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

Abstract

chow and Sinclair, 1991), and sunflower (Helianthus annuus L.) (Chapman et al., 1993). An approach based on a linear rate of increase in harvest indexDeficiencies 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) showedconditions. 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 anthe-Frequent 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. How-Harvest 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 wasAs crop models need to be applied across a diverse 0.0198 d Ϫ1 , 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.Hammer,

Separating competition-related factors limiting crop performance in an agroforestry parkland system in Burkina Faso

“…The good rainfall in 2008 also explains higher values of HI compared to what was obtained in 2007 as grain yield is expected to be proportional to total aboveground biomass. The averages HI recorded for sorghum in this study are within the range (0.12-0.57) reported by previous workers (Prihar and Stewart 1991;Hammer and Broad 2003;Tariq et al 2007). This indicates that the competition for growth resources is more severe during years with poor rainfall.…”

“…Good rainfall in 2008 (more frequent and more important) may have favor N and P solubilization thus improving their bioavailability for plant uptake, resulting in a higher grain yield this year compared to 2007. Indeed, differences in total rainfall as well as to its distribution can both significantly affect assimilation during grain filling and remobilization of preanthesis assimilate as reported by Hammer and Broad (2003). The good rainfall in 2008 also explains higher values of HI compared to what was obtained in 2007 as grain yield is expected to be proportional to total aboveground biomass.…”

Yield component analysis of grain sorghum grown under water stress

“…Eck and Musick (1979) reported well-watered grain yields of 749 g m −2 while well-watered yields given in Hammer and Broad (2003) varied from 495 to 875 g m −2 in four experiments. Tolk and Howell (2003) reported a well-watered grain yield of 687 g m −2 , an ET of 490 mm, and WUE of 1.42 kg m −3 .…”

Tamanho de parcela para produtividade de grãos de sorgo granífero em diferentes densidades de plantas

“…As determinações da densidade de semeadura e espaçamentos entre linhas ideais para diversas situações de manejo da cultura, entre outros fatores, são primordiais para otimizar a produtividade (Berenguer & Faci, 2001;Hammer & Broad, 2003).…”