Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/53795
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRahman, Muhammad Moshiuren
dc.contributor.authorRobson, Andrewen
dc.contributor.authorBrinkhoff, Jamesen
dc.date.accessioned2022-12-12T03:37:11Z-
dc.date.available2022-12-12T03:37:11Z-
dc.date.issued2022-11-24-
dc.identifier.citationRemote Sensing, 14(23), p. 1-18en
dc.identifier.issn2072-4292en
dc.identifier.urihttps://hdl.handle.net/1959.11/53795-
dc.description.abstractThe ability to accurately and systematically monitor avocado crop phenology offers significant benefits for the optimization of farm management activities, improvement of crop productivity, yield estimation, and evaluation crops' resilience to extreme weather conditions and future climate change. In this study, Sentinel-2-derived enhanced vegetation indices (EVIs) from 2017 to 2021 were used to retrieve canopy reflectance information that coincided with crop phenological stages, such as flowering (F), vegetative growth (V), fruit maturity (M), and harvest (H), in commercial avocado orchards in Bundaberg, Queensland and Renmark, South Australia. Tukey's honestly significant difference (Tukey-HSD) test after one-way analysis of variance (ANOVA) with EVI metrics (EVI<sub>mean</sub> and EVI<sub>slope</sub>) showed statistically significant differences between the four phenological stages. From a Pearson correlation analysis, a distinctive seasonal trend of EVIs was observed (R = 0.68 to 0.95 for Bundaberg and R = 0.8 to 0.96 for Renmark) in all 5 years, with the peak EVIs being observed at the M stage and the trough being observed at the F stage. However, a Tukey-HSD test showed significant variability in mean EVI values between seasons for both the Bundaberg and Renmark farms. The variability of the mean EVIs between the two farms was also evident with a <i>p</i>-value < 0.001. This novel study highlights the applicability of remote sensing for the monitoring of avocado phenological stages retrospectively and near-real time. This information not only supports the 'benchmarking' of seasonal orchard performance to identify potential impacts of seasonal weather variation and pest and disease incursions, but when seasonal growth profiles are aligned with the corresponding annual production, it can also be used to develop phenology-based yield prediction models.en
dc.languageenen
dc.publisherMDPI AGen
dc.relation.ispartofRemote Sensingen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titlePotential of Time-Series Sentinel 2 Data for Monitoring Avocado Crop Phenologyen
dc.typeJournal Articleen
dc.identifier.doi10.3390/rs14235942en
dcterms.accessRightsUNE Greenen
local.contributor.firstnameMuhammad Moshiuren
local.contributor.firstnameAndrewen
local.contributor.firstnameJamesen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailmrahma37@une.edu.auen
local.profile.emailarobson7@une.edu.auen
local.profile.emailjbrinkho@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeSwitzerlanden
local.identifier.runningnumber5942en
local.format.startpage1en
local.format.endpage18en
local.peerreviewedYesen
local.identifier.volume14en
local.identifier.issue23en
local.access.fulltextYesen
local.contributor.lastnameRahmanen
local.contributor.lastnameRobsonen
local.contributor.lastnameBrinkhoffen
dc.identifier.staffune-id:mrahma37en
dc.identifier.staffune-id:arobson7en
dc.identifier.staffune-id:jbrinkhoen
local.profile.orcid0000-0001-6430-0588en
local.profile.orcid0000-0001-5762-8980en
local.profile.orcid0000-0002-0721-2458en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/53795en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitlePotential of Time-Series Sentinel 2 Data for Monitoring Avocado Crop Phenologyen
local.relation.fundingsourcenoteHorticulture Innovation Australia Ltd. (HIA), project number AV21006en
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorRahman, Muhammad Moshiuren
local.search.authorRobson, Andrewen
local.search.authorBrinkhoff, Jamesen
local.open.fileurlhttps://rune.une.edu.au/web/retrieve/f1772751-2a84-4697-8efe-df16cd2b7735en
local.uneassociationYesen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2022en
local.fileurl.openhttps://rune.une.edu.au/web/retrieve/f1772751-2a84-4697-8efe-df16cd2b7735en
local.fileurl.openpublishedhttps://rune.une.edu.au/web/retrieve/f1772751-2a84-4697-8efe-df16cd2b7735en
local.subject.for2020300206 Agricultural spatial analysis and modellingen
local.subject.for2020300802 Horticultural crop growth and developmenten
local.subject.for2020300207 Agricultural systems analysis and modellingen
local.subject.seo2020260502 Avocadoen
local.subject.seo2020280101 Expanding knowledge in the agricultural, food and veterinary sciencesen
local.subject.seo2020280111 Expanding knowledge in the environmental sciencesen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
Appears in Collections:Journal Article
School of Science and Technology
Files in This Item:
2 files
File Description SizeFormat 
openpublished/PotentialRahmanRobsonBrinkhoff2022JournalArticle.pdfPublished version2.99 MBAdobe PDF
Download Adobe
View/Open
Show simple item record

SCOPUSTM   
Citations

2
checked on Dec 21, 2024

Page view(s)

288
checked on Mar 9, 2023

Download(s)

6
checked on Mar 9, 2023
Google Media

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons