Simulating Growth and Development of Tomato Crop

Crop models are powerful tools to test hypotheses, synthesize and convey knowledge, describe and understand complex systems and compare different scenarios. Models may be used for prediction and planning of production, in decision support systems and control of the greenhouse climate, water supply and nutrient supply. The mechanistic simulation of tomato crop growth and development is described in this paper. The main processes determining yield, growth, development and water and nutrient uptake of a tomato crop are discussed in relation to growth conditions and crop management. Organ initiation is simulated as a function of temperature. Simulation of leaf area expansion is also based on temperature, unless a maximum specific leaf area is reached. Leaf area is an important determinant for the light interception of the canopy. Radiation shows exponential extinction with depth in the canopy. For leaf photosynthesis several models are available. Transpiration is calculated according to the Penman-Monteith approach. Net assimilate production is calculated as the difference between canopy gross photosynthesis and maintenance respiration. The net assimilate production is used for growth of the different plant organs and growth respiration. Partitioning of assimilates among plant organs is simulated based on the relative sink strengths of the organs. The simulation of plant-nutrient relationships starts with the calculation of the demanded concentrations of different macronutrients for each plant organ with the demand depending on the ontogenetic stage of the organ. Subsequently, the demanded nutrient uptake is calculated from these demanded concentrations and dry weight of the organs. When there is no limitation in the availability at the root surface, the actual uptake will equal the demanded uptake. When the root system cannot fulfil the demand, uptake is less, plant nutrient concentration drops and crop production might be reduced. It is concluded that mechanistic crop models accurately simulate yield, growth, development and water and nutrient relations of greenhouse grown tomato in different climate zones. INTRODUCTION Models are powerful tools to test hypotheses, synthesize and convey knowledge, describe and understand complex systems and compare different scenarios. Crop models can be used to identify the desired growth conditions, explore effects of growth conditions related to the introduction of new technologies as well as identify the target traits of a crop that are particularly important for a specific environment. Models have been used in decision support systems, greenhouse climate and fertigation control, and prediction and planning of production. Models predicting growth and yield have been developed for a large number of crops including tomato (Dayan et al., 1993; Gary et al., 1995; Heuvelink, 1995a; Marcelis et al., 1998; Cooman, 2002; Cooman and Schrevens, 2003; Dai et al., 2006; Boote and Scholberg, 2006). In this paper, the main processes of a mechanistic crop model for tomato are analysed. The modeling concepts are based on the models TOMSIM (Heuvelink, 1999) and INTKAM (Gijzen, 1994; Marcelis et al., 2000). Processes addressed are leaf area Proc. IS on Tomato in the Tropics Eds.: G. Fischer et al. Acta Hort. 821, ISHS 2009 102 expansion, light interception, photosynthesis, respiration, fruit set, dry matter partitioning, transpiration, and water and nutrient uptake. SIMULATION OF CROP GROWTH A mechanistic crop growth model considers the main crop physiological processes (Fig. 1). The first process to be considered is the light interception by leaves. The calculated light interception depends mainly on leaf area of the crop and light incidence on the crop. Subsequently photosynthesis rate is calculated followed by calculations of the photosynthate use for respiration, conversion into structural dry matter (DM), the partitioning of DM among the different plant organs, and, finally, the fresh weight from the dry weight. Transpiration is calculated in parallel to calculations of photosynthesis. Also, nutrient demand and uptake are calculated. Leaf Area Leaf area is the most important factor that determines the fraction of incident radiation absorbed by the canopy. Leaf area formation rate is simulated as a function of number of stems per m, temperature and light intensity. In addition, the variety or root stock may affect leaf area expansion. Sub-optimal water and nutrient supply may limit leaf area expansion (see paragraph on water and nutrient uptake). Furthermore, the amount of leaf area of a tomato crop is affected by pruning of lower old leaves and sometimes some very young leaves. A leaf area index of 3 to 4 (m leaves m floor) appears to be optimal for tomato because then already about 90-95% of the visible light is intercepted by the canopy (Heuvelink et al., 2005). Measurements at seven commercial farms in the Netherlands showed that in the summer season light interception was on average 90% with values varying between 86 and 96%. Two approaches are predominantly used in crop models to simulate leaf area index: 1) leaf area is described as a function of plant developmental stage (or accumulated temperature sum); and 2) leaf area is computed from simulated leaf dry weight (Marcelis et al., 1998). In tomato, the initiation rate of leaves is primarily determined by temperature, while leaf area per leaf is also affected by assimilate supply, which depends on radiation (Heuvelink and Marcelis, 1996). Due to these effects of assimilate supply the first approach does not give reliable results in greenhouse production, where the correlation between temperature and radiation is lower than in open field situations. In the second approach, first leaf dry weight is calculated and then multiplied by the specific leaf area (SLA). However, SLA is far from constant during a growing season (Heuvelink, 1999) and tends to be negatively correlated with the radiation level. More appropriate is to combine the two approaches as first presented by Gary et al. (1995). Leaf area increase is potential if SLA of the whole canopy is smaller than the maximum SLA (SLAmax). Potential leaf area increase is computed as the product of the potential weight of new leaf material and the minimum SLA (SLAmin). If the actual SLA is greater than SLAmax (if the leaf is thinner than permitted), leaf area increase is equal to the product of the weight of new leaf material and SLAmax. SLAmax is a constant, and SLAmin is made dependent on the day of the year as described by Heuvelink (1999). Light Interception Crop production is often linearly related to cumulative intercepted radiation, although environmental conditions, such as CO2 concentration and temperature, may affect this relationship. In many cases, a linear relation between production and cumulative incident radiation is also found. Cockshull et al. (1992) observed over the first 12 weeks of harvest a fresh tomato production of 2 kg/100 MJ of incident solar radiation. Penning de Vries and Van Laar (1982) showed that the slope of the relationship between cumulative gross CO2 assimilation and cumulative intercepted photosynthetically active radiation increased with latitude (range 0 to 60°) when all other conditions were the same. This means that crop production in the tropics can be much lower than at higher latitudes