Temperature- and Radiation-Based Models for Predicting Spatial Growth of Purple Nutsedge (Cyperus rotundus)
Purple nutsedge is a troublesome C4 weed, characterized by high photosynthetic efficiency, compared to C3 weeds. As its dispersal is based on vegetative growth, accurate prediction of its growth could help in arriving at favorable management decisions. This article details the development and valida...
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| Veröffentlicht in: | Weed science 2011-10, Vol.59 (4), p.476-482 |
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| creator | Lati, Ran Nisim Filin, Sagi Eizenberg, Hanan |
| description | Purple nutsedge is a troublesome C4 weed, characterized by high photosynthetic efficiency, compared to C3 weeds. As its dispersal is based on vegetative growth, accurate prediction of its growth could help in arriving at favorable management decisions. This article details the development and validation of predictive models of purple nutsedge spatial growth, based on temperature (thermal model), and temperature and radiation (photothermal model) measurements. Plants were grown in six experiments in the summers of 2008, 2009, and 2010, under different temperature and radiation conditions. Results indicate that under optimal temperatures, radiation becomes the main growth-limiting factor, and is highly related to the final leaf-cover area (R2 = 0.89). Comparison of the thermal and photothermal models showed that under all conditions, including varied temperature and radiation, the photothermal model performs significantly better, with differences in root-mean-square error values reaching up to 0.073, compared to 0.195 with the thermal model. Validation experiments confirmed the ability of the photothermal model to predict purple nutsedge spatial growth accurately. Nomenclature: Purple nutsedge, Cyperus rotundus L. CYPRO. |
| doi_str_mv | 10.1614/WS-D-11-00007.1 |
| format | Article |
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As its dispersal is based on vegetative growth, accurate prediction of its growth could help in arriving at favorable management decisions. This article details the development and validation of predictive models of purple nutsedge spatial growth, based on temperature (thermal model), and temperature and radiation (photothermal model) measurements. Plants were grown in six experiments in the summers of 2008, 2009, and 2010, under different temperature and radiation conditions. Results indicate that under optimal temperatures, radiation becomes the main growth-limiting factor, and is highly related to the final leaf-cover area (R2 = 0.89). Comparison of the thermal and photothermal models showed that under all conditions, including varied temperature and radiation, the photothermal model performs significantly better, with differences in root-mean-square error values reaching up to 0.073, compared to 0.195 with the thermal model. Validation experiments confirmed the ability of the photothermal model to predict purple nutsedge spatial growth accurately. Nomenclature: Purple nutsedge, Cyperus rotundus L. CYPRO.</description><identifier>ISSN: 0043-1745</identifier><identifier>EISSN: 1550-2759</identifier><identifier>DOI: 10.1614/WS-D-11-00007.1</identifier><identifier>CODEN: WEESA6</identifier><language>eng</language><publisher>810 East 10th Street, Lawrence, KS 66044-8897: Weed Science Society of America</publisher><subject>Biological and medical sciences ; Biomass ; Cyperus rotundus ; effective degree day ; Environmental conditions ; Experiments ; Field study ; Fundamental and applied biological sciences. Psychology ; Growing seasons ; Growth models ; Irrigation ; leaf-cover area ; Modeling ; Parasitic plants. Weeds ; photosynthesis ; photosynthetically active radiation ; Phytopathology. Animal pests. Plant and forest protection ; Plant growth ; Plant shading ; Plants ; prediction ; prediction model ; Prediction models ; Predictive modeling ; Spatial models ; Temperature ; Tubers ; Vegetative growth ; WEED BIOLOGY AND ECOLOGY ; Weeds</subject><ispartof>Weed science, 2011-10, Vol.59 (4), p.476-482</ispartof><rights>Weed Science Society of America</rights><rights>Copyright © Weed Science Society of America</rights><rights>Copyright 2011 Weed Science Society of America</rights><rights>2015 INIST-CNRS</rights><rights>Copyright Allen Press Publishing Services Oct-Dec 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b536t-a508e30eecf8faa6fcf303e11993a15e850cb59ef2c8cdb1d91a56439535aaa83</citedby><cites>FETCH-LOGICAL-b536t-a508e30eecf8faa6fcf303e11993a15e850cb59ef2c8cdb1d91a56439535aaa83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://bioone.org/doi/pdf/10.1614/WS-D-11-00007.1$$EPDF$$P50$$Gbioone$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/23018851$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,26955,27901,27902,52338,57992,58225</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24606609$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Lati, Ran Nisim</creatorcontrib><creatorcontrib>Filin, Sagi</creatorcontrib><creatorcontrib>Eizenberg, Hanan</creatorcontrib><title>Temperature- and Radiation-Based Models for Predicting Spatial Growth of Purple Nutsedge (Cyperus rotundus)</title><title>Weed science</title><addtitle>Weed sci</addtitle><description>Purple nutsedge is a troublesome C4 weed, characterized by high photosynthetic efficiency, compared to C3 weeds. As its dispersal is based on vegetative growth, accurate prediction of its growth could help in arriving at favorable management decisions. This article details the development and validation of predictive models of purple nutsedge spatial growth, based on temperature (thermal model), and temperature and radiation (photothermal model) measurements. Plants were grown in six experiments in the summers of 2008, 2009, and 2010, under different temperature and radiation conditions. Results indicate that under optimal temperatures, radiation becomes the main growth-limiting factor, and is highly related to the final leaf-cover area (R2 = 0.89). Comparison of the thermal and photothermal models showed that under all conditions, including varied temperature and radiation, the photothermal model performs significantly better, with differences in root-mean-square error values reaching up to 0.073, compared to 0.195 with the thermal model. Validation experiments confirmed the ability of the photothermal model to predict purple nutsedge spatial growth accurately. Nomenclature: Purple nutsedge, Cyperus rotundus L. CYPRO.</description><subject>Biological and medical sciences</subject><subject>Biomass</subject><subject>Cyperus rotundus</subject><subject>effective degree day</subject><subject>Environmental conditions</subject><subject>Experiments</subject><subject>Field study</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Growing seasons</subject><subject>Growth models</subject><subject>Irrigation</subject><subject>leaf-cover area</subject><subject>Modeling</subject><subject>Parasitic plants. Weeds</subject><subject>photosynthesis</subject><subject>photosynthetically active radiation</subject><subject>Phytopathology. Animal pests. Plant and forest protection</subject><subject>Plant growth</subject><subject>Plant shading</subject><subject>Plants</subject><subject>prediction</subject><subject>prediction model</subject><subject>Prediction models</subject><subject>Predictive modeling</subject><subject>Spatial models</subject><subject>Temperature</subject><subject>Tubers</subject><subject>Vegetative growth</subject><subject>WEED BIOLOGY AND ECOLOGY</subject><subject>Weeds</subject><issn>0043-1745</issn><issn>1550-2759</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkM1v1DAQxS1EJZaWMyeEhYQEB7ceO87HsWxLi1SgYlv1aE0Se8mSjYPtqOp_j7dZ0RPCFx_m997Me4S8Bn4MOWQndyt2xgAYT684hmdkAUpxJgpVPScLzjPJoMjUC_IyhA3nkAuoFuTXjdmOxmOcvGEUh5b-wLbD2LmBfcJgWvrVtaYP1DpPr71puyZ2w5quxsRgTy-8u48_qbP0evJjb-i3KSbV2tAPy4dkPAXqXZyGdgofj8iBxT6YV_v_kNx-Pr9ZXrKr7xdflqdXrFYyjwwVL43kxjS2tIi5bazk0gBUlURQplS8qVVlrGjKpq2hrQBVnslKSYWIpTwk72bf0bvfkwlRb9zkh7RSVym4KESmEnQyQ413IXhj9ei7LfoHDVzvCtV3K32mAfRjoRqS4v3eFkODvfU4NF34KxNZzvOcV4l7M3ObEJ1_mksOZal2Pm_nuUWnce2Tx-1KcFC7RUIURSJgfxtua9-lNp8S_Ps6NmvqzrnB_DfNHw3rpwU</recordid><startdate>20111001</startdate><enddate>20111001</enddate><creator>Lati, Ran Nisim</creator><creator>Filin, Sagi</creator><creator>Eizenberg, Hanan</creator><general>Weed Science Society of America</general><general>Cambridge University Press</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7SS</scope><scope>7T7</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M0K</scope><scope>M2O</scope><scope>M7N</scope><scope>M7P</scope><scope>MBDVC</scope><scope>P64</scope><scope>PADUT</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope></search><sort><creationdate>20111001</creationdate><title>Temperature- and Radiation-Based Models for Predicting Spatial Growth of Purple Nutsedge (Cyperus rotundus)</title><author>Lati, Ran Nisim ; Filin, Sagi ; Eizenberg, Hanan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b536t-a508e30eecf8faa6fcf303e11993a15e850cb59ef2c8cdb1d91a56439535aaa83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Biological and medical sciences</topic><topic>Biomass</topic><topic>Cyperus rotundus</topic><topic>effective degree day</topic><topic>Environmental conditions</topic><topic>Experiments</topic><topic>Field study</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Growing seasons</topic><topic>Growth models</topic><topic>Irrigation</topic><topic>leaf-cover area</topic><topic>Modeling</topic><topic>Parasitic plants. Weeds</topic><topic>photosynthesis</topic><topic>photosynthetically active radiation</topic><topic>Phytopathology. Animal pests. Plant and forest protection</topic><topic>Plant growth</topic><topic>Plant shading</topic><topic>Plants</topic><topic>prediction</topic><topic>prediction model</topic><topic>Prediction models</topic><topic>Predictive modeling</topic><topic>Spatial models</topic><topic>Temperature</topic><topic>Tubers</topic><topic>Vegetative growth</topic><topic>WEED BIOLOGY AND ECOLOGY</topic><topic>Weeds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lati, Ran Nisim</creatorcontrib><creatorcontrib>Filin, Sagi</creatorcontrib><creatorcontrib>Eizenberg, Hanan</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</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>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Research Library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Research Library China</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><jtitle>Weed science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lati, Ran Nisim</au><au>Filin, Sagi</au><au>Eizenberg, Hanan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Temperature- and Radiation-Based Models for Predicting Spatial Growth of Purple Nutsedge (Cyperus rotundus)</atitle><jtitle>Weed science</jtitle><addtitle>Weed sci</addtitle><date>2011-10-01</date><risdate>2011</risdate><volume>59</volume><issue>4</issue><spage>476</spage><epage>482</epage><pages>476-482</pages><issn>0043-1745</issn><eissn>1550-2759</eissn><coden>WEESA6</coden><abstract>Purple nutsedge is a troublesome C4 weed, characterized by high photosynthetic efficiency, compared to C3 weeds. As its dispersal is based on vegetative growth, accurate prediction of its growth could help in arriving at favorable management decisions. This article details the development and validation of predictive models of purple nutsedge spatial growth, based on temperature (thermal model), and temperature and radiation (photothermal model) measurements. Plants were grown in six experiments in the summers of 2008, 2009, and 2010, under different temperature and radiation conditions. Results indicate that under optimal temperatures, radiation becomes the main growth-limiting factor, and is highly related to the final leaf-cover area (R2 = 0.89). Comparison of the thermal and photothermal models showed that under all conditions, including varied temperature and radiation, the photothermal model performs significantly better, with differences in root-mean-square error values reaching up to 0.073, compared to 0.195 with the thermal model. Validation experiments confirmed the ability of the photothermal model to predict purple nutsedge spatial growth accurately. Nomenclature: Purple nutsedge, Cyperus rotundus L. CYPRO.</abstract><cop>810 East 10th Street, Lawrence, KS 66044-8897</cop><pub>Weed Science Society of America</pub><doi>10.1614/WS-D-11-00007.1</doi><tpages>7</tpages></addata></record> |
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| subjects | Biological and medical sciences Biomass Cyperus rotundus effective degree day Environmental conditions Experiments Field study Fundamental and applied biological sciences. Psychology Growing seasons Growth models Irrigation leaf-cover area Modeling Parasitic plants. Weeds photosynthesis photosynthetically active radiation Phytopathology. Animal pests. Plant and forest protection Plant growth Plant shading Plants prediction prediction model Prediction models Predictive modeling Spatial models Temperature Tubers Vegetative growth WEED BIOLOGY AND ECOLOGY Weeds |
| title | Temperature- and Radiation-Based Models for Predicting Spatial Growth of Purple Nutsedge (Cyperus rotundus) |
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