A Mechanistic Model for Describing Corn Plant Leaf Area Distribution

Abstract

Mathematical models to describe corn (Zea mays L.) leaf area are important components of computer simulation of corn growth and development. The objective of this research was to develop a mechanistic model to describe corn leaf growth. The hypothesis was that single leaf growth rate is the difference between potential positive leaf growth and reduced leaf growth rate because assimilates are also being utilized for stem, roots, other leaves, and reproductive organ growth. The model is S = S0exp[(L − L0)2/(−2k2)], where S is the area of individual leaf with rank L, S0 is the area of the largest individual leaf with rank L0, and k is a constant. The model was evaluated with 77 independent data sets from 64 genotype‐by‐environment combinations during 1989 to 2001. The fitting precision of the model to the data was high (multiple correlation coefficients ≥ 0.97), the model was applicable to widely different combinations of genotypes and environments, and the model was suitable for all leaves and green leaves only. Validation of the model for predicting leaf area was conducted using 174 data sets from 30 diverse cultivars and showed that the predicted leaf area was within 10% of the measured leaf area for 27 of the 30 cultivars with maximum deviation being 14%. The correlation of predicted leaf area with measured leaf area equaled 0.94 for all data. The reduced model for individual leaf area estimation is F = F0exp{−[F0(L − L0)]2/0.3542}, where F = S/ST and ST is sum of all leaf areas.