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An ecophysiological model analysis of yield differences within a set of contrasting cultivars and an F1 segregating population of potato (Solanum tuberosum L.) grown under diverse environments

Author

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  • Khan, Muhammad S.
  • Yin, Xinyou
  • van der Putten, Peter E.L.
  • Struik, Paul C.

Abstract

The generic ecophysiological model ‘GECROS’ simulates crop growth and development as affected by genetic characteristics and climatic and edaphic environmental variables. We used this model to analyse differences in tuber yield of potato in five cultivars covering a wide range of maturity types and 100 individuals of a diploid F1 population segregating for maturity type. Six field experiments were conducted, in which contrasting nitrogen availabilities were created to represent six environments. Values of five genotype-specific model-input parameters were estimated and calibrated. Variation among the 100 F1 genotypes was as wide as, or slightly wider than, that among the five contrasting cultivars for any of the five parameters values but not for tuber yield. For the 100 F1 genotypes, the model accounted for 86% of genotypic differences in across-environment average tuber yield and 89% of environmental difference in across-genotype average yield. But the percentage in the genotypic differences in yield for a given experiment accounted for by the model ranged from 2% to 65%. Model analysis identified Nmax (i.e. total crop N uptake) and tuber N concentration as key components affecting tuber yield for all six experiments. Genotypes with higher Nmax and lower tuber N concentration exhibited higher tuber dry matter yield. The development of potato ideotypes for any specific environments should prioritize optimising N-related traits.

Suggested Citation

  • Khan, Muhammad S. & Yin, Xinyou & van der Putten, Peter E.L. & Struik, Paul C., 2014. "An ecophysiological model analysis of yield differences within a set of contrasting cultivars and an F1 segregating population of potato (Solanum tuberosum L.) grown under diverse environments," Ecological Modelling, Elsevier, vol. 290(C), pages 146-154.
    • Handle: RePEc:eee:ecomod:v:290:y:2014:i:c:p:146-154
    DOI: 10.1016/j.ecolmodel.2013.11.015
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    References listed on IDEAS

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    1. Boote, K. J. & Kropff, M. J. & Bindraban, P. S., 2001. "Physiology and modelling of traits in crop plants: implications for genetic improvement," Agricultural Systems, Elsevier, vol. 70(2-3), pages 395-420.
    2. Anothai, J. & Patanothai, A. & Pannangpetch, K. & Jogloy, S. & Boote, K.J. & Hoogenboom, G., 2008. "Reduction in data collection for determination of cultivar coefficients for breeding applications," Agricultural Systems, Elsevier, vol. 96(1-3), pages 195-206, March.
    3. Dingkuhn, Michael, 1996. "Modelling concepts for the phenotypic plasticity of dry matter and nitrogen partitioning in rice," Agricultural Systems, Elsevier, vol. 52(2-3), pages 383-397.
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