Plant development controls leaf area expansion in alfalfa plants competing for light.

摘要

Background and Aims: The growth of crops in a mixture is more variable and difficult to predict than that in pure stands. Light partitioning and crop leaf area expansion play prominent roles in explaining this variability. However, in many crops commonly grown in mixtures, including the forage species alfalfa, the sensitivity and relative importance of the physiological responses involved in the light modulation of leaf area expansion are still to be established. This study was designed to assess the relative sensitivity of primary shoot development, branching and individual leaf expansion in alfalfa in response to light availability. Methods: Two experiments were carried out. The first studied isolated plants to assess the potential development of different shoot types and growth periods. The second consisted of manipulating the intensity of competition for light using a range of canopies in pure and mixed stands at two densities so as to evaluate the relative effects on shoot development, leaf growth, and plant and shoot demography. Key Results: Shoot development in the absence of light competition was deterministic (constant phyllochrons of 32.5 degrees Cd and 48.2 degrees Cd for primary axes and branches, branching probability of 1, constant delay of 1.75 phyllochron before axillary bud burst) and identical irrespective of shoot type and growth/regrowth periods. During light competition experiments, changes in plant development explained most of the plant leaf area variations, with average leaf size contributing to a lesser extent. Branch development and the number of shoots per plant were the leaf area components most affected by light availability. Primary axis development and plant demography were only affected in situations of severe light competition. Conclusions: Plant leaf area components differed with regard to their sensitivity to light competition. The potential shoot development model presented in this study could serve as a framework to integrate light responses in alfalfa crop models.