Knowledge Center Catalog

An automatic method based on daily in situ images and deep learning to date wheat heading stage (Record no. 62023)

MARC details
000 -LEADER
fixed length control field 02627nab a22003857a 4500
001 - CONTROL NUMBER
control field 62023
003 - CONTROL NUMBER IDENTIFIER
control field MX-TxCIM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251010172732.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200602s2020 ne |||p|op||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 0378-4290
024 8# - OTHER STANDARD IDENTIFIER
Standard number or code https://doi.org/10.1016/j.fcr.2020.107793
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) 13778
Personal name Velumani, K.
245 13 - TITLE STATEMENT
Title An automatic method based on daily in situ images and deep learning to date wheat heading stage
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. Amsterdam (Netherlands) :
Name of publisher, distributor, etc. Elsevier,
Date of publication, distribution, etc. 2020.
500 ## - GENERAL NOTE
General note Peer review
520 ## - SUMMARY, ETC.
Summary, etc. Accurate and timely observations of wheat phenology and, particularly, of heading date are instrumental for many scientific and technical domains such as wheat ecophysiology, crop breeding, crop management or precision agriculture. Visual annotation of the heading date in situ is a labour-intensive task that may become prohibitive in scientific and technical activities where high-throughput is needed. This study presents an automatic method to estimate wheat heading date from a series of daily images acquired by a fixed RGB camera in the field. A convolutional neural network (CNN) is trained to identify the presence of spikes in small patches. The heading date is then estimated from the dynamics of the spike presence in the patches over time. The method is applied and validated over a large set of 47 experimental sites located in different regions in France, covering three years with nine wheat cultivars. Results show that our method provides good estimates of the heading dates with a root mean square error close to 2 days when compared to the visual scoring from experts. It outperforms the predictions of a phenological model based on the ARCWHEAT crop model calibrated for our local conditions. The potentials and limits of the proposed methodology towards a possible operational implementation in agronomic applications and decision support systems are finally further discussed.
546 ## - LANGUAGE NOTE
Language note Text in English
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Source of heading or term AGROVOC
9 (RLIN) 4770
Topical term or geographic name as entry element Phenology
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Source of heading or term AGROVOC
9 (RLIN) 4872
Topical term or geographic name as entry element Internet
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Source of heading or term AGROVOC
9 (RLIN) 9056
Topical term or geographic name as entry element Neural Networks
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Source of heading or term AGROVOC
9 (RLIN) 2530
Topical term or geographic name as entry element Sensors
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Source of heading or term AGROVOC
9 (RLIN) 11710
Topical term or geographic name as entry element Modelling
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 10190
Personal name Madec, S.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name De Solan, B.
9 (RLIN) 10072
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 13779
Personal name Lopez-Lozano, R.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 13780
Personal name Gillet, J.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 13781
Personal name Labrosse, J.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 13782
Personal name Jezequel, S.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 10054
Personal name Comar, A.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 10106
Personal name Baret, F.
773 0# - HOST ITEM ENTRY
Place, publisher, and date of publication Amsterdam (Netherlands) : Elsevier, 2020.
Related parts v. 252, art. 107793
Title Field Crops Research
International Standard Serial Number 0378-4290
Record control number u444314
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Article
Suppress in OPAC No
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
06/04/2020   06/04/2020 Article Not Lost Dewey Decimal Classification     Reprints Collection   CIMMYT Knowledge Center: John Woolston Library CIMMYT Knowledge Center: John Woolston Library 06/04/2020

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