A simple quantitative model to predict leaf area index in sorghum

dc.citation.doidoi:10.2134/agronj2013.0311en_US
dc.citation.epage226en_US
dc.citation.issue1en_US
dc.citation.jtitleAgronomy Journalen_US
dc.citation.spage219en_US
dc.citation.volume106en_US
dc.contributor.authorNarayanan, Sruthi
dc.contributor.authorAiken, Robert M.
dc.contributor.authorPrasad, P. V. Vara
dc.contributor.authorXin, Zhanguo
dc.contributor.authorPaul, George
dc.contributor.authorYu, Jianming
dc.contributor.authoreidraikenen_US
dc.contributor.authoreidvaraen_US
dc.date.accessioned2014-04-07T20:05:40Z
dc.date.available2014-04-07T20:05:40Z
dc.date.issued2014-04-07
dc.date.published2014en_US
dc.description.abstractLeaf area index (LAI) is a widely used physiological parameter to quantify the vegetative canopy structure of crops. Over the years, several models to estimate LAI have been developed with various degrees of complexity and inherent shortcomings. The LAI simulation models proposed so far for sorghum [Sorghum bicolor (L.) Moench] either lack details of the leaf area dynamics of expanding leaves or demand exhaustive measurements. The objective of this study was to develop a simple quantitative model to predict the LAI of sorghum by introducing a new method for simulation of the leaf area of expanding leaves. The proposed model relates LAI to thermal time. It calculates LAI from an algorithm considering the total number of mature leaves, the area of mature leaves, the area of expanding leaves, and plant density. The performance of the model was tested using LAI data collected using a nondestructive method under field conditions. The slope of the regression of modeled LAI on observed LAI varied for photoperiod-sensitive and -insensitive genotypes in 2010. The coefficients of determination (R²) between modeled and observed LAI were 0.96 in 2009 and 0.99 (photoperiod insensitive) and 0.95 (photoperiod sensitive) in 2010. The inclusion of expanding leaves in the model improved its accuracy. The model provides an accurate estimate of LAI at any given day of the vegetative growing season based only on thermal time and making use of default coefficients demonstrated in this research.en_US
dc.identifier.urihttp://hdl.handle.net/2097/17295
dc.language.isoen_USen_US
dc.relation.urihttps://www.agronomy.org/publications/aj/articles/106/1/219en_US
dc.rightsPermission to archive granted by American Society of Agronomy, Feb. 28, 2014.en_US
dc.subjectLeaf area indexen_US
dc.subjectSorghumen_US
dc.titleA simple quantitative model to predict leaf area index in sorghumen_US
dc.typeArticle (publisher version)en_US

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