Cereal yield is determined by the accumulated photosynthetic assimilates over the entire growing season that are partitioned into the caryopses. Improvements in crop management and genetic gain in harvest index are largely responsible for the increased cereal yields over the last decades (Austin 1999; Peng et al. 2008). However, it has been argued that cereal production is now approaching a plateau and further increases in yield will necessitate an increase in photosynthesis (Austin 1994; Mitchell & Sheehy 2006; Lawson, Kramer & Raines 2012).
Crop photosynthesis accumulated for the entire growing season depends on the ability of the crop to build up and maintain a canopy for capturing incoming light, and also on the photosynthetic capacity and efficiency of leaves. There may be chances to increase the light capture by improving early leaf area growth rate or by introducing ‘stay green’ genes to extend the growing season (Long et al. 2006). For rice, however, leaf area dynamics and canopy architecture may have been effectively optimized for maximum light capture through breeding (Horton 2000). Any further increase in photosynthesis of the rice crop may largely have to come from improved leaf photosynthesis, although there may still be scope to improve canopy architecture. Photosynthesis per unit leaf area seems to have been improved already as suggested by experimental comparisons of old and modern varieties of cereals, including rice, in concert with improvements in harvest index and grain number (Fischer & Edmeades 2010).
Given that crop genetic transformation is becoming increasingly routine, opportunities for improving leaf-level photosynthesis via genetic engineering have been extensively explored, by either experimental approaches or theoretical computation. Approaches include, for example, designing more efficient ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco; Mueller-Cajar & Whitney 2008; Whitney & Sharwood 2008); exploiting existing interspecific variation in Rubisco efficiency (Zhu, Portis & Long 2004a); increasing RuBP regeneration and light reaction (Miyagawa, Tamoi & Shigeoka 2001; Peterhansel, Niessen & Kebeish 2008; Rott et al. 2011); increasing mesophyll conductance (Uehlein et al. 2008); introducing CO2-concentrating mechanism into C3 crops (Price et al. 2008); introducing CO2-concentrating mechanism with Kranz anatomy into C3 crops (von Caemmerer, Quick & Furbank 2012); short-circuiting photorespiration (Maurino & Peterhansel 2010); and increasing the rate of transition from photoprotection (Zhu et al. 2004b). Long et al. (2006) estimated that these ambitious approaches, if successful, would need research efforts of 10–30 years, depending on the avenues to be used.
Leaf photosynthesis could be improved not only through transgenic biotechnology, but also through the exploitation of natural variation with a conventional breeding approach. Parry et al. (2011) indicated that mining existing genetic variation could be the most efficient method for short-term improvements (<5 years). Recently, quantitative trait loci (QTLs) related to different photosynthetic parameters have been successfully mapped (Takai et al. 2009; Adachi et al. 2011; Gu et al. 2012a). Furthermore, Gu et al. (2012b), using the biochemical photosynthesis model of Farquhar, von Caemmerer & Berry (1980) as adapted by Yin et al. (2009), successfully dissected genetic variation of leaf photosynthesis present in an introgression line (IL) population into different biophysical and biochemical components. Their analysis showed that by using genetic variation in all components, leaf-level photosynthesis could potentially be increased by ca. 20% through marker-assisted selection.
However, photosynthesis rate per unit area of leaf does not correlate well with crop yield (Evans & Dunstone 1970; Teng et al. 2004). This has led to a common notion that increasing leaf photosynthesis is not a useful strategy to increase crop yield (Richards 2000; Zhao et al. 2008). Actually, this notion was confirmed by our own work on the IL population: among the many physiological parameters examined, leaf photosynthesis was not important in determining the differences in crop yield among the ILs observed in a field experiment, either under drought or under well-watered conditions (Gu 2013). This lack of persistence of variation across scales is probably due to the complex hierarchy from leaf-level photosynthesis to crop yield and to interaction and feedback mechanisms occurring between physiological components within the individual plant, between plants of the same crop and between the crop and the environment. Moreover, relationships between leaf photosynthesis and crop yields may depend on genetic background of plant materials. These complexities might mask the potential contribution of the small within-population variation in leaf photosynthesis to the variation in final crop yield. Therefore, modelling has been a useful tool to investigate the potential of improved photosynthesis on crop productivity (Day & Chalabi 1988; Long et al. 2006).
In this paper, we used the process-based crop model GECROS (Yin & van Laar 2005) to examine the extent to which exploiting the natural genetic variation in leaf photosynthesis components can contribute to variation in canopy photosynthesis and in crop productivity in rice. The GECROS model combines sufficient physiological rigour for complex phenotypic responses with genotype-specific parameters. We used this model to scale up variation in leaf photosynthesis components as detected in our previous study (Gu et al. 2012b) to variation in canopy photosynthesis and in biomass productivity across the entire growing season for contrasting environments. Input parameter values for model simulation are only those derived from our previous results on QTLs for various leaf photosynthesis parameters, while other input parameters of the GECROS model are maintained the same across rice genotypes. In this way, potential confounding effects due to variation in other physiological processes can be avoided to exclusively illustrate the potential impact of natural genetic variation in leaf photosynthesis on crop productivity. We specifically hypothesize for potential larger persistence during scaling up than observed in previous studies from the literature if photosynthesis can be improved irrespective of light level, and test this hypothesis using the IL population segregating for QTLs related to both light-saturated and light-limited photosynthesis parameters.