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Towards the Reliable Prediction of Time to Flowering in Six Annual Crops. VI. Applications in Crop Improvement

Published online by Cambridge University Press:  03 October 2008

R. J. Lawn ,
R. J. Summerfield ,
R. H. Ellis ,
A. Qi ,
E. H. Roberts ,
P. M. Chay ,
J. B. Brouwer ,
J. L. Rose  and
S. J. Yeates
R. J. Lawn
Affiliation:
CSIRO Division of Tropical Crops and Pastures, The Cunningham Laboratory, 306 Carmody Road, St Lucia, Queensland 4067, Australia
R. J. Summerfield
Affiliation:
University of Reading, Department of Agriculture, Plant Environment Laboratory, Cutbush Lane, Reading RG2 9AD, England
R. H. Ellis
Affiliation:
University of Reading, Department of Agriculture, Plant Environment Laboratory, Cutbush Lane, Reading RG2 9AD, England
A. Qi
Affiliation:
University of Reading, Department of Agriculture, Plant Environment Laboratory, Cutbush Lane, Reading RG2 9AD, England
E. H. Roberts
Affiliation:
University of Reading, Department of Agriculture, Plant Environment Laboratory, Cutbush Lane, Reading RG2 9AD, England
P. M. Chay
Affiliation:
CSIRO Davies Laboratory, Private Mail Bag, PO Aitkenvale, Queensland 4814, Australia
J. B. Brouwer
Affiliation:
Victorian Institute for Dryland Agriculture, Private Bag 260, Natimuk Road, Horsham, Victoria 3401, Australia
J. L. Rose
Affiliation:
Queensland Department of Primary Industries, Hermitage Research Station, via Warwick, Queensland 4370, Australia
S. J. Yeates
Affiliation:
Department of Primary Industries and Fisheries, PO Box 1346, Katherine, Northern Territory 5780, Australia
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Summary

Variation in time from sowing to flowering (f) was examined for 44 cultivars of soyabean, mungbean, black gram, ricebean, cowpea, chickpea, lentil and barley, when grown in up to 21 diverse environments obtained by making one or more sowings at each of six locations spanning tropical, sub-tropical and temperate climates in Australia. The utility of simple linear models, relating rate of development (l/f) towards flowering to mean photoperiod and temperature prevailing between sowing and flowering, was evaluated. The models were highly efficient, explaining most (86.7%) of the variation observed across species, cultivars and environments. They were particularly efficient in describing responses where cultivars were relatively well-adapted, in agronomic terms, and least efficient where cultivars were exposed to unfavourable temperature and, to a lesser extent, photoperiod. Opportunities for exploiting the models in applied crop improvement include their use in interpretation of G × E interaction, genotypic characterization and selection of parental genotypes, selection of test environments, designing screening procedures, and more efficiently matching genotypes to target environments. The main strengths of these linear, additive rate models in crop improvement are their wide applicability across species and genotypes, their relative simplicity, and the requirement for few genotype-specific response parameters. Their main weakness is their lack of precision in describing responses when plants are exposed to unfavourable photothermal extremes, albeit in circumstances that are sometimes unrealistic for cropping those particular genotypes.

Predicciones del tiempo que ha de transcurrir hanta la floración. VI.

Type
Research Article
Information
Experimental Agriculture , Volume 31 , Issue 1 , January 1995 , pp. 89 - 108
Copyright
Copyright © Cambridge University Press 1995

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