Knowledge Center Catalog

Using continous wavelet analysis for monitoring wheat yellow rust in different infestation stages based on unmanned aerial vehicle hyperspectral images (Record no. 63325)

MARC details
000 -LEADER
fixed length control field 01807nab|a22003377a|4500
001 - CONTROL NUMBER
control field 63325
003 - CONTROL NUMBER IDENTIFIER
control field MX-TxCIM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20211006073557.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190911s2020||||xxu|||p|op||||00||0|eng|d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 1559-128X
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 2155-3165 (Online)
024 8# - OTHER STANDARD IDENTIFIER
Standard number or code https://doi.org/10.1364/AO.397844
040 ## - CATALOGING SOURCE
Original cataloging agency MX-TxCIM
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
100 0# - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 18444
Personal name Qiong Zheng
245 10 - TITLE STATEMENT
Title Using continous wavelet analysis for monitoring wheat yellow rust in different infestation stages based on unmanned aerial vehicle hyperspectral images
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. USA :
Name of publisher, distributor, etc. OSA Publishing,
Date of publication, distribution, etc. 2020.
500 ## - GENERAL NOTE
General note Peer review
520 ## - SUMMARY, ETC.
Summary, etc. Yellow rust is the most extensive disease in wheat cultivation, seriously affecting crop quality and yield. This study proposes sensitive wavelet features (WFs) for wheat yellow rust monitoring based on unmanned aerial vehicle hyperspectral imagery of different infestation stages [26 days after inoculation (26 DAI) and 42 DAI]. Furthermore, we evaluated the monitoring ability of WFs and vegetation indices on wheat yellow rust through linear discriminant analysis and support vector machine (SVM) classification frameworks in different infestation stages, respectively. The results show that WFs-SVM have promising potential for wheat yellow rust monitoring in both the 26 DAI and 42 DAI stages.
546 ## - LANGUAGE NOTE
Language note Text in English
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Source of heading or term AGROVOC
9 (RLIN) 6664
Topical term or geographic name as entry element Monitoring
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Plant diseases
Miscellaneous information AGROVOC
Source of heading or term
9 (RLIN) 1206
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) 18428
Personal name Wenjiang Huang
700 0# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 18445
Personal name Huichun Ye
700 0# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 18446
Personal name Yingying Dong
700 0# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 18447
Personal name Yue Shi
700 0# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 18448
Personal name Shuisen Chen
773 0# - HOST ITEM ENTRY
Related parts v. 59, no. 26, p. 8003-8013
Place, publisher, and date of publication USA : OSA Publishing, 2020.
International Standard Serial Number 1559-128X
Title Applied Optics
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
02/12/2021   02/12/2021 Article Not Lost Dewey Decimal Classification     Reprints Collection   CIMMYT Knowledge Center: John Woolston Library CIMMYT Knowledge Center: John Woolston Library 02/12/2021

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