Literature DB >> 22925524

Dissecting maize productivity: ideotypes associated with grain yield under drought stress and well-watered conditions.

Jill E Cairns1, Ciro Sanchez, Mateo Vargas, Raziel Ordoñez, Jose Luis Araus.   

Abstract

To increase maize (Zea mays L.) yields in drought-prone environments and offset predicted maize yield losses under future climates, the development of improved breeding pipelines using a multi-disciplinary approach is essential. Elucidating key growth processes will provide opportunities to improve drought breeding progress through the identification of key phenotypic traits, ideotypes, and donors. In this study, we tested a large set of tropical and subtropical maize inbreds and single cross hybrids under reproductive stage drought stress and well-watered conditions. Patterns of biomass production, senescence, and plant water status were measured throughout the crop cycle. Under drought stress, early biomass production prior to anthesis was important for inbred yield, while delayed senescence was important for hybrid yield. Under well-watered conditions, the ability to maintain a high biomass throughout the growing cycle was crucial for inbred yield, while a stay-green pattern was important for hybrid yield. While new quantitative phenotyping tools such as spectral reflectance (Normalized Difference Vegetation Index, NDVI) allowed for the characterization of growth and senescence patterns as well as yield, qualitative measurements of canopy senescence were also found to be associated with grain yield.
© 2012 Institute of Botany, Chinese Academy of Sciences.

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Year:  2012        PMID: 22925524     DOI: 10.1111/j.1744-7909.2012.01156.x

Source DB:  PubMed          Journal:  J Integr Plant Biol        ISSN: 1672-9072            Impact factor:   7.061


  22 in total

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3.  Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress.

Authors:  Nathan T Hein; Ignacio A Ciampitti; S V Krishna Jagadish
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4.  Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize.

Authors:  M Zaman-Allah; O Vergara; J L Araus; A Tarekegne; C Magorokosho; P J Zarco-Tejada; A Hornero; A Hernández Albà; B Das; P Craufurd; M Olsen; B M Prasanna; J Cairns
Journal:  Plant Methods       Date:  2015-06-24       Impact factor: 4.993

5.  Multispectral airborne imagery in the field reveals genetic determinisms of morphological and transpiration traits of an apple tree hybrid population in response to water deficit.

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Journal:  J Exp Bot       Date:  2015-07-23       Impact factor: 6.992

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Authors:  Izabela Marcińska; Ilona Czyczyło-Mysza; Edyta Skrzypek; Maciej T Grzesiak; Franciszek Janowiak; Maria Filek; Michał Dziurka; Kinga Dziurka; Piotr Waligórski; Katarzyna Juzoń; Katarzyna Cyganek; Stanisław Grzesiak
Journal:  Int J Mol Sci       Date:  2013-06-26       Impact factor: 5.923

7.  Remote, aerial phenotyping of maize traits with a mobile multi-sensor approach.

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Journal:  Plant Methods       Date:  2015-02-25       Impact factor: 4.993

8.  Detection and validation of stay-green QTL in post-rainy sorghum involving widely adapted cultivar, M35-1 and a popular stay-green genotype B35.

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Journal:  BMC Genomics       Date:  2014-10-18       Impact factor: 3.969

9.  Influence of the variation of geometrical and topological traits on light interception efficiency of apple trees: sensitivity analysis and metamodelling for ideotype definition.

Authors:  David Da Silva; Liqi Han; Robert Faivre; Evelyne Costes
Journal:  Ann Bot       Date:  2014-09       Impact factor: 4.357

10.  Plant phenotyping: from bean weighing to image analysis.

Authors:  Achim Walter; Frank Liebisch; Andreas Hund
Journal:  Plant Methods       Date:  2015-03-04       Impact factor: 4.993

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