Modelling indeterminate development, dry matter partitioning andthe effect of nitrogen supply in tomato with the generic STICScrop–soil model
2014
Valdés-Gómez, H. | Gary, Christian, C. | Brisson, Nadine, N. | Matus, F. | Facultad de Ciencias Agrarias ; Universidad de Talca | Fonctionnement et conduite des Systèmes de culture Tropicaux et Méditerranéens ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Agroclim (AGROCLIM) ; Institut National de la Recherche Agronomique (INRA) | Universidad de la frontera [Tecumo, Chile] = University of La Frontera [Tecumo, Chile] = Université de La Frontera [Tecumo, Chili] (UFRO)
International audience
显示更多 [+] 显示较少 [-]英语. In crop models, yield depends on complex interactions between biomass production, crop development and assimilate partitioning, particularly with crop species exhibiting indeterminate patterns of development and submitted to limiting soil resources. The present study aimed at: (i) evaluating the adaptability of the STICS model based on the boxcartrain approach for the simulation of the fruit development and growth of tomato cultivars with different growth habits and (ii) evaluating the hypothesis that both carbon and nitrogen limitations alter fruit setting. Four experiments were carried out to test the model, one on a vine type tomato cultivar grown in a greenhouse and three on bush type tomato cultivars grown in open field, at the experimental station Panguilemo that belongs to Talca University in Chile. Total dry matter, nitrogen uptake, leaf area index and fruit number were satisfactorily simulated (model efficiency (EF) > 82%), whereas the fruit dry matter production was predicted with a lower precision (EF = 63%). The simulations showed that the indeterminate growth features incorporated in the STICS model were appropriate to simulate the crop growth and development for both the vine and bush types of tomato cultivars. Introducing a stress nitrogen index in the algorithm to calculate fruit set improved the quality of prediction of the fruit number.
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