MecaNiCAL, a supply-demand model of carbon and nitrogen partitioning applied to defoliated grass 1. Model description and analysis

被引:17
作者
Tabourel-Tayot, F [1 ]
Gastal, F [1 ]
机构
[1] INRA, Ctr Rech Poitou Charentes, Stn Ecophysiol Plantes Fourrageres, F-86600 Lusignan, France
关键词
assumption; carbon supply; grass; light; model; nitrogen; partitioning; plant demand; root : shoot ratio;
D O I
10.1016/S1161-0301(98)00039-2
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
A model for the dynamic simulation of dry matter distribution between shoots and roots of a grass forage plant is presented. The objective of this work was to develop a relatively simple mechanistic model of grass growth to simulate the response of assimilate partitioning to variations in light and nitrogen supply based on an original theoretical scheme [Gillet, M., Lemaire, G., Gosse, G., 1984. Essai d'elaboration d'un schema global de la croissance des graminees forrageres. Agronomie 4 (1), 75-82]. In the model, called MecaNiCAL, C and N assimilates are partitioned between shoots and roots according to the availability of carbohydrate substrate, organ demands and a fixed priority between each demand. Demand related to organ synthesis is described as a function of the plant concentration in the organic nitrogen substrate and temperature. To stay within an acceptable range of complexity, the model is applied only in one vegetative regrowth performed on a hydroponic system with different light and nitrogen nutrition. Carbon and nitrogen acquisition per day are computed by independent submodels, which makes it possible to connect simple and robust functions of carbon assimilation and nitrogen uptake to the partitioning model. Carbon assimilation is simulated for a plant in a canopy, and nitrogen uptake is simulated by a function which depends on nitrogen plant requirements directly related to plant net photosynthesis and the amount of nitrogen available in the nutritive solution. All the assumptions used to describe assimilate partitioning are discussed in relation to knowledge of physiological processes in order to examine closely the limits of the model. (C) 1998 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:223 / 241
页数:19
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