Estimation of leaf area of soybeans grown under elevated carbon dioxide levels

Abstract

Leaf area (LA) data are required for describing numerous canopy processes. However, determining LA for a crop is both time consuming and labor intensive, requiring a substantial investment of resources. The objectives of this study were (1) to develop statistical models for estimating LA of field-grown soybean ( Glycine max ) plants grown in open-top field chambers from measurements of destructive (leaf and top dry weight) and non-destructive (leaf number, plant height, and branch length) variables, (2) to examine the effect of CO 2 concentration on these statistical relationships, and (3) to test the applicability of such models to independent data collected under different experimental conditions. Predictive models of LA based on either branch length (LA = 147.6· BRL 0·635 , CV = 11%) or top dry weight (LA = 328.8·TDW 0·731 , CV = 12%) were found to have the lowest coefficient of variation about the regression line, to be unaffected by increasing CO 2 , and to be reasonable predictors of LA under different growth conditions. Both leaf area per leaf and specific leaf area ratios changed with increasing CO 2 and growth conditions. Plant height was a poor predictor of LA.