Literature DB >> 27161822

Physiological breeding.

Matthew Reynolds1, Peter Langridge2.   

Abstract

Physiological breeding crosses parents with different complex but complementary traits to achieve cumulative gene action for yield, while selecting progeny using remote sensing, possibly in combination with genomic selection. Physiological approaches have already demonstrated significant genetic gains in Australia and several developing countries of the International Wheat Improvement Network. The techniques involved (see Graphical Abstract) also provide platforms for research and refinement of breeding methodologies. Recent examples of these include screening genetic resources for novel expression of Calvin cycle enzymes, identification of common genetic bases for heat and drought adaptation, and genetic dissection of trade-offs among yield components. Such information, combined with results from physiological crosses designed to test novel trait combinations, lead to more precise breeding strategies, and feed models of genotype-by-environment interaction to help build new plant types and experimental environments for future climates.
Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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Year:  2016        PMID: 27161822     DOI: 10.1016/j.pbi.2016.04.005

Source DB:  PubMed          Journal:  Curr Opin Plant Biol        ISSN: 1369-5266            Impact factor:   7.834


  53 in total

1.  Reconstruction of Networks with Direct and Indirect Genetic Effects.

Authors:  Willem Kruijer; Pariya Behrouzi; Daniela Bustos-Korts; María Xosé Rodríguez-Álvarez; Seyed Mahdi Mahmoudi; Brian Yandell; Ernst Wit; Fred A van Eeuwijk
Journal:  Genetics       Date:  2020-02-03       Impact factor: 4.562

2.  Compositional equivalence of event IND-ØØ412-7 to non-transgenic wheat.

Authors:  Francisco Ayala; Griselda V Fedrigo; Moises Burachik; Patricia V Miranda
Journal:  Transgenic Res       Date:  2019-01-17       Impact factor: 2.788

3.  Genomic Prediction with Pedigree and Genotype × Environment Interaction in Spring Wheat Grown in South and West Asia, North Africa, and Mexico.

Authors:  Sivakumar Sukumaran; Jose Crossa; Diego Jarquin; Marta Lopes; Matthew P Reynolds
Journal:  G3 (Bethesda)       Date:  2017-02-09       Impact factor: 3.154

Review 4.  Identification and Characterization of Contrasting Genotypes/Cultivars for Developing Heat Tolerance in Agricultural Crops: Current Status and Prospects.

Authors:  Shikha Chaudhary; Poonam Devi; Anjali Bhardwaj; Uday Chand Jha; Kamal Dev Sharma; P V Vara Prasad; Kadambot H M Siddique; H Bindumadhava; Shiv Kumar; Harsh Nayyar
Journal:  Front Plant Sci       Date:  2020-10-22       Impact factor: 5.753

Review 5.  Breeding for drought and heat tolerance in wheat.

Authors:  Peter Langridge; Matthew Reynolds
Journal:  Theor Appl Genet       Date:  2021-03-14       Impact factor: 5.699

Review 6.  Scaling up high-throughput phenotyping for abiotic stress selection in the field.

Authors:  Daniel T Smith; Andries B Potgieter; Scott C Chapman
Journal:  Theor Appl Genet       Date:  2021-06-02       Impact factor: 5.699

7.  Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number.

Authors:  Sivakumar Sukumaran; Marta Lopes; Susanne Dreisigacker; Matthew Reynolds
Journal:  Theor Appl Genet       Date:  2017-12-07       Impact factor: 5.699

8.  High-resolution spectral information enables phenotyping of leaf epicuticular wax in wheat.

Authors:  Fátima Camarillo-Castillo; Trevis D Huggins; Suchismita Mondal; Matthew P Reynolds; Michael Tilley; Dirk B Hays
Journal:  Plant Methods       Date:  2021-06-07       Impact factor: 4.993

9.  Harnessing translational research in wheat for climate resilience.

Authors:  Matthew P Reynolds; Janet M Lewis; Karim Ammar; Bhoja R Basnet; Leonardo Crespo-Herrera; José Crossa; Kanwarpal S Dhugga; Susanne Dreisigacker; Philomin Juliana; Hannes Karwat; Masahiro Kishii; Margaret R Krause; Peter Langridge; Azam Lashkari; Suchismita Mondal; Thomas Payne; Diego Pequeno; Francisco Pinto; Carolina Sansaloni; Urs Schulthess; Ravi P Singh; Kai Sonder; Sivakumar Sukumaran; Wei Xiong; Hans J Braun
Journal:  J Exp Bot       Date:  2021-07-10       Impact factor: 6.992

10.  Peanut Leaf Wilting Estimation From RGB Color Indices and Logistic Models.

Authors:  Sayantan Sarkar; A Ford Ramsey; Alexandre-Brice Cazenave; Maria Balota
Journal:  Front Plant Sci       Date:  2021-06-18       Impact factor: 5.753

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