A Very Simple Model for Yield Prediction of Rice under Different Water and Nitrogen Applications
The ability to accurately model crop water and nitrogen requirements can improve irrigation and nitrogen application management. Forecasting of rice yield at the time of planting, under different irrigation and nitrogen application management programmes, is possible with a rice yield simulation mode...
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Veröffentlicht in: | Biosystems engineering 2006, Vol.93 (1), p.25-34 |
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description | The ability to accurately model crop water and nitrogen requirements can improve irrigation and nitrogen application management. Forecasting of rice yield at the time of planting, under different irrigation and nitrogen application management programmes, is possible with a rice yield simulation model calibrated for the study area. In this study, a very simple model (VSM) was developed for simulation of rice grain and biomass yields under different irrigation and nitrogen application management strategies. The model assumes a triangular pattern for leaf area changes and proportionately of biomass accumulation to the intercepted solar radiation. The model can provide the grain and biomass yields based on maximum leaf area index, harvest index, and light use efficiency. These parameters were estimated by multiple regression equations. Nitrogen application rate, seasonal amount of applied irrigation water, plant population, maximum applied water in flood irrigation, and mean daily solar input before and after flowering are model inputs. Furthermore, the transplanting, flowering, and harvest dates should be specified. The model was calibrated for a lowland local rice cultivar (Champa-Kamfiroozi) in the Kooshkak area (semi-arid climate), Fars province, I.R. of Iran, with data from an experiment with five irrigation treatments and three nitrogen application rates in two consecutive years. The model produced good estimates of dry matter and grain yields. The accuracy of the model was verified with independent data from other experiments in the study area and in the northern parts of Iran with sub-humid climate. |
doi_str_mv | 10.1016/j.biosystemseng.2005.09.004 |
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Forecasting of rice yield at the time of planting, under different irrigation and nitrogen application management programmes, is possible with a rice yield simulation model calibrated for the study area. In this study, a very simple model (VSM) was developed for simulation of rice grain and biomass yields under different irrigation and nitrogen application management strategies. The model assumes a triangular pattern for leaf area changes and proportionately of biomass accumulation to the intercepted solar radiation. The model can provide the grain and biomass yields based on maximum leaf area index, harvest index, and light use efficiency. These parameters were estimated by multiple regression equations. Nitrogen application rate, seasonal amount of applied irrigation water, plant population, maximum applied water in flood irrigation, and mean daily solar input before and after flowering are model inputs. Furthermore, the transplanting, flowering, and harvest dates should be specified. The model was calibrated for a lowland local rice cultivar (Champa-Kamfiroozi) in the Kooshkak area (semi-arid climate), Fars province, I.R. of Iran, with data from an experiment with five irrigation treatments and three nitrogen application rates in two consecutive years. The model produced good estimates of dry matter and grain yields. The accuracy of the model was verified with independent data from other experiments in the study area and in the northern parts of Iran with sub-humid climate.</description><identifier>ISSN: 1537-5110</identifier><identifier>EISSN: 1537-5129</identifier><identifier>DOI: 10.1016/j.biosystemseng.2005.09.004</identifier><identifier>CODEN: BEINBJ</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>accuracy ; Agronomy. Soil science and plant productions ; Biological and medical sciences ; Biometrics, statistics, experimental designs, modeling, agricultural computer applications ; dry matter accumulation ; estimation ; fertilizer application ; flowering ; Fundamental and applied biological sciences. Psychology ; Generalities. Biometrics, experimentation. Remote sensing ; grain yield ; growth models ; harvest date ; irrigation ; leaf area ; leaf area index ; model validation ; nitrogen ; nitrogen fertilizers ; regression analysis ; rice ; simulation models ; solar radiation ; subhumid zones ; water ; water requirement</subject><ispartof>Biosystems engineering, 2006, Vol.93 (1), p.25-34</ispartof><rights>2005 Silsoe Research Institute</rights><rights>2006 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c412t-ec4681f336fa180d77f0c94ef2bf8c738f4c7388d823448309145a29a5c5bebb3</citedby><cites>FETCH-LOGICAL-c412t-ec4681f336fa180d77f0c94ef2bf8c738f4c7388d823448309145a29a5c5bebb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1537511005002151$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,4010,27900,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17462166$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Pirmoradian, N.</creatorcontrib><creatorcontrib>Sepaskhah, A.R.</creatorcontrib><title>A Very Simple Model for Yield Prediction of Rice under Different Water and Nitrogen Applications</title><title>Biosystems engineering</title><description>The ability to accurately model crop water and nitrogen requirements can improve irrigation and nitrogen application management. Forecasting of rice yield at the time of planting, under different irrigation and nitrogen application management programmes, is possible with a rice yield simulation model calibrated for the study area. In this study, a very simple model (VSM) was developed for simulation of rice grain and biomass yields under different irrigation and nitrogen application management strategies. The model assumes a triangular pattern for leaf area changes and proportionately of biomass accumulation to the intercepted solar radiation. The model can provide the grain and biomass yields based on maximum leaf area index, harvest index, and light use efficiency. These parameters were estimated by multiple regression equations. Nitrogen application rate, seasonal amount of applied irrigation water, plant population, maximum applied water in flood irrigation, and mean daily solar input before and after flowering are model inputs. Furthermore, the transplanting, flowering, and harvest dates should be specified. The model was calibrated for a lowland local rice cultivar (Champa-Kamfiroozi) in the Kooshkak area (semi-arid climate), Fars province, I.R. of Iran, with data from an experiment with five irrigation treatments and three nitrogen application rates in two consecutive years. The model produced good estimates of dry matter and grain yields. The accuracy of the model was verified with independent data from other experiments in the study area and in the northern parts of Iran with sub-humid climate.</description><subject>accuracy</subject><subject>Agronomy. Soil science and plant productions</subject><subject>Biological and medical sciences</subject><subject>Biometrics, statistics, experimental designs, modeling, agricultural computer applications</subject><subject>dry matter accumulation</subject><subject>estimation</subject><subject>fertilizer application</subject><subject>flowering</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Generalities. Biometrics, experimentation. Remote sensing</subject><subject>grain yield</subject><subject>growth models</subject><subject>harvest date</subject><subject>irrigation</subject><subject>leaf area</subject><subject>leaf area index</subject><subject>model validation</subject><subject>nitrogen</subject><subject>nitrogen fertilizers</subject><subject>regression analysis</subject><subject>rice</subject><subject>simulation models</subject><subject>solar radiation</subject><subject>subhumid zones</subject><subject>water</subject><subject>water requirement</subject><issn>1537-5110</issn><issn>1537-5129</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNqNkF1rFDEUhoMoWFd_gwHRux1PPmYmg1dLW22h2mJbxauYyZwsWWaTMZkV9t83yxbFO2-SHHjec04eQt4wqBiw5v2m6n3M-zzjNmNYVxygrqCrAOQTcsJq0S5rxrunf94MnpMXOW8AWN3K5oT8XNFvmPb01m-nEennOOBIXUz0h8dxoDcJB29nHwONjn71FukuDJjomXcOE4aZfjdzqU0Y6Bc_p7jGQFfTNHprDrH8kjxzZsz46vFekPuP53enF8ur60-Xp6urpZWMz0u0slHMCdE4wxQMbevAdhId752yrVBOHk41KC6kVAI6JmvDO1Pbuse-Fwvy7th3SvHXDvOstz5bHEcTMO6yZp3kStSqgB-OoE0x54ROT8lvTdprBvpgVW_0P1b1waqGTherJf32cYzJ1owumWB9_tuiSOWsaQr3-sg5E7VZp8Lc33JgAhjUDS-_WJDzI4HFym-PSWfrMdgiPKGd9RD9f230AE-1nvY</recordid><startdate>2006</startdate><enddate>2006</enddate><creator>Pirmoradian, N.</creator><creator>Sepaskhah, A.R.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>C1K</scope></search><sort><creationdate>2006</creationdate><title>A Very Simple Model for Yield Prediction of Rice under Different Water and Nitrogen Applications</title><author>Pirmoradian, N. ; Sepaskhah, A.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c412t-ec4681f336fa180d77f0c94ef2bf8c738f4c7388d823448309145a29a5c5bebb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>accuracy</topic><topic>Agronomy. Soil science and plant productions</topic><topic>Biological and medical sciences</topic><topic>Biometrics, statistics, experimental designs, modeling, agricultural computer applications</topic><topic>dry matter accumulation</topic><topic>estimation</topic><topic>fertilizer application</topic><topic>flowering</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Generalities. Biometrics, experimentation. Remote sensing</topic><topic>grain yield</topic><topic>growth models</topic><topic>harvest date</topic><topic>irrigation</topic><topic>leaf area</topic><topic>leaf area index</topic><topic>model validation</topic><topic>nitrogen</topic><topic>nitrogen fertilizers</topic><topic>regression analysis</topic><topic>rice</topic><topic>simulation models</topic><topic>solar radiation</topic><topic>subhumid zones</topic><topic>water</topic><topic>water requirement</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pirmoradian, N.</creatorcontrib><creatorcontrib>Sepaskhah, A.R.</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Biosystems engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pirmoradian, N.</au><au>Sepaskhah, A.R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Very Simple Model for Yield Prediction of Rice under Different Water and Nitrogen Applications</atitle><jtitle>Biosystems engineering</jtitle><date>2006</date><risdate>2006</risdate><volume>93</volume><issue>1</issue><spage>25</spage><epage>34</epage><pages>25-34</pages><issn>1537-5110</issn><eissn>1537-5129</eissn><coden>BEINBJ</coden><abstract>The ability to accurately model crop water and nitrogen requirements can improve irrigation and nitrogen application management. Forecasting of rice yield at the time of planting, under different irrigation and nitrogen application management programmes, is possible with a rice yield simulation model calibrated for the study area. In this study, a very simple model (VSM) was developed for simulation of rice grain and biomass yields under different irrigation and nitrogen application management strategies. The model assumes a triangular pattern for leaf area changes and proportionately of biomass accumulation to the intercepted solar radiation. The model can provide the grain and biomass yields based on maximum leaf area index, harvest index, and light use efficiency. These parameters were estimated by multiple regression equations. Nitrogen application rate, seasonal amount of applied irrigation water, plant population, maximum applied water in flood irrigation, and mean daily solar input before and after flowering are model inputs. Furthermore, the transplanting, flowering, and harvest dates should be specified. The model was calibrated for a lowland local rice cultivar (Champa-Kamfiroozi) in the Kooshkak area (semi-arid climate), Fars province, I.R. of Iran, with data from an experiment with five irrigation treatments and three nitrogen application rates in two consecutive years. The model produced good estimates of dry matter and grain yields. The accuracy of the model was verified with independent data from other experiments in the study area and in the northern parts of Iran with sub-humid climate.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.biosystemseng.2005.09.004</doi><tpages>10</tpages></addata></record> |
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subjects | accuracy Agronomy. Soil science and plant productions Biological and medical sciences Biometrics, statistics, experimental designs, modeling, agricultural computer applications dry matter accumulation estimation fertilizer application flowering Fundamental and applied biological sciences. Psychology Generalities. Biometrics, experimentation. Remote sensing grain yield growth models harvest date irrigation leaf area leaf area index model validation nitrogen nitrogen fertilizers regression analysis rice simulation models solar radiation subhumid zones water water requirement |
title | A Very Simple Model for Yield Prediction of Rice under Different Water and Nitrogen Applications |
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