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1.  Regulation of tillering in sorghum: environmental effects 
Annals of Botany  2010;106(1):57-67.
Background and Aims
Tillering has a significant effect on canopy development and, hence, on resource capture, crop growth and grain yield in sorghum. However, the physiological basis of tillering and its regulation by environmental effects are not fully understood. The objective of this study was to understand and quantify the environmental effects on tillering in sorghum using a carbohydrate supply–demand framework.
Methods
A series of five experiments with a wide range of radiation and temperature conditions was conducted and details of the tillering responses of a single representative hybrid were monitored. The concept of internal plant competition for carbohydrate was developed for analysis of these responses.
Key Results
Tiller appearance was highly synchronized with main shoot leaf appearance, with a consistent hierarchy for tillering across environments. The main environmental effect was on the frequency of tiller appearance, in particular of the lower-rank tillers. This explained some of the observed environmental differences in the onset of tillering. A generalized index of internal plant competition, which took account of plant assimilate supply and demand (S/Dindex) during the critical period for tillering, explained most of the variation in maximum tiller number observed across the five experiments.
Conclusions
This result was consistent with the hypothesis that internal plant competition for assimilates regulates tillering in sorghum. Hence, the framework outlined has a predictive value that could provide the basis for dynamic simulation of tillering in crop growth models.
doi:10.1093/aob/mcq079
PMCID: PMC2889793  PMID: 20421230
Carbohydrate supply–demand ratio; internal plant competition; leaf area development; modelling; radiation; Sorghum bicolor; temperature; tiller hierarchy
2.  Regulation of tillering in sorghum: genotypic effects 
Annals of Botany  2010;106(1):69-78.
Background and Aims
Genotypic variation in tillering can be caused by differences in the carbon supply–demand balance within a plant. The aim of this study was to understand and quantify the effects of genotype on tillering as a consequence of the underlying internal competition for carbohydrates.
Methods
Five sorghum hybrids, derived from inbred lines with a common genetic background and with similar phenology and plant height but contrasting tillering, were grown in five experiments. The experiments covered a wide range in radiation and temperature conditions, so that number of tillers produced varied significantly. Data on leaf area, tiller number, and biomass accumulation and partitioning were collected at regular intervals. To quantify internal plant competition for carbohydrates, a carbohydrate supply–demand index (S/Dindex) was developed and related to variation in tillering.
Key Results
The appearance of main shoot leaves and tillers was highly co-ordinated across genotypes. High-tillering hybrids had a greater appearance frequency of early tiller ranks than low-tillering hybrids, and this was associated with narrower and hence smaller main shoot leaves. A generalized S/Dindex of internal plant competition accounted for most of the observed variation in maximum tiller number (Ntiller,max) across genotypes. However, genotypic differences in the relationship between the S/Dindex and Ntiller,max suggested that high-tillering hybrids also had a lower S/D threshold at which tillers appeared, possibly associated with hormonal effects.
Conclusions
The results support the hypothesis that genotypic differences in tillering were associated with differences in plant carbon S/D balance, associated with differences in leaf size and in the threshold at which tillers grow out. The results provide avenues for phenotyping of mapping populations to identify genomic regions regulating tillering. Incorporating the results in crop growth simulation models could provide insight into the complex genotype-by-management-by-environment interactions associated with drought adaptation.
doi:10.1093/aob/mcq080
PMCID: PMC2889794  PMID: 20430784
Carbohydrate supply–demand ratio; genotype-by-environment interaction; internal plant competition; leaf area development; leaf width; Sorghum bicolor; tiller number; tiller onset
3.  Using Virtual Plants to Analyse the Light-foraging Efficiency of a Low-density Cotton Crop 
Annals of Botany  2008;101(8):1153-1166.
Background and Aims
Cotton shows a marked plasticity vs. density in terms of branch development and geometry, internode elongation and leaf expansion. This paper proposes interpretations for observed plasticity in terms of light quantity and quality.
Methods
3-D virtual plants were reconstructed from field observations and 3-D digitization and were used to simulate the light regime in cotton stands of different densities.
Key Results
All densities showed the same linear relationship between LAI and the sum of light intercepted by the canopy, from seedling emergence up to flowering. Simulated R : FR ratio profiles can very likely explain (1) the longer first internodes on main stem and branches and (2) the azimuthal re-orientation of branches toward the inter-row.
Conclusions
Simulation tools were used to analyse plant plasticity in terms of light quantity and quality. The methodology applied here at the stand scale will now be continued at the plant scale to further strengthen the above hypotheses.
doi:10.1093/aob/mcm316
PMCID: PMC2710272  PMID: 18184646
Light capture; photomorphogensis; R : FR ratio; cotton; Gossypium hirsutum; plant architecture; virtual plants; phenotypic plasticity; density
4.  Parameter Stability of the Functional–Structural Plant Model GREENLAB as Affected by Variation within Populations, among Seasons and among Growth Stages 
Annals of Botany  2006;99(1):61-73.
Background and Aims
It is increasingly accepted that crop models, if they are to simulate genotype-specific behaviour accurately, should simulate the morphogenetic process generating plant architecture. A functional–structural plant model, GREENLAB, was previously presented and validated for maize. The model is based on a recursive mathematical process, with parameters whose values cannot be measured directly and need to be optimized statistically. This study aims at evaluating the stability of GREENLAB parameters in response to three types of phenotype variability: (1) among individuals from a common population; (2) among populations subjected to different environments (seasons); and (3) among different development stages of the same plants.
Methods
Five field experiments were conducted in the course of 4 years on irrigated fields near Beijing, China. Detailed observations were conducted throughout the seasons on the dimensions and fresh biomass of all above-ground plant organs for each metamer. Growth stage-specific target files were assembled from the data for GREENLAB parameter optimization. Optimization was conducted for specific developmental stages or the entire growth cycle, for individual plants (replicates), and for different seasons. Parameter stability was evaluated by comparing their CV with that of phenotype observation for the different sources of variability. A reduced data set was developed for easier model parameterization using one season, and validated for the four other seasons.
Key Results and Conclusions
The analysis of parameter stability among plants sharing the same environment and among populations grown in different environments indicated that the model explains some of the inter-seasonal variability of phenotype (parameters varied less than the phenotype itself), but not inter-plant variability (parameter and phenotype variability were similar). Parameter variability among developmental stages was small, indicating that parameter values were largely development-stage independent. The authors suggest that the high level of parameter stability observed in GREENLAB can be used to conduct comparisons among genotypes and, ultimately, genetic analyses.
doi:10.1093/aob/mcl245
PMCID: PMC2802986  PMID: 17158141
Plant architecture; functional–structural models; crop simulation; parameter stability; allometric relationships; sink capacity; Zea mays

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