Methods of high-throughput plant phenotyping for large-scale breeding and genetic experiments

被引:1
作者
Afonnikov, D. A. [1 ,2 ]
Genaev, M. A. [1 ]
Doroshkov, A. V. [1 ]
Komyshev, E. G. [1 ]
Pshenichnikova, T. A. [1 ]
机构
[1] Russian Acad Sci, Inst Cytol & Genet, Siberian Branch, Novosibirsk 630090, Russia
[2] Novosibirsk State Univ, Novosibirsk 630090, Russia
基金
俄罗斯科学基金会;
关键词
plant phenomics; breeding and genetic experiment; high-throughput phenotyping; image analysis; databases; GENOME-WIDE ASSOCIATION; IMAGE-ANALYSIS PIPELINE; ARABIDOPSIS-THALIANA; LEAF PUBESCENCE; CHLOROPHYLL FLUORESCENCE; INFORMATION-SYSTEM; ANALYSIS PLATFORM; QTL ANALYSIS; GROWTH; ROOT;
D O I
10.1134/S1022795416070024
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Phenomics is a field of science at the junction of biology and informatics which solves the problems of rapid, accurate estimation of the plant phenotype; it was rapidly developed because of the need to analyze phenotypic characteristics in large scale genetic and breeding experiments in plants. It is based on using the methods of computer image analysis and integration of biological data. Owing to automation, new approaches make it possible to considerably accelerate the process of estimating the characteristics of a phenotype, to increase its accuracy, and to remove a subjectivism (inherent to humans). The main technologies of high-throughput plant phenotyping in both controlled and field conditions, their advantages and disadvantages, and also the prospects of their use for the efficient solution of problems of plant genetics and breeding are presented in the review.
引用
收藏
页码:688 / 701
页数:14
相关论文
共 132 条
[1]  
Abrmoff MD., 2004, Image Processing with ImageJ, V11, P36, DOI DOI 10.1201/9781420005615.AX4
[2]   Large-Scale Reverse Genetics in Arabidopsis: Case Studies from the Chloroplast 2010 Project [J].
Ajjawi, Imad ;
Lu, Yan ;
Savage, Linda J. ;
Bell, Shannon M. ;
Last, Robert L. .
PLANT PHYSIOLOGY, 2010, 152 (02) :529-540
[3]   P-TRAP: a Panicle Trait Phenotyping tool [J].
AL-Tam, Faroq ;
Adam, Helene ;
dos Anjos, Antonio ;
Lorieux, Mathias ;
Larmande, Pierre ;
Ghesquiere, Alain ;
Jouannic, Stefan ;
Shahbazkia, Hamid Reza .
BMC PLANT BIOLOGY, 2013, 13
[4]   A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects [J].
Arvidsson, Samuel ;
Perez-Rodriguez, Paulino ;
Mueller-Roeber, Bernd .
NEW PHYTOLOGIST, 2011, 191 (03) :895-907
[5]   leafprocessor: a new leaf phenotyping tool using contour bending energy and shape cluster analysis [J].
Backhaus, Andreas ;
Kuwabara, Asuka ;
Bauch, Marion ;
Monk, Nick ;
Sanguinetti, Guido ;
Fleming, Andrew .
NEW PHYTOLOGIST, 2010, 187 (01) :251-261
[6]   Rapid, noninvasive screening for perturbations of metabolism and plant growth using chlorophyll fluorescence imaging [J].
Barbagallo, RP ;
Oxborough, K ;
Pallett, KE ;
Baker, NR .
PLANT PHYSIOLOGY, 2003, 132 (02) :485-493
[7]   Early detection of Fusarium infection in wheat using hyper-spectral imaging [J].
Bauriegel, E. ;
Giebel, A. ;
Geyer, M. ;
Schmidt, U. ;
Herppich, W. B. .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2011, 75 (02) :304-312
[8]  
Beavis William D., 1998, P145
[9]   IMAGE ANALYSIS OF ARABIDOPSIS TRICHOME PATTERNING IN 4D CONFOCAL DATASETS [J].
Bensch, R. ;
Ronneberger, O. ;
Greese, B. ;
Fleck, C. ;
Wester, K. ;
Huelskamp, M. ;
Burkhardt, H. .
2009 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1 AND 2, 2009, :742-+
[10]   Data management pipeline for plant phenotyping in a multisite project [J].
Billiau, Kenny ;
Sprenger, Heike ;
Schudoma, Christian ;
Walther, Dirk ;
Koehl, Karin I. .
FUNCTIONAL PLANT BIOLOGY, 2012, 39 (10-11) :948-957