SORGHUM Genotype and Environment Effects on Dynamics of Harvest Index during Grain Filling in Sorghum

chow and Sinclair, 1991), and sunflower (Helianthus annuus L.) (Chapman et al., 1993). An approach based on a linear rate of increase in harvest index Deficiencies in the HI approach, however, may be (HI) with time after anthesis has been used as a simple means to predict grain growth and yield in many crop simulation models. When associated with use of a constant rate of HI increase applied to diverse situations, however, this approach has been found across diverse environments, particularly for cool temto introduce significant error in grain yield predictions. Accordingly, peratures, and possible variation in maximum HI or this study was undertaken to examine the stability of the HI approach timing of cessation of linear increase in HI associated for yield prediction in sorghum [Sorghum bicolor (L.) Moench]. Four with other factors, such as crop maturity. In studies on field experiments were conducted under nonlimiting water and N HI dynamics in sunflower, Bange et al. (1998) showed conditions. The experiments were sown at times that ensured a broad that while rate of increase in HI was linear, the rate range in temperature and radiation conditions. Treatments consisted decreased with low temperature during grain filling. of two population densities and three genotypes varying in maturity. They also noted that duration of the period from antheFrequent sequential harvests were used to monitor crop growth, yield, sis to the onset of linear increase in HI (i.e., lag phase) and the dynamics of HI. Experiments varied greatly in yield and final HI. There was also a tendency for lower HI with later maturity. varied and was inversely related to temperature. HowHarvest index dynamics also varied among experiments and, to a ever, rate of increase in HI did not differ among levels lesser extent, among treatments within experiments. The variation of N for sunflower (Bange et al., 1998) or sorghum was associated mostly with the linear rate of increase in HI and timing (Muchow, 1988). of cessation of that increase. The average rate of HI increase was As crop models need to be applied across a diverse 0.0198 d 1, but this was reduced considerably (0.0147) in one experirange of environments in exploring strategies to imment that matured in cool conditions. The variations found in HI prove crop management, such as sowing date (e.g., Mudynamics could be largely explained by differences in assimilation chow et al., 1994), it is important that they incorporate during grain filling and remobilization of preanthesis assimilate. We robust approaches to growth and yield prediction. Acconcluded that this level of variation in HI dynamics limited the cordingly, this study was undertaken to examine the general applicability of the HI approach in yield prediction and suggested a potential alternative for testing. stability of the HI approach for yield prediction in sorghum. Field experiments were conducted using a range of genotypes and growing conditions, and crop growth, yield, and HI dynamics were monitored and analyzed. C simulation models are often deficient in their predictions of grain growth. Hammer and Muchow (1994) developed a crop model for sorghum that acMATERIALS AND METHODS counted for 94% of the variation in total biomass, but Field Experiments only 64% of the variation in grain yield, when tested using data sets spanning a broad range of environments. Four experiments were conducted at Lawes (27 34 S, 152 20 E; altitude 90 m above sea level) in southeastern Their testing procedure showed a weakness in using an Queensland, Australia, on a Lawes brown black clay loam, approach based on HI dynamics to predict grain growth which is a moderately fertile deep alluvial, weakly cracking and yield. The HI approach used a linear increase in vertisol (Typic Chromustert) that was well drained. The experHI with time from shortly after anthesis until two-thirds iments were sown on 27 Sept. 1993, 28 Jan. and 10 Nov. 1994, of the time between anthesis and physiological maturity and 12 Jan. 1995. Meteorological conditions were recorded at had elapsed or the maximum HI of 0.55 had been the experimental site using a data logger with appropriately reached (Hammer and Muchow, 1994). This approach calibrated sensors. was based on the concept developed in soybean [Glycine In the first two experiments, three sorghum hybrids difmax (L.) Merr.] by Spaeth and Sinclair (1985) from fering in maturity formed the main treatments. Hybrids Piotheir observation of stability in HI dynamics for a small neer S34, RS610, and RS671 were chosen for their contrasting phenology: Pioneer S34 has quick maturity, RS671 medium number of experiments. The approach had proved uselate maturity, and RS610 intermediate maturity. In the third ful in other crops, such as peanut (Arachis hypogaea and fourth experiments, the two sorghum hybrids differing L.) (Hammer et al., 1995), maize (Zea mays L.) (Mumost in maturity (Pioneer S34 and RS671) were grown at two levels of plant population—16 and 8 plants m . The density G.L. Hammer and I.J. Broad, Agric. Prod. Syst. Res. Unit, Queensland used in the first two experiments corresponded with the highDep. of Primary Industries, Toowoomba, QLD 4350, Australia. G.L. density treatment in the latter two experiments. Plots meaHammer, School of Land and Food Sci., The Univ. of Queensland, Brisbane, QLD 4072, Australia. Received 2 Mar. 2002. *Corresponding author ([email protected]). Abbreviations: A-M, anthesis to physiological maturity; E-A, emergence to anthesis; HI, harvest index; LAI, leaf area index. Published in Agron. J. 95:199–206 (2003).