In previous research, either one cultivar was studied to investigate the effect of source and sink strength on fruit-set (Pettigrew, 1994
; Marcelis et al., 2004
) or fruit-set on different cultivars was studied without any explanation of the possible causes of the observed differences (Egli and Bruening, 2006
). In the present study, cultivar differences were compared with experimental and modelling approaches for the analyses of fruit-set, fruit harvest and plant yield. Temporal heterogeneity of fruit-set occurred for pepper plants with wave-like patterns over the fruiting period of the plant: the larger the fruit, the larger the c.v. of fruit-set and fruit yield for different weeks (Table ), thus affecting fruit yield between the cultivars (Table , Fig. ). Simulation showed that large-fruited cultivars need a higher source–sink ratio for fruit-set (threshold), which means higher demand for assimilates per fruit (Table ).
The GREENLAB model was used to study the source–sink dynamics of individual organ growth and link it to fruit-set and fruit yield for different cultivars with variations of fruit size. The advantage of this model over our previous model (Wubs et al., 2009a
) is that the temporal and spatial positions of fruit-set (Fig. ) were considered and their effects on plant growth and yield were quantified. One of the results of this study compared with earlier GREENLAB models (Yan et al., 2004
; Guo et al., 2006
) was to introduce the measured potential fruit growth rate (Marcelis and BaanHofman-Eijer, 1995
) into the GREENLAB model to represent the fruit sink strength. The sink strength of each organ then has units of (g GC−1
) and represents the ability to compete for assimilates instead of a relative value compared with the leaf blade. An individual organ's absolute share of the currently available assimilates depends on the number, type and expansion status of other organs competing for the same resources.
Reduced heterogeneity of fruit-set was achieved through different ways in our simulation with changing model parameter values (Tables and ): increasing source strength; decreasing vegetative sink strength and source–sink ratio for fruit-set and flower appearance rate; and harvesting fruit earlier. Generally, reducing this heterogeneity, by increasing source strength and decreasing vegetative sink strength, increased fruit-set and weight for all cultivars. This result agreed well with the experimental study of Marcelis et al. (2004)
. When we decreased the required source–sink ratio for fruit-set, the number of fruits retained on the plant increased, and fruit competition for assimilates significantly increased. However, individual fruit dry weight decreased significantly (Table ). The changes to source and vegetative sink strength could be achieved by plant breeding, which may be able to develop a plant with high yield and low variation of fruit-set and harvest.
In commercial production, growers benefit from less variation in fruit production leading to relatively constant prices and labour requirements for harvest. Several methods have been used to reduce or even avoid cyclical fluctuations in fruit-set and yield: different planting dates and fruit pruning (Heuvelink et al., 2004
); plant growth regulators (Wien and Zhang, 1991
); temperature regulators (Van Henten et al., 2006
); or parthenocarpic fruit growth (Heuvelink and Körner, 2001
). From our sensitivity analysis, we propose that a decrease in fruit size at harvest results in more fruit-set, and thus more potential harvest fruits and less variation of fruit production are obtained. Similar results were obtained on cucumber by Marcelis (1994)
. The reason for this is that when fruit was harvested earlier, a sink was removed. The total sink strength of fruits decreases and fruit-set can increase. If fruit-set increased, the variation in fruit-set decreased. This is one strategy for reducing yield fluctuation for pepper plants. However, more experiments to validate the response to these harvest criteria are needed in future studies.
In our simulation, constant specific leaf area (SLA) and leaf functioning time were used. However, studies have shown that SLA is affected by light intensity (Shipley, 2002
), temperature (Nilwik, 1981
) and source–sink ratio (Marcelis et al., 2004
). Leaf senescence is also determined at the whole-plant level by source–sink relationships in the plant (Rajcan and Tollenaar, 1999
). Therefore, quantitative relationships of SLA and leaf senescence with plant carbon balance should be established and introduced into our model in a future version.
FSPMs can simulate plant growth based on interactions among structural dynamics, external resources and the physiological processes that govern inter-organ competition with the source–sink concept, the key concept in competition theory representing the supply and demand for assimilates, respectively (Marcelis, 1994
). When the total sink strength is high, due to the presence of many growing fruits, flowers and young fruits are not able to compete for assimilates with the fast-growing fruits and hence abort. The results found in the current experiment are also likely to explain differences in fruit-set between cultivars with different fruit sizes in other crops such as pumpkin, melon, tomato and cucumber. Furthermore, the effect of dynamic fruit-set pattern on plant architecture can be simulated with a three-dimensional crop architecture model. Such a model can be output for each simulation time step and used to calculate precise light interception and energy balances for a single plant and stand in a greenhouse (Buck-Sorlin et al., 2010