Generation of mechanistic variability in a process-based object-oriented plant model

• Published in: Ecological modelling 1993, Vol.67 (2), p.285-306
• Main Authors: Sequeira, Ronaldo Antonio, Stone, Nicholas D., Makela, Merry E., El-Zik, Kamal M., Sharpe, Peter J.H.
• Format: Article
• Language: English
• Subjects: age; Agronomy. Soil science and plant productions; Animal and plant ecology; Animal, plant and microbial ecology; Autoecology; Biological and medical sciences; crecimiento; croissance; dimension; dimensions; edad; etapas de desarrollo de la planta; Fundamental and applied biological sciences. Psychology; Gossypium; growth; modele; modelos; plant developmental stages; Plants and fungi; simulacion; simulation; stade de developpement vegetal
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/0304-3800(93)90010-P

A cotton crop model based on individual plant developmental behavior and variability was developed. Object-oriented simulation (OOS) provided the conceptual basis for the new model structure. The procedural model, COTSIM, provided the theoretical background for cotton plant development. Data collected during 1987 from field-grown cotton were used for model development and verification, and data from 1988 were used for model validation. The model predicted mass accretion and production of organs within the patterns and magnitudes observed in the field. The model also predicted crop development aspects that had not previously been described by procedural models. Age and size of leaves and fruit and associated developmental variability were included in the model through representation of objects and their variable behavior defined by their position on the plant and how this constrains their growth. Observed variability was the result of the aggregate behavior of components. Variability in our OOS model is an output as opposed to being an input in most procedural plant models. The model has recreated both realistic plants and populations in a mechanistic simulation. Object-oriented models are an important step towards common structures and languages for model design and the development of simulations. It was noted that increased mechanistic detail resulted in an increase of procedure calls (messages) and a five-fold increase in model run time.