A generalization of ordinary yield response functions
In an integrated model study of economics and ecology by Vatn et al. (1996), year specific expressions for crop yield response as a function of N-fertilization constituted an important link between the economic and ecological models. It was recognized, however, that data were too few to uniquely est...
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description | In an integrated model study of economics and ecology by
Vatn et al. (1996), year specific expressions for crop yield response as a function of N-fertilization constituted an important link between the economic and ecological models. It was recognized, however, that data were too few to uniquely estimate yield response functions in all desired simulation scenarios. In future model studies of this type, however, this problem can be reduced by using a generalization of ordinary yield response functions. An ordinary yield function and a generalized yield function were based on a modified version of the Michaelis–Menten equation, where the generalized type of yield function is taking account of the observed differences between years as to how the yield respond to nitrogen fertilizer. Measurements of dry matter in harvested barley grain from field experiments in south-east Norway (1970–1988) were used for parameter estimation and the predictive power was evaluated by cross validation. Based on the prize of grains and nitrogen fertilizers, both yield functions were used to calculate the expected economic optimum amount of N-fertilizer. The particular advantage of using a physiologically grounded functional relationship like the Michaelis–Menten equation, drawbacks and strengths of the two types of yield functions, and the use of dynamic crop-growth models to generate simulated data points of yield dry weight, for use in situations where real observations are few or completely unavailable, are discussed. |
doi_str_mv | 10.1016/S0304-3800(98)00031-3 |
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Vatn et al. (1996), year specific expressions for crop yield response as a function of N-fertilization constituted an important link between the economic and ecological models. It was recognized, however, that data were too few to uniquely estimate yield response functions in all desired simulation scenarios. In future model studies of this type, however, this problem can be reduced by using a generalization of ordinary yield response functions. An ordinary yield function and a generalized yield function were based on a modified version of the Michaelis–Menten equation, where the generalized type of yield function is taking account of the observed differences between years as to how the yield respond to nitrogen fertilizer. Measurements of dry matter in harvested barley grain from field experiments in south-east Norway (1970–1988) were used for parameter estimation and the predictive power was evaluated by cross validation. Based on the prize of grains and nitrogen fertilizers, both yield functions were used to calculate the expected economic optimum amount of N-fertilizer. The particular advantage of using a physiologically grounded functional relationship like the Michaelis–Menten equation, drawbacks and strengths of the two types of yield functions, and the use of dynamic crop-growth models to generate simulated data points of yield dry weight, for use in situations where real observations are few or completely unavailable, are discussed.</description><identifier>ISSN: 0304-3800</identifier><identifier>EISSN: 1872-7026</identifier><identifier>DOI: 10.1016/S0304-3800(98)00031-3</identifier><identifier>CODEN: ECMODT</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Agronomy. Soil science and plant productions ; APLICACION DE ABONOS ; Biological and medical sciences ; CARACTERES DE RENDIMIENTO ; Climatic parameters ; COMPOSANTE DE RENDEMENT ; CROP YIELD ; Cross validation ; ECOLOGIA ; ECOLOGIE ; ECOLOGY ; ECONOMIA ; Economic optimum N-fertilization ; ECONOMICS ; ECONOMIE ; FERTILISATION ; FERTILIZER APPLICATION ; Fundamental and applied biological sciences. Psychology ; General agronomy. Plant production ; Generalized yield response ; Michaelis–Menten equation ; MODELE ; MODELOS ; Nitrogen fertilization ; Nitrogen, phosphorus, potassium fertilizations ; RENDEMENT DES CULTURES ; RENDIMIENTO DE CULTIVOS ; Soil-plant relationships. Soil fertility. Fertilization. Amendments ; YIELD COMPONENTS</subject><ispartof>Ecological modelling, 1998-05, Vol.108 (1), p.227-236</ispartof><rights>1998 Elsevier Science B.V.</rights><rights>1998 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c389t-1a5e2b73da5f971599e617419c88e742ee8bf6e11924a202bca5cb4b4d52521a3</citedby><cites>FETCH-LOGICAL-c389t-1a5e2b73da5f971599e617419c88e742ee8bf6e11924a202bca5cb4b4d52521a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/S0304-3800(98)00031-3$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>309,310,314,780,784,789,790,3550,23930,23931,25140,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=2321171$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Vold, Arild</creatorcontrib><title>A generalization of ordinary yield response functions</title><title>Ecological modelling</title><description>In an integrated model study of economics and ecology by
Vatn et al. (1996), year specific expressions for crop yield response as a function of N-fertilization constituted an important link between the economic and ecological models. It was recognized, however, that data were too few to uniquely estimate yield response functions in all desired simulation scenarios. In future model studies of this type, however, this problem can be reduced by using a generalization of ordinary yield response functions. An ordinary yield function and a generalized yield function were based on a modified version of the Michaelis–Menten equation, where the generalized type of yield function is taking account of the observed differences between years as to how the yield respond to nitrogen fertilizer. Measurements of dry matter in harvested barley grain from field experiments in south-east Norway (1970–1988) were used for parameter estimation and the predictive power was evaluated by cross validation. Based on the prize of grains and nitrogen fertilizers, both yield functions were used to calculate the expected economic optimum amount of N-fertilizer. The particular advantage of using a physiologically grounded functional relationship like the Michaelis–Menten equation, drawbacks and strengths of the two types of yield functions, and the use of dynamic crop-growth models to generate simulated data points of yield dry weight, for use in situations where real observations are few or completely unavailable, are discussed.</description><subject>Agronomy. Soil science and plant productions</subject><subject>APLICACION DE ABONOS</subject><subject>Biological and medical sciences</subject><subject>CARACTERES DE RENDIMIENTO</subject><subject>Climatic parameters</subject><subject>COMPOSANTE DE RENDEMENT</subject><subject>CROP YIELD</subject><subject>Cross validation</subject><subject>ECOLOGIA</subject><subject>ECOLOGIE</subject><subject>ECOLOGY</subject><subject>ECONOMIA</subject><subject>Economic optimum N-fertilization</subject><subject>ECONOMICS</subject><subject>ECONOMIE</subject><subject>FERTILISATION</subject><subject>FERTILIZER APPLICATION</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General agronomy. Plant production</subject><subject>Generalized yield response</subject><subject>Michaelis–Menten equation</subject><subject>MODELE</subject><subject>MODELOS</subject><subject>Nitrogen fertilization</subject><subject>Nitrogen, phosphorus, potassium fertilizations</subject><subject>RENDEMENT DES CULTURES</subject><subject>RENDIMIENTO DE CULTIVOS</subject><subject>Soil-plant relationships. Soil fertility. Fertilization. Amendments</subject><subject>YIELD COMPONENTS</subject><issn>0304-3800</issn><issn>1872-7026</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><recordid>eNqFkE1PwzAMhiMEEmPwEyb1gBAcCnHStMkJTRNf0gQH4BylqTsFdc1IOqTx62m3aVdOPvjxa_shZAL0Fijkd--U0yzlktJrJW8opRxSfkRGIAuWFpTlx2R0QE7JWYxfPQRMshER02SBLQbTuF_TOd8mvk58qFxrwibZOGyqJGBc-TZiUq9bOzDxnJzUpol4sa9j8vn48DF7TudvTy-z6Ty1XKouBSOQlQWvjKhVAUIpzKHIQFkpscgYoizrHAEUywyjrLRG2DIrs0owwcDwMbna5a6C_15j7PTSRYtNY1r066ghzzLORdGDYgfa4GMMWOtVcMv-BQ1UD5L0VpIeDGgl9VaS5v3c5X6BidY0dTCtdfEwzDgDKKDHJjusNl6bReiR1zko1acJyIeY-10fexk_DoOO1mFrsXIBbacr7_455A-BwILm</recordid><startdate>19980501</startdate><enddate>19980501</enddate><creator>Vold, Arild</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>C1K</scope></search><sort><creationdate>19980501</creationdate><title>A generalization of ordinary yield response functions</title><author>Vold, Arild</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c389t-1a5e2b73da5f971599e617419c88e742ee8bf6e11924a202bca5cb4b4d52521a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Agronomy. Soil science and plant productions</topic><topic>APLICACION DE ABONOS</topic><topic>Biological and medical sciences</topic><topic>CARACTERES DE RENDIMIENTO</topic><topic>Climatic parameters</topic><topic>COMPOSANTE DE RENDEMENT</topic><topic>CROP YIELD</topic><topic>Cross validation</topic><topic>ECOLOGIA</topic><topic>ECOLOGIE</topic><topic>ECOLOGY</topic><topic>ECONOMIA</topic><topic>Economic optimum N-fertilization</topic><topic>ECONOMICS</topic><topic>ECONOMIE</topic><topic>FERTILISATION</topic><topic>FERTILIZER APPLICATION</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General agronomy. Plant production</topic><topic>Generalized yield response</topic><topic>Michaelis–Menten equation</topic><topic>MODELE</topic><topic>MODELOS</topic><topic>Nitrogen fertilization</topic><topic>Nitrogen, phosphorus, potassium fertilizations</topic><topic>RENDEMENT DES CULTURES</topic><topic>RENDIMIENTO DE CULTIVOS</topic><topic>Soil-plant relationships. Soil fertility. Fertilization. Amendments</topic><topic>YIELD COMPONENTS</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vold, Arild</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Ecological modelling</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vold, Arild</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A generalization of ordinary yield response functions</atitle><jtitle>Ecological modelling</jtitle><date>1998-05-01</date><risdate>1998</risdate><volume>108</volume><issue>1</issue><spage>227</spage><epage>236</epage><pages>227-236</pages><issn>0304-3800</issn><eissn>1872-7026</eissn><coden>ECMODT</coden><abstract>In an integrated model study of economics and ecology by
Vatn et al. (1996), year specific expressions for crop yield response as a function of N-fertilization constituted an important link between the economic and ecological models. It was recognized, however, that data were too few to uniquely estimate yield response functions in all desired simulation scenarios. In future model studies of this type, however, this problem can be reduced by using a generalization of ordinary yield response functions. An ordinary yield function and a generalized yield function were based on a modified version of the Michaelis–Menten equation, where the generalized type of yield function is taking account of the observed differences between years as to how the yield respond to nitrogen fertilizer. Measurements of dry matter in harvested barley grain from field experiments in south-east Norway (1970–1988) were used for parameter estimation and the predictive power was evaluated by cross validation. Based on the prize of grains and nitrogen fertilizers, both yield functions were used to calculate the expected economic optimum amount of N-fertilizer. The particular advantage of using a physiologically grounded functional relationship like the Michaelis–Menten equation, drawbacks and strengths of the two types of yield functions, and the use of dynamic crop-growth models to generate simulated data points of yield dry weight, for use in situations where real observations are few or completely unavailable, are discussed.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/S0304-3800(98)00031-3</doi><tpages>10</tpages></addata></record> |
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subjects | Agronomy. Soil science and plant productions APLICACION DE ABONOS Biological and medical sciences CARACTERES DE RENDIMIENTO Climatic parameters COMPOSANTE DE RENDEMENT CROP YIELD Cross validation ECOLOGIA ECOLOGIE ECOLOGY ECONOMIA Economic optimum N-fertilization ECONOMICS ECONOMIE FERTILISATION FERTILIZER APPLICATION Fundamental and applied biological sciences. Psychology General agronomy. Plant production Generalized yield response Michaelis–Menten equation MODELE MODELOS Nitrogen fertilization Nitrogen, phosphorus, potassium fertilizations RENDEMENT DES CULTURES RENDIMIENTO DE CULTIVOS Soil-plant relationships. Soil fertility. Fertilization. Amendments YIELD COMPONENTS |
title | A generalization of ordinary yield response functions |
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