MARC details
000 -LEADER |
fixed length control field |
03700nab a22004097a 4500 |
001 - CONTROL NUMBER |
control field |
61504 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
MX-TxCIM |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20231009164119.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
200320s2019 xxk|||p|op||| 00| 0 eng d |
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
International Standard Serial Number |
1746-4811 |
024 8# - OTHER STANDARD IDENTIFIER |
Standard number or code |
https://doi.org/10.1186/s13007-019-0419-7 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
MX-TxCIM |
041 ## - LANGUAGE CODE |
Language code of text/sound track or separate title |
eng |
100 1# - MAIN ENTRY--PERSONAL NAME |
9 (RLIN) |
7723 |
Personal name |
Hassan, M.A. |
245 10 - TITLE STATEMENT |
Title |
Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc. |
London (United Kingdom) : |
Name of publisher, distributor, etc. |
BioMed Central, |
Date of publication, distribution, etc. |
2019. |
500 ## - GENERAL NOTE |
General note |
Peer review |
500 ## - GENERAL NOTE |
General note |
Open Access |
520 ## - SUMMARY, ETC. |
Summary, etc. |
Background. Plant height is an important selection target since it is associated with yield potential, stability and particularly with lodging resistance in various environments. Rapid and cost-effective estimation of plant height from airborne devices using a digital surface model can be integrated with academic research and practical wheat breeding programs. A bi-parental wheat population consisting of 198 doubled haploid lines was used for time-series assessments of progress in reaching final plant height and its accuracy was assessed by quantitative genomic analysis. UAV-based data were collected at the booting and mid-grain fill stages from two experimental sites and compared with conventional measurements to identify quantitative trait loci (QTL) underlying plant height. Results. A significantly high correlation of R2 = 0.96 with a 5.75 cm root mean square error was obtained between UAV-based plant height estimates and ground truth observations at mid-grain fill across both sites. Correlations for UAV and ground-based plant height data were also very high (R2 = 0.84–0.85, and 0.80–0.83) between plant height at the booting and mid-grain fill stages, respectively. Broad sense heritabilities were 0.92 at booting and 0.90–0.91 at mid-grain fill across sites for both data sets. Two major QTL corresponding to Rht-B1 on chromosome 4B and Rht-D1 on chromosome 4D explained 61.3% and 64.5% of the total phenotypic variations for UAV and ground truth data, respectively. Two new and stable QTL on chromosome 6D seemingly associated with accelerated plant growth was identified at the booting stage using UAV-based data. Genomic prediction accuracy for UAV and ground-based data sets was significantly high, ranging from r = 0.47–0.55 using genome-wide and QTL markers for plant height. However, prediction accuracy declined to r = 0.20–0.31 after excluding markers linked to plant height QTL. Conclusion. This study provides a fast way to obtain time-series estimates of plant height in understanding growth dynamics in bread wheat. UAV-enabled phenotyping is an effective, high-throughput and cost-effective approach to understand the genetic basis of plant height in genetic studies and practical breeding. |
526 ## - STUDY PROGRAM INFORMATION NOTE |
Program name |
Wheat CRP |
Wheat Flagship Projects |
FP2 - Novel diversity and tools adapt to climate change and resource constraints |
546 ## - LANGUAGE NOTE |
Language note |
Text in English |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Source of heading or term |
AGROVOC |
9 (RLIN) |
1836 |
Topical term or geographic name as entry element |
Aerial surveying |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Source of heading or term |
AGROVOC |
9 (RLIN) |
1132 |
Topical term or geographic name as entry element |
Genomics |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Source of heading or term |
AGROVOC |
9 (RLIN) |
1853 |
Topical term or geographic name as entry element |
Quantitative Trait Loci |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Source of heading or term |
AGROVOC |
9 (RLIN) |
1296 |
Topical term or geographic name as entry element |
Triticum aestivum |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Source of heading or term |
AGROVOC |
9 (RLIN) |
11401 |
Topical term or geographic name as entry element |
Unmanned aerial vehicles |
700 0# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
7724 |
Personal name |
Mengjiao Yang |
700 0# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
5903 |
Personal name |
Luping Fu |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Awais Rasheed |
Miscellaneous information |
Global Wheat Program |
Field link and sequence number |
I1706474 |
9 (RLIN) |
1938 |
700 1# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
3434 |
Personal name |
Bangyou Zheng |
700 0# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
377 |
Personal name |
Xianchun Xia |
700 0# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
1687 |
Personal name |
Yonggui Xiao |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
He Zhonghu |
Miscellaneous information |
Global Wheat Program |
Field link and sequence number |
INT2411 |
9 (RLIN) |
838 |
773 0# - HOST ITEM ENTRY |
Place, publisher, and date of publication |
London (United Kingdom) : BioMed Central, 2019. |
Related parts |
v. 15, art. 37 |
Title |
Plant Methods |
Record control number |
57210 |
International Standard Serial Number |
1746-4811 |
856 4# - ELECTRONIC LOCATION AND ACCESS |
Link text |
Open Access through DSpace |
Uniform Resource Identifier |
https://hdl.handle.net/10883/20808 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Article |
Suppress in OPAC |
No |