Development and Test of Prediction Model for Maize Leaf Appearance during Vegetative Phase

Abstract

Optimization strategies for crop growth have been explored, particularly with a view to maximization of yield and efficient use of irrigation water. Strategic use of agricultural resources requires knowledge of plant growth dynamics. Recent research establishes models describing plant growth. Use of more precise plant models, particularly those related to irrigation control may be useful in automation of irrigation scheduling. In this work, in addition to a system view-based thinking of plant growth, leaf appearance is considered. It is assumed that prediction of leaf appearance in maize plants is useful in forecasting growth stages, which allows planning for growth-stage dependent resource allocation for optimal growth. It can be shown that the appearance of new leaves corresponds to an observable decrease in leaf elongation rate. It is therefore possible to forecast timing of appearance of new leaves from the growth trajectory of older leaves. Based on the growth behavior of individual leaves, a linear approximative modeling approach is applied to maize plants in the vegetative phase. The predicted timing of end of leaf growth is compared to the experimentally observed appearance of new leaves. This novel application of sequenced linear models using different individual leaf models allows the prediction of appearance of leaves 4 and 5 to within 35 and 22 growing degree days respectively.