Weather During Critical Epidemiological Periods and Subsequent Severity of Powdery Mildew on Grape Berries.
Identifieur interne : 000354 ( Main/Exploration ); précédent : 000353; suivant : 000355Weather During Critical Epidemiological Periods and Subsequent Severity of Powdery Mildew on Grape Berries.
Auteurs : Michelle M. Moyer [États-Unis] ; David M. Gadoury [États-Unis] ; Wayne F. Wilcox [États-Unis] ; Robert C. Seem [États-Unis]Source :
- Plant disease [ 0191-2917 ] ; 2016.
Abstract
Recorded severity of grape powdery mildew on berries of untreated, susceptible hybrid cultivars varied from 0.2 to 50.5% across a 30-year period in Geneva, NY; within 7 of those years, cluster disease severity ranged from 3.42 to 99.5% on Vitis vinifera 'Chardonnay'. Although existing temperature-driven risk models could not account for this annual variation, pan evaporation (Epan), an environmental variable influenced by the collective effects of temperature, vapor pressure deficit, solar radiation, and wind speed, did. Logistic regression analysis (LRA) was used to classify epidemics as either mild or severe. Recursive partition analysis (RPA) provided a simplified decision tree for calculation of powdery mildew risk and incorporated (i) an estimate of the relative primary inoculum levels based on temperatures in the previous late summer and (ii) the current season favorability for pathogen development during the grapevine phenological period critical for berry infection by Erysiphe necator. Although the LRA had fewer instances of misclassification, RPA provided a rapid means for seasonal risk classification. Both the RPA and LRA models are able to describe disease severity risk in real time or can be used to forecast risk, thereby allowing growers to adjust management programs in a responsive manner.
DOI: 10.1094/PDIS-12-14-1278-RE
PubMed: 30688564
Affiliations:
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Wilcox</name><affiliation wicri:level="2"><nlm:affiliation>Division of Plant Pathology and Plant-Microbe Biology, Cornell University, New York State Agricultural Experiment Station, Geneva, NY 14456.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">État de New York</region></placeName><wicri:cityArea>Division of Plant Pathology and Plant-Microbe Biology, Cornell University, New York State Agricultural Experiment Station, Geneva</wicri:cityArea></affiliation></author><author><name sortKey="Seem, Robert C" sort="Seem, Robert C" uniqKey="Seem R" first="Robert C" last="Seem">Robert C. Seem</name><affiliation wicri:level="2"><nlm:affiliation>Division of Plant Pathology and Plant-Microbe Biology, Cornell University, New York State Agricultural Experiment Station, Geneva, NY 14456.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">État de New York</region></placeName><wicri:cityArea>Division of Plant Pathology and Plant-Microbe Biology, Cornell University, New York State Agricultural Experiment Station, Geneva</wicri:cityArea></affiliation></author></analytic><series><title level="j">Plant disease</title><idno type="ISSN">0191-2917</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Recorded severity of grape powdery mildew on berries of untreated, susceptible hybrid cultivars varied from 0.2 to 50.5% across a 30-year period in Geneva, NY; within 7 of those years, cluster disease severity ranged from 3.42 to 99.5% on Vitis vinifera 'Chardonnay'. Although existing temperature-driven risk models could not account for this annual variation, pan evaporation (E<sub>pan</sub>), an environmental variable influenced by the collective effects of temperature, vapor pressure deficit, solar radiation, and wind speed, did. Logistic regression analysis (LRA) was used to classify epidemics as either mild or severe. Recursive partition analysis (RPA) provided a simplified decision tree for calculation of powdery mildew risk and incorporated (i) an estimate of the relative primary inoculum levels based on temperatures in the previous late summer and (ii) the current season favorability for pathogen development during the grapevine phenological period critical for berry infection by Erysiphe necator. Although the LRA had fewer instances of misclassification, RPA provided a rapid means for seasonal risk classification. Both the RPA and LRA models are able to describe disease severity risk in real time or can be used to forecast risk, thereby allowing growers to adjust management programs in a responsive manner.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">30688564</PMID><DateRevised><Year>2019</Year><Month>11</Month><Day>20</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">0191-2917</ISSN><JournalIssue CitedMedium="Print"><Volume>100</Volume><Issue>1</Issue><PubDate><Year>2016</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Plant disease</Title><ISOAbbreviation>Plant Dis</ISOAbbreviation></Journal><ArticleTitle>Weather During Critical Epidemiological Periods and Subsequent Severity of Powdery Mildew on Grape Berries.</ArticleTitle><Pagination><MedlinePgn>116-124</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1094/PDIS-12-14-1278-RE</ELocationID><Abstract><AbstractText>Recorded severity of grape powdery mildew on berries of untreated, susceptible hybrid cultivars varied from 0.2 to 50.5% across a 30-year period in Geneva, NY; within 7 of those years, cluster disease severity ranged from 3.42 to 99.5% on Vitis vinifera 'Chardonnay'. Although existing temperature-driven risk models could not account for this annual variation, pan evaporation (E<sub>pan</sub>), an environmental variable influenced by the collective effects of temperature, vapor pressure deficit, solar radiation, and wind speed, did. Logistic regression analysis (LRA) was used to classify epidemics as either mild or severe. Recursive partition analysis (RPA) provided a simplified decision tree for calculation of powdery mildew risk and incorporated (i) an estimate of the relative primary inoculum levels based on temperatures in the previous late summer and (ii) the current season favorability for pathogen development during the grapevine phenological period critical for berry infection by Erysiphe necator. Although the LRA had fewer instances of misclassification, RPA provided a rapid means for seasonal risk classification. Both the RPA and LRA models are able to describe disease severity risk in real time or can be used to forecast risk, thereby allowing growers to adjust management programs in a responsive manner.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Moyer</LastName><ForeName>Michelle M</ForeName><Initials>MM</Initials><AffiliationInfo><Affiliation>Department of Horticulture, Washington State University, Irrigated Agriculture Research and Extension Center, Prosser, WA 99350.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gadoury</LastName><ForeName>David M</ForeName><Initials>DM</Initials><AffiliationInfo><Affiliation>Division of Plant Pathology and Plant-Microbe Biology, Cornell University, New York State Agricultural Experiment Station, Geneva, NY 14456.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wilcox</LastName><ForeName>Wayne F</ForeName><Initials>WF</Initials><AffiliationInfo><Affiliation>Division of Plant Pathology and Plant-Microbe Biology, Cornell University, New York State Agricultural Experiment Station, Geneva, NY 14456.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Seem</LastName><ForeName>Robert C</ForeName><Initials>RC</Initials><AffiliationInfo><Affiliation>Division of Plant Pathology and Plant-Microbe Biology, Cornell University, New York State Agricultural Experiment Station, Geneva, NY 14456.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>10</Month><Day>27</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Plant Dis</MedlineTA><NlmUniqueID>9882809</NlmUniqueID><ISSNLinking>0191-2917</ISSNLinking></MedlineJournalInfo></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2019</Year><Month>1</Month><Day>29</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2016</Year><Month>1</Month><Day>1</Day><Hour>0</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>1</Month><Day>1</Day><Hour>0</Hour><Minute>1</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">30688564</ArticleId><ArticleId IdType="doi">10.1094/PDIS-12-14-1278-RE</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Washington (État)</li><li>État de New York</li></region></list><tree><country name="États-Unis"><region name="Washington (État)"><name sortKey="Moyer, Michelle M" sort="Moyer, Michelle M" uniqKey="Moyer M" first="Michelle M" last="Moyer">Michelle M. Moyer</name></region><name sortKey="Gadoury, David M" sort="Gadoury, David M" uniqKey="Gadoury D" first="David M" last="Gadoury">David M. Gadoury</name><name sortKey="Seem, Robert C" sort="Seem, Robert C" uniqKey="Seem R" first="Robert C" last="Seem">Robert C. Seem</name><name sortKey="Wilcox, Wayne F" sort="Wilcox, Wayne F" uniqKey="Wilcox W" first="Wayne F" last="Wilcox">Wayne F. Wilcox</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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