2021
DOI: 10.5513/jcea01/22.2.3114
|View full text |Cite
|
Sign up to set email alerts
|

The use of DNA markers for genetic differentiation of common (Avena sativa L.) and naked oat (Avena nuda L.)

Abstract: The usefulness of genetic identification of varieties for seed quality analyses becomes important, when we suspect the presence of another variety, species or even genus, based on morphological seed traits in the purity analysis and germination test, With genetic analyses, the doubt about the authenticity of the naked oats (Avena nuda L.) variety 'Kamil' was successfully solved. There were atypical seeds with chaff among the samples of this variety, so it was not possible to confirm with certainty, whether the… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3

Citation Types

0
3
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(3 citation statements)
references
References 5 publications
0
3
0
Order By: Relevance
“…Due to the continuous development and application of molecular marker technology in cultivar identification, molecular detection has been considered as an effective identification method with high precision ( Saccomanno et al., 2020 ). RFLP (restriction fragment length polymorphism), RAPD (randomly amplified polymorphic DNA), SSR (simple sequence repeat) and other molecular markers have been successfully applied in oat cultivars identification ( O’Donoughue et al., 1994 ; Paczos-Grzeda, 2004 ; Wight et al., 2010 ; Pipan et al., 2021 ). However, the lack of validated markers is one of the constraints of using molecular method ( Sakiyama et al., 2014 ), and it is generally conducted destructive.…”
Section: Introductionmentioning
confidence: 99%
“…Due to the continuous development and application of molecular marker technology in cultivar identification, molecular detection has been considered as an effective identification method with high precision ( Saccomanno et al., 2020 ). RFLP (restriction fragment length polymorphism), RAPD (randomly amplified polymorphic DNA), SSR (simple sequence repeat) and other molecular markers have been successfully applied in oat cultivars identification ( O’Donoughue et al., 1994 ; Paczos-Grzeda, 2004 ; Wight et al., 2010 ; Pipan et al., 2021 ). However, the lack of validated markers is one of the constraints of using molecular method ( Sakiyama et al., 2014 ), and it is generally conducted destructive.…”
Section: Introductionmentioning
confidence: 99%
“…In the Official Herbage and Turfgrass Seeds Testing Center, Ministry of Agriculture and Rural Affairs, China, there are nearly 2000 categories of seed identification tasks every year. Traditional methods of seed classification and identification include visual methods, chemical methods, biological methods, etc 3 , 4 . Because different seeds have different characteristics, such as shape and texture, which are important features to distinguish seed categories, physical observation method is the most direct and simplest method, but the realization of seed classification by observation method not only requires certain expertise but also has low efficiency and poor stability.…”
Section: Introductionmentioning
confidence: 99%
“…Traditional methods of seed classification and identification include visual methods, chemical methods, biological methods, etc. 3,4 Because different seeds have different characteristics, such as shape and texture, which are important features to distinguish seed categories, physical observation method is the most direct and simplest method, but the realization of seed classification by observation method not only requires certain expertise but also has low efficiency and poor stability. In addition, the chemical method is based on the different chemical and biological characteristics of different seeds, through these different characteristics can effectively identify their species and vitality.…”
Section: Introductionmentioning
confidence: 99%