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Tillering regulates the yield of cereal grains through manipulating the number of extra panicles and assimilates availability for grain formation. It is one of the key plastic traits of cereals, showing response to changes in growing environments. It is an important agronomic traits related to crop adaptation to changed environments, as high tillering genotypes suits better in favourable environment to maximize resource use, while low tillering one may be more desirable for stressed conditions to reduce resource loss (Daisuke Fujita et al., 2010). As a special kind of branch of monocotyledonous plants, tillers are one of the fundamental components of plant architecture regulating the yield of cereals (Kuraparthy et al., 2008), as it is directly linked to the number of panicles formed (Aarati et al., 2003; Beall et al., 1991; Chai et al., 2006). Tillering plays an important role in biomass accumulation as intercepted radiation is increased with the greater leaf area associated with tillering. In adverse environmental conditions when water for transpiration is limited, low tillering is expected to allow more efficient use of available water. Production of few but vigorous productive tillers can restrict plant size, which can increase post-anthesis water availability and grain yield in water limited conditions (Hammer, 2006). However, excessive tillering can lead to high tiller abortion, poor grain set, and small panicle size and reduce tiller leaf area for photo-assimilation thereby reduce grain yield (Kariali and Mohapatra, 2007). Therefore, a clear understanding of regulation of tillering in cereals is required to identify genotypes with adaptation to target environments.
The mechanism of tiller development is characterized by the initiation of axillary meristem, formation of axillary bud and subsequent outgrowth (Schmitz and Theres, 2005). All these three stages are regulated by internal genetic back ground, external environment and their interactions (Anterola et al., 2009; Beveridge et al., 2003; Shimizu-Sato et al., 2009). The genetic mechanism and environmental regulation of tiller dynamics triggers the physiological mechanism happening in the cell. Discoveries achieved in this area revealed that an array of genes with their coordinated expression in common networks controls the axillary branching in Arabiodopsis, tomato, petunia and pea (Reviewed in (Yaish, 2010),(Doust, 2007); (Dun et al., 2006; Leyser, 2005; McSteen, 2009; McSteen and Leyser, 2005). Some orthologous genes of those gene networks have also been found in rice and maize (Li et al., 2003; Mao et al., 2007; Takeda et al., 2003). All these genes were found to control shoot branching through the alteration of different transcriptional and hormonal pathways (Reviewed in (Yaish, 2010). However, the exact mechanism of hormonal and transcriptional regulation of tillering is still unclear. Environmental parameters such as nutrient supply, irradiance, and spacing influence growth of emergent tillers in the field (De Datta, 1981; Yoshida, 1981). In conditions where tillering is not affected by water or nitrogen stress, the plant carbon balance, and in particular the availability of assimilates, drives tiller production (Lafarge, 2006; Mitchell, 1953; Ong and Marshall, 1979). The availability of assimilates for tillering decreases with either increasing demand by the main culm or a reduced supply from photosynthesis. Assimilate demand of the main culm increases at high temperatures (Bos and Neuteboom, 1998; Cannell, 1969; Major et al., 1982) in response to a high leaf growth rate (Lafarge et al., 1998). Assimilate supply is reduced by low light interception, resulting from low incident radiation, a short photoperiod, high planting density or defoliation (Bos and Neuteboom, 1998; Cannell, 1969; Gautier et al., 1999; Gerik and Neely, 1987). A change in light quality associated with increases in plant density has also been shown to affect tiller production. In crops grown with non-limiting water and nutrients, Deregibus et al. (1985) and Ballare et al. (1987) observed a decrease in the ratio of redÂ :Â far-red light and in tiller production as density increased; this occurred prior to any appreciable shading or depletion of assimilate resources.
One glass house and two field experiments were carried out in two sorghum growing seasons under different environmental regimes (Table 2). Experiment 1 was sown in September 2008 in a glasshouse at the University of Queensland in St Lucia and Experiment 2 and Experiment 3 were sown in December 2008 and January 2010 respectively in the field at Hermitage Research Station, Warwick, Queensland. In Exp-1, maximum and minimum air temperature and total radiation were logged daily using a datalogger (CR10; Campbell Scientific). Thermal time was calculated from hourly data, using broken linear relationship with cardinal temperatures of 11, 30 and 42 for the base, optimum and maximum temperature (Hammer et al., 1993; Kim et al., 2010a; Kim et al., 2010b). For Exp. 2 and 3, weather data were recorded at a centrally located weather station. Daily accumulated radiation was also calculated. Both temperature and radiation data were measured from first 45 days after sowing as most of the tillers appeared within this duration. Exp. 1 tended to have higher temperature and Exp. 2 and Exp 3 higher daily radiation (Table 2).
Should we include length and width of leaf no 5, 7 and 9 or any one? It is interesting that LW5 is not significantly correlated with tiller number, correlation increased with higher (larger) leaf number. We can explain leaf width increase rate as a component of resource demand or as a blocking component of intercepted radiation at the tillering site and sink.
Fig. 3 Biplots showing genetic correlations among traits
???? Should we include biplots of each experiment?
Physiological determinants of tillering: Are those genetic?
Fig 4 Scatter plots showing genetic relationship of tillering with physiological parameters (ID, LLIR and LWIR as components of resource demand for other growth and developmental processes and S/D index as an indicator of resource availability for tillering).
??? I am not sure, we should include these scatter plots or not, though genetic correlation of this traits were depicted in biplots. But these scatter plots describe the amount of genetic variability of tillering can be explained by those parameters.
Fig 5 Scatter plot of S/D index versus total tiller number in two environments shows that the regulation of tillering through supply-demand in mainly environmental not genetic. Tillering of all the genotypes is higher in environments with high supply-demand ratio.