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Published on: April 17, 2015
Modelling ontogenetic changes of nitrogen and water content in lettuce
Ido Seginer1, Peter Bleyaert, Maaike Breugelmans
1Faculty of Civil and Environmental Engineering, Division of Environmental Engineering, Water and Agriculture, Technion, Haifa 32000, Israel. segineri@tx.technion.ac.il
Background And Aims:
It is well established that the nitrogen content of plants, including lettuce, decreases with time. It has also been observed that water content of lettuce increases between planting and harvest. This paper is an attempt at modelling these observations.
Methods:
An existing dynamic model (Nicolet), designed to predict growth and nitrate content of glasshouse lettuce, is modified to accommodate the ontogenetic changes of reduced-nitrogen and water contents (on a dry matter basis). The decreasing reduced-N content and the increasing water content are mimicked by dividing the originally uniform plant into 'metabolically active' tissue and 'support' tissue. The 'metabolic' tissue is assumed to contain a higher nitrogen content and a lower water content than the 'support' tissue. As the plants grow, the ratio of 'support' to 'metabolic' tissue increases, resulting in an increased mean water content and a decreased reduced-N content. Simulations with the new model are compared with experimental glasshouse data over four seasons.
Key Results:
The empirical linear relationship between water and reduced-N contents, matches, to a good approximation, the corresponding relationship based on the model. The agreement between the two makes it possible to effectively uncouple the estimation of the 'ontogenetic' parameters from the estimation of the other parameters. The growth and nitrate simulation results match the data rather well and are hardly affected by the new refinement. The reduced-N and water contents are predicted much better with the new model.
Conclusion:
Prediction of nitrogen uptake for the substantial nitrate pool of lettuce depends on the water content. Hence, the modified model may assist in making better fertilization decisions and better estimates of nitrogen leaching.
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