Linking process-based potato models with light reflectance data: Does model complexity enhance yield prediction accuracy?

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• 作者：R. Quiroz^a ; H. Loayza^a ; C. Barreda^a ; C. Gavilá ; n^a ; ^b ; A. Posadas^a ; D.A. Ramí ; rez^a ; ^c ; ^{d.ramirez@cgiar.org}
• 关键词：D ; duration of leaf senescence ; DCPM ; dynamic- hourly scale- canopy photosynthesis model ; DTY ; dry tuber yield ; LUE ; light use efficiency ; CGM ; crop growth model ; CGMCC ; crop growth model parameterized using canopy cover ; CGMWDVI ; crop growth model parameterized using weighted difference vegetation index ; Chl ; total chlorophyll concentration per leaf area ; Chl max ; maximum total chlorophyll concentration per leaf area ; fi ; biomass fraction of organ i ; FLINT ; fraction of PAR intercepted by the fo
• 刊名：European Journal of Agronomy
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：82
• 期：part_PA
• 页码：104-112
• 全文大小：1001 K
• 卷排序：82

文摘

A reliable yield prediction was obtained using models of different complexity. The use of light reflectance data allowed an improvement in yield prediction. Senescence initiation was a main factor affecting tuber yield in the complex model. Transformation of radiation into biomass was more efficient under cloudy environment.