Literature DB >> 22698516

Plant variety and cultivar identification: advances and prospects.

Nicholas Kibet Korir1, Jian Han, Lingfei Shangguan, Chen Wang, Emrul Kayesh, Yanyi Zhang, Jinggui Fang.   

Abstract

Plant variety and cultivar identification is one of the most important aspects in agricultural systems. The large number of varieties or landraces among crop plants has made it difficult to identify and characterize varieties solely on the basis of morphological characters because they are non stable and originate due to environmental and climatic conditions, and therefore phenotypic plasticity is an outcome of adaptation. To mitigate this, scientists have developed and employed molecular markers, statistical tests and software to identify and characterize the required plant cultivars or varieties for cultivation, breeding programs as well as for cultivar-right-protection. The establishment of genome and transcriptome sequencing projects for many crops has led to generation of a huge wealth of sequence information that could find much use in identification of plants and their varieties. We review the current status of plant variety and cultivar identification, where an attempt has been made to describe the different strategies available for plant identification. We have found that despite the availability of methods and suitable markers for a wide range of crops, there is dearth of simple ways of making both morphological descriptors and molecular markers easy, referable and practical to use although there are ongoing attempts at making this possible. Certain limitations present a number of challenges for the development and utilization of modern scientific methods in variety or cultivar identification in many important crops.

Mesh:

Substances:

Year:  2012        PMID: 22698516     DOI: 10.3109/07388551.2012.675314

Source DB:  PubMed          Journal:  Crit Rev Biotechnol        ISSN: 0738-8551            Impact factor:   8.429


  18 in total

1.  A cost-effective barcode system for maize genetic discrimination based on bi-allelic InDel markers.

Authors:  Shuaiqiang Liang; Feng Lin; Yiliang Qian; Tifu Zhang; Yibo Wu; Yaocheng Qi; Sihai Ren; Long Ruan; Han Zhao
Journal:  Plant Methods       Date:  2020-07-29       Impact factor: 4.993

2.  Diversity analysis of cotton (Gossypium hirsutum L.) germplasm using the CottonSNP63K Array.

Authors:  Lori L Hinze; Amanda M Hulse-Kemp; Iain W Wilson; Qian-Hao Zhu; Danny J Llewellyn; Jen M Taylor; Andrew Spriggs; David D Fang; Mauricio Ulloa; John J Burke; Marc Giband; Jean-Marc Lacape; Allen Van Deynze; Joshua A Udall; Jodi A Scheffler; Steve Hague; Jonathan F Wendel; Alan E Pepper; James Frelichowski; Cindy T Lawley; Don C Jones; Richard G Percy; David M Stelly
Journal:  BMC Plant Biol       Date:  2017-02-03       Impact factor: 4.215

3.  Applications of DNA Technologies in Agriculture.

Authors:  Jinggui Fang; Xudong Zhu; Chen Wang; Lingfei Shangguan
Journal:  Curr Genomics       Date:  2016-08       Impact factor: 2.236

4.  Barcode System for Genetic Identification of Soybean [Glycine max (L.) Merrill] Cultivars Using InDel Markers Specific to Dense Variation Blocks.

Authors:  Hwang-Bae Sohn; Su-Jeong Kim; Tae-Young Hwang; Hyang-Mi Park; Yu-Young Lee; Kesavan Markkandan; Dongwoo Lee; Sunghoon Lee; Su-Young Hong; Yun-Ho Song; Bon-Cheol Koo; Yul-Ho Kim
Journal:  Front Plant Sci       Date:  2017-04-10       Impact factor: 5.753

5.  Development and characterization of polymorphic genic-SSR markers in Larix kaempferi.

Authors:  Xing-Bin Chen; Yun-Hui Xie; Xiao-Mei Sun
Journal:  Molecules       Date:  2015-04-08       Impact factor: 4.411

6.  Genotyping-by-sequencing identifies date palm clone preference in agronomics of the State of Qatar.

Authors:  Gaurav Thareja; Sweety Mathew; Lisa S Mathew; Yasmin Ali Mohamoud; Karsten Suhre; Joel A Malek
Journal:  PLoS One       Date:  2018-12-05       Impact factor: 3.240

7.  Development of model web-server for crop variety identification using throughput SNP genotyping data.

Authors:  Rajender Singh; M A Iquebal; C N Mishra; Sarika Jaiswal; Deepender Kumar; Nishu Raghav; Surinder Paul; Sonia Sheoran; Pradeep Sharma; Arun Gupta; Vinod Tiwari; U B Angadi; Neeraj Kumar; Anil Rai; G P Singh; Dinesh Kumar; Ratan Tiwari
Journal:  Sci Rep       Date:  2019-03-26       Impact factor: 4.379

8.  Identification of pummelo cultivars by using a panel of 25 selected SNPs and 12 DNA segments.

Authors:  Bo Wu; Guang-yan Zhong; Jian-qiang Yue; Run-ting Yang; Chong Li; Yue-jia Li; Yun Zhong; Xuan Wang; Bo Jiang; Ji-wu Zeng; Li Zhang; Shu-tang Yan; Xue-jun Bei; Dong-guo Zhou
Journal:  PLoS One       Date:  2014-04-14       Impact factor: 3.240

9.  SSR marker development and intraspecific genetic divergence exploration of Chrysanthemum indicum based on transcriptome analysis.

Authors:  Zhengzhou Han; Xinye Ma; Min Wei; Tong Zhao; Ruoting Zhan; Weiwen Chen
Journal:  BMC Genomics       Date:  2018-04-25       Impact factor: 3.969

10.  Near-Infrared Hyperspectral Imaging Combined with Deep Learning to Identify Cotton Seed Varieties.

Authors:  Susu Zhu; Lei Zhou; Pan Gao; Yidan Bao; Yong He; Lei Feng
Journal:  Molecules       Date:  2019-09-07       Impact factor: 4.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.