Modelling environmental effects on phenology and canopy development of diverse sorghum genotypesExport / Share PlumX View Altmetrics View AltmetricsKumar, S.R., Hammer, G.L., Broad, I. J., Harland, P. and McLean, G. (2009) Modelling environmental effects on phenology and canopy development of diverse sorghum genotypes. Field Crops Research, 111 (1-2). pp. 157-165. Full text not currently attached. Access may be available via the Publisher's website or OpenAccess link. Article Link: http://dx.doi.org/10.1016/j.fcr.2008.11.010 Publisher URL: http://www.elsevier.com AbstractThe ability to predict phenology and canopy development is critical in crop models used for simulating likely consequences of alternative crop management and cultivar choice strategies. Here we quantify and contrast the temperature and photoperiod responses for phenology and canopy development of a diverse range of elite Indian and Australian sorghum genotypes (hybrid and landrace). Detailed field experiments were undertaken in Australia and India using a range of genotypes, sowing dates, and photoperiod extension treatments. Measurements of timing of developmental stages and leaf appearance were taken. The generality of photo-thermal approaches to modelling phenological and canopy development was tested. Environmental and genotypic effects on rate of progression from emergence to floral initiation (E-FI) were explained well using a multiplicative model, which combined the intrinsic development rate (Ropt), with responses to temperature and photoperiod. Differences in Ropt and extent of the photoperiod response explained most genotypic effects. Average leaf initiation rate (LIR), leaf appearance rate and duration of the phase from anthesis to physiological maturity differed among genotypes. The association of total leaf number (TLN) with photoperiod found for all genotypes could not be fully explained by effects on development and LIRs. While a putative effect of photoperiod on LIR would explain the observations, other possible confounding factors, such as air-soil temperature differential and the nature of model structure were considered and discussed. This study found a generally robust predictive capacity of photo-thermal development models across diverse ranges of both genotypes and environments. Hence, they remain the most appropriate models for simulation analysis of genotype-by-management scenarios in environments varying broadly in temperature and photoperiod.
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