Application of remote sensing to identify adult plant resistance loci to stripe rust in two bread wheat mapping populations

Application of remote sensing to identify adult plant resistance loci to stripe rust in two bread... Phenotyping of wheat stripe rust in genetic studies has traditionally relied on quantifying disease by means of the modified Cobb Scale. This approach requires scoring of disease severity and response type, either on flag leaves or on a whole plot basis. The use of spectral crop sensors in wheat phenotyping has raised the question of whether this objective methodology is suitable for detecting stripe rust resistance loci in genetic studies. An Avocet S X Francolin#1 recombinant inbred population developed at the International Maize and Wheat Improvement Center (Centro Internacional de Mejoramiento de Maiz y Trigo—acronym CIMMYT), and a Kariega X Avocet S doubled haploid population developed in South Africa, both with available genetic maps, were used in this study. Field trials for stripe rust evaluation of these populations were planted at Greytown, South Africa in 2013 and 2014. Severe and uniformly distributed infection of Puccinia striiformis race 6E22A+ occurred in both years. Populations and parents were phenotyped according to the modified Cobb Scale and with a handheld Trimble GreenSeeker® crop sensor (model HCS-100). The sensing device emits red and infrared light and measures the reflectance of each wavelength in terms of the normalized difference vegetation index (NDVI). In both years, NDVI detected four previously characterized quantitative trait loci (QTL) on chromosomes 1BL, 2BS, 3BS and 6AL in the Avocet S X Francolin#1 population. The same QTL were detected with visual estimates in 2013 but only 2BS was significant in 2014. In the Kariega X Avocet S population, all stripe rust traits, including NDVI, mapped to previously described QTL on chromosomes 2BS, 4AL and 7DS. Remote sensing of infection levels thus consistently detected the same QTL regions as described by using visual ratings in earlier studies, indicating that a crop sensor can be easily applied in genetic mapping of stripe rust resistance in wheat. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Application of remote sensing to identify adult plant resistance loci to stripe rust in two bread wheat mapping populations

Loading next page...
 
/lp/springer_journal/application-of-remote-sensing-to-identify-adult-plant-resistance-loci-81xmP5cV9Q
Publisher
Springer US
Copyright
Copyright © 2016 by Springer Science+Business Media New York
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-016-9461-x
Publisher site
See Article on Publisher Site

Abstract

Phenotyping of wheat stripe rust in genetic studies has traditionally relied on quantifying disease by means of the modified Cobb Scale. This approach requires scoring of disease severity and response type, either on flag leaves or on a whole plot basis. The use of spectral crop sensors in wheat phenotyping has raised the question of whether this objective methodology is suitable for detecting stripe rust resistance loci in genetic studies. An Avocet S X Francolin#1 recombinant inbred population developed at the International Maize and Wheat Improvement Center (Centro Internacional de Mejoramiento de Maiz y Trigo—acronym CIMMYT), and a Kariega X Avocet S doubled haploid population developed in South Africa, both with available genetic maps, were used in this study. Field trials for stripe rust evaluation of these populations were planted at Greytown, South Africa in 2013 and 2014. Severe and uniformly distributed infection of Puccinia striiformis race 6E22A+ occurred in both years. Populations and parents were phenotyped according to the modified Cobb Scale and with a handheld Trimble GreenSeeker® crop sensor (model HCS-100). The sensing device emits red and infrared light and measures the reflectance of each wavelength in terms of the normalized difference vegetation index (NDVI). In both years, NDVI detected four previously characterized quantitative trait loci (QTL) on chromosomes 1BL, 2BS, 3BS and 6AL in the Avocet S X Francolin#1 population. The same QTL were detected with visual estimates in 2013 but only 2BS was significant in 2014. In the Kariega X Avocet S population, all stripe rust traits, including NDVI, mapped to previously described QTL on chromosomes 2BS, 4AL and 7DS. Remote sensing of infection levels thus consistently detected the same QTL regions as described by using visual ratings in earlier studies, indicating that a crop sensor can be easily applied in genetic mapping of stripe rust resistance in wheat.

Journal

Precision AgricultureSpringer Journals

Published: Jul 25, 2016

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off