>IPM</subject><subject>maize leafhopper</subject><subject>Mathematical models</subject><subject>Poaceae</subject><subject>Populations</subject><subject>Technicians</subject><subject>Von Foerster’s equation</subject><subject>Zea mays</subject><issn>0013-8703</issn><issn>1570-7458</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp1kctOwzAQRS0EEuWx4A9GYsUixXYedtlVUB4SEgtgHTn2hBq5dbATqvI1fCouYctsPLo-M9fWJeSM0SlLdYmopiynVbVHJqwUNBNFKffJhFKWZ1LQ_JAcxfhOKRVixibke_Gp3KB669fgW1DQLbfReuffrFbObaFREQ2svEEHvYcuoLG6hxvlmsENEVbKGhvBaz2EgGuNYNc78QtBB9_FK0gG1owO6arfeDC2bTHBPcSh6RO18wIVUMXdI5790C9hvsKQ9BNy0CoX8fTvPCavt4uX6_vs8enu4Xr-mGk-E1VmWlZpIdpWF4KLRuYCjeTNLPWl0YZzZXjBGDUoKoOlSUOsrFTBpayEKTE_Jufj3i74jwFjX7_7IayTZc3LXFaSi0Im6mKk0t9iDNjWXbArFbY1o_UugDoFUP8GkNjLkd1Yh9v_wXqxmI8TP78LikU</recordid><startdate>202107</startdate><enddate>202107</enddate><creator>Rossini, Luca</creator><creator>Virla, Eduardo G.</creator><creator>Albarracín, Erica Luft</creator><creator>Van Nieuwenhove, Guido A.</creator><creator>Speranza, Stefano</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QG</scope><scope>7QR</scope><scope>7SN</scope><scope>7SS</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><orcidid>https://orcid.org/0000-0003-2558-7111</orcidid></search><sort><creationdate>202107</creationdate><title>Evaluation of a physiologically based model to predict Dalbulus maidis occurrence in maize crops: validation in two different subtropical areas of South America</title><author>Rossini, Luca ; Virla, Eduardo G. ; Albarracín, Erica Luft ; Van Nieuwenhove, Guido A. ; Speranza, Stefano</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2976-df16c77ffc4727b837ed82b927b5dcd22ad24110de76de5d297156a428867d5e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Agrochemicals</topic><topic>Artificial intelligence</topic><topic>Cereal crops</topic><topic>Cicadellidae</topic><topic>Climatic conditions</topic><topic>Corn</topic><topic>corn leafhopper</topic><topic>Dalbulus maidis</topic><topic>decision support system</topic><topic>Decision support systems</topic><topic>Disease transmission</topic><topic>Experimentation</topic><topic>Forecasting</topic><topic>forecasting models</topic><topic>Growing season</topic><topic>Hemiptera</topic><topic>Insecticides</topic><topic>integrated pest management</topic><topic>IPM</topic><topic>maize leafhopper</topic><topic>Mathematical models</topic><topic>Poaceae</topic><topic>Populations</topic><topic>Technicians</topic><topic>Von Foerster’s equation</topic><topic>Zea mays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rossini, Luca</creatorcontrib><creatorcontrib>Virla, Eduardo G.</creatorcontrib><creatorcontrib>Albarracín, Erica Luft</creatorcontrib><creatorcontrib>Van Nieuwenhove, Guido A.</creatorcontrib><creatorcontrib>Speranza, Stefano</creatorcontrib><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>Entomologia experimentalis et applicata</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rossini, Luca</au><au>Virla, Eduardo G.</au><au>Albarracín, Erica Luft</au><au>Van Nieuwenhove, Guido A.</au><au>Speranza, Stefano</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of a physiologically based model to predict Dalbulus maidis occurrence in maize crops: validation in two different subtropical areas of South America</atitle><jtitle>Entomologia experimentalis et applicata</jtitle><date>2021-07</date><risdate>2021</risdate><volume>169</volume><issue>7</issue><spage>597</spage><epage>609</epage><pages>597-609</pages><issn>0013-8703</issn><eissn>1570-7458</eissn><abstract>The maize leafhopper, Dalbulus maidis (DeLong) (Hemiptera: Cicadellidae), is a specialist herbivore that develops on maize plants (Zea mays L., Poaceae). Every year, it is responsible for considerable reductions in yields of the maize fields of the Americas, because alongside its direct damages it is also a vector of three relevant plant pathogens. The transmitted diseases come to have a high incidence, resulting in significant yield losses, thereby forcing farmers and technicians to attempt a tight control of the fields mostly using non‐specific insecticides. Decision support systems based on mathematical models may be valuable in helping to reduce the use of agrochemicals in this regard, as they can provide a projection of the future situation based on past and present data. With this precondition, this work aims to apply and validate a physiologically based model to describe populations of D. maidis developing in two experimental fields located in Argentina, which are characterised by different climatic conditions. Experimentation in the two fields involved a 3‐year survey during the growing seasons 2009, 2010, and 2011, where the adult populations of maize leafhoppers were monitored from the sowing of maize plants to the end of the phenological stage at which they are most susceptible to D. maidis activity. Results showed a good response of the model in describing maize leafhopper populations, also allowing the possibility of setting a threshold for intervention and a projection of the situation if any control action is applied.
Dalbulus maidis (Hemiptera: Cicadellidae) is one of the major pests of maize crops, a vector of relevant plant pathogens, and responsible for considerable reductions in yields. To support integrated pest management control strategies, a physiologically based model was identified as a valuable candidate for decision‐making programmes. The model was validated in two experimental fields located in Argentina during a 3‐year survey. Results showed a good response of the model in describing maize leafhopper populations.</abstract><cop>Amsterdam</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/eea.13066</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-2558-7111</orcidid></addata></record> |
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subjects | Agrochemicals Artificial intelligence Cereal crops Cicadellidae Climatic conditions Corn corn leafhopper Dalbulus maidis decision support system Decision support systems Disease transmission Experimentation Forecasting forecasting models Growing season Hemiptera Insecticides integrated pest management IPM maize leafhopper Mathematical models Poaceae Populations Technicians Von Foerster’s equation Zea mays |
title | Evaluation of a physiologically based model to predict Dalbulus maidis occurrence in maize crops: validation in two different subtropical areas of South America |
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