Knowledge Center Catalog

Feature engineering of environmental covariates improves plant genomic-enabled prediction (Record no. 67683)

MARC details
000 -LEADER
fixed length control field 03156nab|a22004697a|4500
001 - CONTROL NUMBER
control field 67683
003 - CONTROL NUMBER IDENTIFIER
control field MX-TxCIM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240919021234.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 20241s2024||||mx |||p|op||||00||0|eng|d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 1664-462X (Online)
024 8# - OTHER STANDARD IDENTIFIER
Standard number or code https://doi.org/10.3389/fpls.2024.1349569
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 Montesinos-Lopez, O.A.
Miscellaneous information Genetic Resources Program
Field link and sequence number I1706800
9 (RLIN) 2700
245 10 - TITLE STATEMENT
Title Feature engineering of environmental covariates improves plant genomic-enabled prediction
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. Frontiers Media S.A.,
Date of publication, distribution, etc. 2024.
Place of publication, distribution, etc. Switzerland :
500 ## - GENERAL NOTE
General note Peer review
500 ## - GENERAL NOTE
General note Open Access
520 ## - SUMMARY, ETC.
Summary, etc. Introduction: Because Genomic selection (GS) is a predictive methodology, it needs to guarantee high-prediction accuracies for practical implementations. However, since many factors affect the prediction performance of this methodology, its practical implementation still needs to be improved in many breeding programs. For this reason, many strategies have been explored to improve the prediction performance of this methodology. Methods: When environmental covariates are incorporated as inputs in the genomic prediction models, this information only sometimes helps increase prediction performance. For this reason, this investigation explores the use of feature engineering on the environmental covariates to enhance the prediction performance of genomic prediction models. Results and discussion: We found that across data sets, feature engineering helps reduce prediction error regarding only the inclusion of the environmental covariates without feature engineering by 761.625% across predictors. These results are very promising regarding the potential of feature engineering to enhance prediction accuracy. However, since a significant gain in prediction accuracy was observed in only some data sets, further research is required to guarantee a robust feature engineering strategy to incorporate the environmental covariates.
546 ## - LANGUAGE NOTE
Language note Text in English
591 ## - CATALOGING NOTES
Affiliation Montesinos-Lopez, O.A. : No CIMMYT Affiliation
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering
Source of heading or term AGROVOC
9 (RLIN) 23223
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Selection
Source of heading or term AGROVOC
9 (RLIN) 4749
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Marker-assisted selection
Source of heading or term AGROVOC
9 (RLIN) 10737
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Plant breeding
Miscellaneous information AGROVOC
Source of heading or term
9 (RLIN) 1203
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Crespo-Herrera, L.A.
Miscellaneous information Global Wheat Program
Field link and sequence number I1706538
9 (RLIN) 2608
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Saint Pierre, C.
Miscellaneous information Global Wheat Program
Field link and sequence number INT2731
9 (RLIN) 855
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Cano-Paez, B.
9 (RLIN) 29337
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Huerta Prado, G.I.
9 (RLIN) 33473
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Mosqueda-Gonzalez, B.A.
9 (RLIN) 19441
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ramos-Pulido, S.
9 (RLIN) 31496
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Gerard, G.S.
Field link and sequence number 1713398
Miscellaneous information Global Wheat Program
9 (RLIN) 11490
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Khalid Alnowibet
9 (RLIN) 34425
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Fritsche-Neto, R.
9 (RLIN) 6507
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Montesinos-Lopez, A.
9 (RLIN) 2702
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Crossa, J.
Miscellaneous information Genetic Resources Program
Field link and sequence number CCJL01
9 (RLIN) 59
773 0# - HOST ITEM ENTRY
Title Frontiers in Plant Science
Related parts v. 15, art. 1349569
Place, publisher, and date of publication Switzerland : Frontiers Media S.A., 2024.
Record control number 56875
International Standard Serial Number 1664-462X
856 4# - ELECTRONIC LOCATION AND ACCESS
Link text Open Access through DSpace
Uniform Resource Identifier https://hdl.handle.net/10883/34616
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Article
Suppress in OPAC No
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Date last seen Total Checkouts Price effective from Koha item type Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Withdrawn status Home library Current library Date acquired
07/03/2024   07/03/2024 Article Not Lost Dewey Decimal Classification     CIMMYT Staff Publications Collection   CIMMYT Knowledge Center: John Woolston Library CIMMYT Knowledge Center: John Woolston Library 07/03/2024

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