Evaluation of a Dynamic Simulation Model for Tomato Crop Growth and Development

A dynamic simulation model for tomato crop growth and development,TOMSIM, is evaluated. Potential crop growth and daily crop grossassimilation rate (P_gc,d) is computed by integration of leafassimilation rates over total crop leaf area throughout theday. Crop growth results fromP_gc,dminus maintenance respirationrate (R_m), multiplied by the conversion efficiency. Dry matterdistribution is simulated, based on the sink strength of theplant organs, which is quantified by their potential growthrate. Within the plant, individual fruit trusses and vegetativeunits (three leaves and stem internodes between two trusses)are distinguished. Sink strength of a truss or a vegetativeunit is described as a function of its developmental stage.In this paper, emphasis is on the interactions between the twosubmodels of, respectively, dry matter production and dry matterdistribution. Sensitivity analysis showed that global radiation,CO₂concentration, specific leaf area (SLA) and the developmentalstage of a vegetative unit at leaf pruning had a large influenceon crop growth rate, whereas temperature, number of fruits pertruss, sink strength of a vegetative unit and plant densitywere less important. Leaf area index (LAI) was very sensitiveto SLA and the developmental stage of a vegetative unit at leafpruning. Temperature did not influence the simulated R_m, asincreased respiration rate per unit of biomass at higher temperatureswas compensated by a decrease in biomass. The model was validatedfor four glasshouse experiments with plant density and fruitpruning treatments, and on data from two commercially growncrops. In general, measured and simulated crop growth ratesfrom 1 month after planting onwards agreed reasonably well,average overestimation being 12%. However, crop growth ratesin the first month after planting were overestimated by 52%on average. Final crop dry mass was overestimated by 0–31%,due to inaccurate simulation of LAI, resulting partly from inaccurateSLA prediction, which is especially important at low plant densityand in a young crop.Copyright 1999 Annals of Botany Company Crop growth, dry matter production, glasshouse, leaf area,Lycopersicon esculentum, partitioning, simulation model, tomato, TOMSIM.