MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03229nab|a22004217a|4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
65758 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
MX-TxCIM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20231009164120.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
20221s2022||||mx |||p|op||||00||0|eng|d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| International Standard Serial Number |
0378-4290 |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| Source |
1872-6852 (Online) |
| 024 8# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
https://doi.org/10.1016/j.fcr.2022.108730 |
| 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 |
|---|
| Personal name |
Fei, S. |
| 9 (RLIN) |
28380 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Application of multi-layer neural network and hyperspectral reflectance in genome-wide association study for grain yield in bread wheat |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc. |
Elsevier, |
| Date of publication, distribution, etc. |
2022. |
| Place of publication, distribution, etc. |
Amsterdam (Netherlands) : |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Grain yield (GY) is a primary trait for phenotype selection in crop breeding. Rapid and cost-effective prediction of GY before harvest from remote sensing platforms can be integrated with practical breeding activities. In this study, a natural population containing 166 wheat cultivars and elite lines was used for time-series prediction of GY using ground-based hyperspectral remote sensing. Canopy hyperspectral data (350–2500 nm) was collected at the flowering, early grain-filling (EGF), mid grain-filling (MGF), and late grain-filling (LGF) stages under four environments. GY was predicted by using full bands reflectance as input of multi-layer neural network. Genome-wide association study (GWAS) was performed using 373,106 markers from 660 K and 90 K single-nucleotide polymorphism (SNP) arrays in 166 wheat genotypes. Prediction accuracy for GY characterized by R2 values were 0.68, 0.69, 0.76, and 0.65 at flowering, EGF, MGF, and LGF, respectively. Among the 26 loci identified by predicted GY, 13 were located in similar positions to previously reported loci related to yield, and another 13 were potentially new loci. Linear regression (R2) ranged from 0.87 to 0.94 indicating that distinct cumulative effects of favorable alleles detected by predicted GY were increasing as compared to measured GY. This study highlights the feasibility of combining remote sensing with machine learning for wheat breeding decisions and to understand the underlying genetic basis of crop yield. |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
Text in English |
| 591 ## - CATALOGING NOTES |
|---|
| Affiliation |
Rasheed, A. : No CIMMYT Affiliation |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Remote sensing |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
1986 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Wheat |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
1310 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Yields |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
1313 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Genomes |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
1131 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Quantitative Trait Loci |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
1853 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Hassan, M.A. |
| 9 (RLIN) |
7723 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Yonggui Xiao |
| 9 (RLIN) |
1687 |
| 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 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Xianchun Xia |
| 9 (RLIN) |
377 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ma, Y. |
| 9 (RLIN) |
29186 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Luping Fu |
| 9 (RLIN) |
5903 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Zhen Chen |
| 9 (RLIN) |
19674 |
| 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 |
|---|
| Title |
Field Crops Research |
| Place, publisher, and date of publication |
Amsterdam (Netherlands) : Elsevier, 2022. |
| Related parts |
v. 289, art. 108730 |
| Record control number |
G444314 |
| International Standard Serial Number |
0378-4290 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Article |
| Suppress in OPAC |
No |
| Source of classification or shelving scheme |
Dewey Decimal Classification |