High-throughput Phenotyping and Genomic Selection: The Frontiers of Crop Breeding Converge

被引:201
作者
Cabrera-Bosquet, Llorenc [2 ]
Crossa, Jose [3 ]
von Zitzewitz, Jarislav [4 ]
Dolors Serret, Maria [1 ]
Luis Araus, Jose [1 ]
机构
[1] Univ Barcelona, Fac Biol, Unit Plant Physiol, E-08028 Barcelona, Spain
[2] INRA, French Natl Inst Agr Res, UMR759, Ecophysiol Lab Plants Environm Stress, F-34060 Montpellier, France
[3] Int Maize & Wheat Improvement Ctr CIMMYT, El Batan 56130, Texcoco, Mexico
[4] Natl Inst Agr Res, Natl Res Program Rainfed Crops, Est Exp La Estanzuela 70000, Colonia, Uruguay
关键词
Genomic selection; high-throughput phenotyping; NIRS; quantitative traits; SNPs; INFRARED REFLECTANCE SPECTROSCOPY; DURUM-WHEAT YIELD; GRAIN-YIELD; QUANTITATIVE TRAITS; DROUGHT TOLERANCE; PLANT; MAIZE; PREDICTION; BIOMASS; TOOL;
D O I
10.1111/j.1744-7909.2012.01116.x
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. [ Jose Luis Araus (Corresponding author)]
引用
收藏
页码:312 / 320
页数:9
相关论文
共 53 条
  • [1] Multiple trait genomic evaluation of conception rate in Holsteins
    Aguilar, I.
    Misztal, I.
    Tsuruta, S.
    Wiggans, G. R.
    Lawlor, T. J.
    [J]. JOURNAL OF DAIRY SCIENCE, 2011, 94 (05) : 2621 - 2624
  • [2] Spectral vegetation indices as nondestructive tools for determining durum wheat yield
    Aparicio, N
    Villegas, D
    Casadesus, J
    Araus, JL
    Royo, C
    [J]. AGRONOMY JOURNAL, 2000, 92 (01) : 83 - 91
  • [3] Araus J.L., 2001, APPL PHYSL WHEAT BRE, P59
  • [4] Breeding cereals for Mediterranean conditions: ecophysiological clues for biotechnology application
    Araus, JL
    Bort, J
    Steduto, P
    Villegas, D
    Royo, C
    [J]. ANNALS OF APPLIED BIOLOGY, 2003, 142 (02) : 129 - 141
  • [5] Plant breeding and drought in C3 cereals:: What should we breed for?
    Araus, JL
    Slafer, GA
    Reynolds, MP
    Royo, C
    [J]. ANNALS OF BOTANY, 2002, 89 : 925 - 940
  • [6] Breeding for Yield Potential and Stress Adaptation in Cereals
    Araus, Jose Luis
    Slafer, Gustavo A.
    Royo, Conxita
    Dolores Serret, M.
    [J]. CRITICAL REVIEWS IN PLANT SCIENCES, 2008, 27 (06) : 377 - 412
  • [7] The potential of using spectral reflectance indices to estimate yield in wheat grown under reduced irrigation
    Babar, M. A.
    van Ginkel, M.
    Klatt, A. R.
    Prasad, B.
    Reynolds, M. P.
    [J]. EUPHYTICA, 2006, 150 (1-2) : 155 - 172
  • [8] Prospects for genomewide selection for quantitative traits in maize
    Bernardo, Rex
    Yu, Jianming
    [J]. CROP SCIENCE, 2007, 47 (03) : 1082 - 1090
  • [9] Burgueno J, 2012, CROP SCI, DOI [10.2135/cropsci2011.06.0299.x, DOI 10.2135/CROPSCI2011.06.0299.X]
  • [10] NDVI as a Potential Tool for Predicting Biomass, Plant Nitrogen Content and Growth in Wheat Genotypes Subjected to Different Water and Nitrogen Conditions
    Cabrera-Bosquet, L.
    Molero, G.
    Stellacci, A. M.
    Bort, J.
    Nogues, S.
    Araus, J. L.
    [J]. CEREAL RESEARCH COMMUNICATIONS, 2011, 39 (01) : 147 - 159