Knowledge Center Catalog

Prediction of aboveground biomass and dry‐matter content in brachiaria pastures by combining meteorological data and satellite imagery (Record no. 63521)

MARC details
000 -LEADER
fixed length control field 00595nab|a22002177a|4500
001 - CONTROL NUMBER
control field 63521
003 - CONTROL NUMBER IDENTIFIER
control field MX-TxCIM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20210326201926.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210113s2021||||xxk|||p|op||||00||0|eng|d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 1365-2494 (Online)
024 8# - OTHER STANDARD IDENTIFIER
Standard number or code https://doi.org/10.1111/gfs.12517
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 Bretas, I.L.
9 (RLIN) 19236
245 10 - TITLE STATEMENT
Title Prediction of aboveground biomass and dry‐matter content in brachiaria pastures by combining meteorological data and satellite imagery
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. United Kingdom :
Name of publisher, distributor, etc. Wiley,
Date of publication, distribution, etc. 2021.
500 ## - GENERAL NOTE
General note Peer review
520 ## - SUMMARY, ETC.
Summary, etc. Aboveground biomass (AGB) data are important for profitable and sustainable pasture management. In this study, we hypothesized that vegetation indexes (VIs) obtained through analysis of moderate spatial resolution satellite data (Landsat‐8 and Sentinel‐2) and meteorological data can accurately predict the AGB of Brachiaria (syn. Urochloa) pastures in Brazil. We used AGB field data obtained from pastures between 2015 and 2019 in four distinct regions of Brazil to evaluate (i) the relationship between three different VIs—normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2) and optimized soil adjusted vegetation index (OSAVI)—and meteorological data with pasture aboveground fresh biomass (AFB), aboveground dry biomass (ADB) and dry‐matter content (DMC); and (ii) the performance of simple linear regression (SLR), multiple linear regression (MLR) and random forest (RF) algorithms for the prediction of pasture AGB based on VIs obtained through satellite imagery combined with meteorological data. The results highlight a strong correlation (r) between VIs and AGB, particularly NDVI (r = 0.52 to 0.84). The MLR and RF algorithms demonstrated high potential to predict AFB (R2 = 0.76 to 0.85) and DMC (R2 = 0.78 to 0.85). We conclude that both MLR and RF algorithms improved the biomass prediction accuracy using satellite imagery combined with meteorological data to determine AFB and DMC, and can be used for Brachiaria (syn. Urochloa) AGB prediction. Additional research on tropical grasses is needed to evaluate different VIs to improve the accuracy of ADB prediction, thereby supporting pasture management in Brazil.
546 ## - LANGUAGE NOTE
Language note Text in English
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Biomass
Source of heading or term AGROVOC
9 (RLIN) 1897
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
Source of heading or term AGROVOC
9 (RLIN) 11127
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 Satellites
Source of heading or term AGROVOC
9 (RLIN) 3815
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Grasslands
Source of heading or term AGROVOC
9 (RLIN) 10923
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Vegetation index
Source of heading or term AGROVOC
9 (RLIN) 5833
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19237
Personal name Valente, D.S.M.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19238
Personal name Silva, F.F.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19239
Personal name Chizzotti, M.L.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19240
Personal name Paulino, M.F.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19241
Personal name D’Áurea, A.P.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19242
Personal name Paciullo, D.S.C.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19243
Personal name Pedreira, B.C.
700 1# - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19244
Personal name Chizzotti, F.H.M.
773 0# - HOST ITEM ENTRY
Related parts In press
Place, publisher, and date of publication United Kingdom : Wiley, 2021.
Title Grass and Forage Science
International Standard Serial Number 1365-2494
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
03/16/2021   03/16/2021 Article Not Lost Dewey Decimal Classification     Reprints Collection   CIMMYT Knowledge Center: John Woolston Library CIMMYT Knowledge Center: John Woolston Library 03/16/2021

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