Potential application of digital image-processing method and fitted logistic model to the control of oriental fruit moths (Grapholita molesta Busck)
Monitoring of oriental fruit moths (Grapholita molesta Busck) is a prerequisite for its control. This study introduced a digital image-processing method and logistic model for the control of oriental fruit moths. First, five triangular sex pheromone traps were installed separately within each area o...
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| Veröffentlicht in: | Bulletin of entomological research 2016-08, Vol.106 (4), p.457-463 |
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| creator | Zhao, Z G Rong, E H Li, S C Zhang, L J Zhang, Z W Guo, Y Q Ma, R Y |
| description | Monitoring of oriental fruit moths (Grapholita molesta Busck) is a prerequisite for its control. This study introduced a digital image-processing method and logistic model for the control of oriental fruit moths. First, five triangular sex pheromone traps were installed separately within each area of 667 m2 in a peach orchard to monitor oriental fruit moths consecutively for 3 years. Next, full view images of oriental fruit moths were collected via a digital camera and then subjected to graying, separation and morphological analysis for automatic counting using MATLAB software. Afterwards, the results of automatic counting were used for fitting a logistic model to forecast the control threshold and key control period. There was a high consistency between automatic counting and manual counting (0.99, P < 0.05). According to the logistic model, oriental fruit moths had four occurrence peaks during a year, with a time-lag of 15-18 days between adult occurrence peak and the larval damage peak. Additionally, the key control period was from 28 June to 3 July each year, when the wormy fruit rate reached up to 5% and the trapping volume was approximately 10.2 per day per trap. Additionally, the key control period for the overwintering generation was 25 April. This study provides an automatic counting method and fitted logistic model with a great potential for application to the control of oriental fruit moths. |
| doi_str_mv | 10.1017/S0007485315001145 |
| format | Article |
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This study introduced a digital image-processing method and logistic model for the control of oriental fruit moths. First, five triangular sex pheromone traps were installed separately within each area of 667 m2 in a peach orchard to monitor oriental fruit moths consecutively for 3 years. Next, full view images of oriental fruit moths were collected via a digital camera and then subjected to graying, separation and morphological analysis for automatic counting using MATLAB software. Afterwards, the results of automatic counting were used for fitting a logistic model to forecast the control threshold and key control period. There was a high consistency between automatic counting and manual counting (0.99, P < 0.05). According to the logistic model, oriental fruit moths had four occurrence peaks during a year, with a time-lag of 15-18 days between adult occurrence peak and the larval damage peak. Additionally, the key control period was from 28 June to 3 July each year, when the wormy fruit rate reached up to 5% and the trapping volume was approximately 10.2 per day per trap. Additionally, the key control period for the overwintering generation was 25 April. This study provides an automatic counting method and fitted logistic model with a great potential for application to the control of oriental fruit moths.</description><identifier>ISSN: 0007-4853</identifier><identifier>EISSN: 1475-2670</identifier><identifier>DOI: 10.1017/S0007485315001145</identifier><identifier>PMID: 27087550</identifier><language>eng</language><publisher>England: Cambridge University Press</publisher><subject>Animals ; Butterflies & moths ; Digital imaging ; Environmental monitoring ; Fruits ; Grapholita molesta ; Image Processing, Computer-Assisted - methods ; Insect control ; Insect Control - methods ; Logistic Models ; Moths - physiology ; Orchards ; Overwintering ; Population Density ; Population Dynamics ; Prunus ; Sex Attractants</subject><ispartof>Bulletin of entomological research, 2016-08, Vol.106 (4), p.457-463</ispartof><rights>Copyright © Cambridge University Press 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-e73f2982402ac53dc70205eb60512477a6fbb3ce893c2174d4e352eea6cc41853</citedby><cites>FETCH-LOGICAL-c362t-e73f2982402ac53dc70205eb60512477a6fbb3ce893c2174d4e352eea6cc41853</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27087550$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhao, Z G</creatorcontrib><creatorcontrib>Rong, E H</creatorcontrib><creatorcontrib>Li, S C</creatorcontrib><creatorcontrib>Zhang, L J</creatorcontrib><creatorcontrib>Zhang, Z W</creatorcontrib><creatorcontrib>Guo, Y Q</creatorcontrib><creatorcontrib>Ma, R Y</creatorcontrib><title>Potential application of digital image-processing method and fitted logistic model to the control of oriental fruit moths (Grapholita molesta Busck)</title><title>Bulletin of entomological research</title><addtitle>Bull Entomol Res</addtitle><description>Monitoring of oriental fruit moths (Grapholita molesta Busck) is a prerequisite for its control. This study introduced a digital image-processing method and logistic model for the control of oriental fruit moths. First, five triangular sex pheromone traps were installed separately within each area of 667 m2 in a peach orchard to monitor oriental fruit moths consecutively for 3 years. Next, full view images of oriental fruit moths were collected via a digital camera and then subjected to graying, separation and morphological analysis for automatic counting using MATLAB software. Afterwards, the results of automatic counting were used for fitting a logistic model to forecast the control threshold and key control period. There was a high consistency between automatic counting and manual counting (0.99, P < 0.05). According to the logistic model, oriental fruit moths had four occurrence peaks during a year, with a time-lag of 15-18 days between adult occurrence peak and the larval damage peak. Additionally, the key control period was from 28 June to 3 July each year, when the wormy fruit rate reached up to 5% and the trapping volume was approximately 10.2 per day per trap. Additionally, the key control period for the overwintering generation was 25 April. This study provides an automatic counting method and fitted logistic model with a great potential for application to the control of oriental fruit moths.</description><subject>Animals</subject><subject>Butterflies & moths</subject><subject>Digital imaging</subject><subject>Environmental monitoring</subject><subject>Fruits</subject><subject>Grapholita molesta</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Insect control</subject><subject>Insect Control - methods</subject><subject>Logistic Models</subject><subject>Moths - physiology</subject><subject>Orchards</subject><subject>Overwintering</subject><subject>Population Density</subject><subject>Population Dynamics</subject><subject>Prunus</subject><subject>Sex Attractants</subject><issn>0007-4853</issn><issn>1475-2670</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqNkc9O3DAQxq0KVBboA_SCLHGhhxT_jZNjQS1FQgKp5Rx5ncmuqROntnPoe_SBOwuUQ7n0NPLMb77PM0PIe84-csbN-TfGmFGNllwzxrnSb8iKK6MrURu2R1a7crWrH5DDnB_wqVrVviUHwrDGaM1W5PddLDAVbwO18xy8s8XHicaB9n7jC6b9aDdQzSk6yNlPGzpC2cae2qmngy8FehrixufiHR1jD4GWSMsWqItTSTHstGLyaIJiQ1p8QaxsMz27SnbexoAumAmQMV4s2f34cEz2BxsyvHuOR-T-y-fvl1-rm9ur68tPN5WTtSgVGDmIthGKCeu07J1hgmlY10xzoYyx9bBeSwdNK53gRvUKpBYAtnZOcVzLETl70sXpfi74gW702UEIdoK45I43rKmbtub8f1CG9rwRiJ7-gz7EJU04yCMl61ZqhRR_olyKOScYujnhqtOvjrNud93u1XWx5-RZeVmP0L90_D2n_AOtKqAQ</recordid><startdate>201608</startdate><enddate>201608</enddate><creator>Zhao, Z G</creator><creator>Rong, E H</creator><creator>Li, S C</creator><creator>Zhang, L J</creator><creator>Zhang, Z W</creator><creator>Guo, Y Q</creator><creator>Ma, R Y</creator><general>Cambridge University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QG</scope><scope>7QR</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H95</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>L.G</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>P64</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>201608</creationdate><title>Potential application of digital image-processing method and fitted logistic model to the control of oriental fruit moths (Grapholita molesta Busck)</title><author>Zhao, Z G ; Rong, E H ; Li, S C ; Zhang, L J ; Zhang, Z W ; Guo, Y Q ; Ma, R Y</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-e73f2982402ac53dc70205eb60512477a6fbb3ce893c2174d4e352eea6cc41853</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Animals</topic><topic>Butterflies & moths</topic><topic>Digital imaging</topic><topic>Environmental monitoring</topic><topic>Fruits</topic><topic>Grapholita molesta</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Insect control</topic><topic>Insect Control - methods</topic><topic>Logistic Models</topic><topic>Moths - physiology</topic><topic>Orchards</topic><topic>Overwintering</topic><topic>Population Density</topic><topic>Population Dynamics</topic><topic>Prunus</topic><topic>Sex Attractants</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, Z G</creatorcontrib><creatorcontrib>Rong, E H</creatorcontrib><creatorcontrib>Li, S C</creatorcontrib><creatorcontrib>Zhang, L J</creatorcontrib><creatorcontrib>Zhang, Z W</creatorcontrib><creatorcontrib>Guo, Y Q</creatorcontrib><creatorcontrib>Ma, R Y</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Bulletin of entomological research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhao, Z G</au><au>Rong, E H</au><au>Li, S C</au><au>Zhang, L J</au><au>Zhang, Z W</au><au>Guo, Y Q</au><au>Ma, R Y</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Potential application of digital image-processing method and fitted logistic model to the control of oriental fruit moths (Grapholita molesta Busck)</atitle><jtitle>Bulletin of entomological research</jtitle><addtitle>Bull Entomol Res</addtitle><date>2016-08</date><risdate>2016</risdate><volume>106</volume><issue>4</issue><spage>457</spage><epage>463</epage><pages>457-463</pages><issn>0007-4853</issn><eissn>1475-2670</eissn><abstract>Monitoring of oriental fruit moths (Grapholita molesta Busck) is a prerequisite for its control. This study introduced a digital image-processing method and logistic model for the control of oriental fruit moths. First, five triangular sex pheromone traps were installed separately within each area of 667 m2 in a peach orchard to monitor oriental fruit moths consecutively for 3 years. Next, full view images of oriental fruit moths were collected via a digital camera and then subjected to graying, separation and morphological analysis for automatic counting using MATLAB software. Afterwards, the results of automatic counting were used for fitting a logistic model to forecast the control threshold and key control period. There was a high consistency between automatic counting and manual counting (0.99, P < 0.05). According to the logistic model, oriental fruit moths had four occurrence peaks during a year, with a time-lag of 15-18 days between adult occurrence peak and the larval damage peak. Additionally, the key control period was from 28 June to 3 July each year, when the wormy fruit rate reached up to 5% and the trapping volume was approximately 10.2 per day per trap. Additionally, the key control period for the overwintering generation was 25 April. This study provides an automatic counting method and fitted logistic model with a great potential for application to the control of oriental fruit moths.</abstract><cop>England</cop><pub>Cambridge University Press</pub><pmid>27087550</pmid><doi>10.1017/S0007485315001145</doi><tpages>7</tpages></addata></record> |
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| ispartof | Bulletin of entomological research, 2016-08, Vol.106 (4), p.457-463 |
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| source | MEDLINE; Cambridge University Press Journals Complete |
| subjects | Animals Butterflies & moths Digital imaging Environmental monitoring Fruits Grapholita molesta Image Processing, Computer-Assisted - methods Insect control Insect Control - methods Logistic Models Moths - physiology Orchards Overwintering Population Density Population Dynamics Prunus Sex Attractants |
| title | Potential application of digital image-processing method and fitted logistic model to the control of oriental fruit moths (Grapholita molesta Busck) |
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