Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/20119
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dc.contributor.authorRobson, Andrewen
dc.contributor.authorRahman, Muhammad Moshiuren
dc.contributor.authorMuir, Jasmineen
dc.contributor.authorSaint, Ashleyen
dc.contributor.authorSimpson, Chaden
dc.contributor.authorSearle, Chrisen
dc.date.accessioned2017-02-27T09:04:00Z
dc.date.issued2016en
dc.identifier.citation19th Precision Agriculture Symposium Proceedings, p. 36-43en
dc.identifier.urihttps://hdl.handle.net/1959.11/20119en
dc.description.abstractAccurate yield forecasting in high value fruit tree crops provides vital management information to growers as well as supporting improved decision making, including postharvest handling, storage and forward selling. Current research evaluated the 8 spectral band WorldView 3 (WV-3) with a spatial resolution of 1.2 m, as a tool for exploring the relationship between individual tree canopy reflectance and a number of tree growth parameters, including yield. WV-3 imagery was captured on the 7th of April, 2016, over two Macadamia ('Macadamia integrifolia') and three Avocado ('Persea americana') orchards growing near the Queensland township of Bundaberg, Australia. Using the extent of each block, the WV-3 imagery was sub-setted and classified into 8 Normalised Difference Vegetation index (NDVI) classes. From these classes 6 replicate trees were selected to represent high, medium and low NDVI regions (n=18) and subsequently ground truthed for a number of yield parameters during April and May, 2016. The measured parameters were then correlated against 20 structural and pigment based vegetation indices derived from the 8 band spectral information corresponding to each individual tree canopy (12.6 m2). The results identified a positive relationship between derived vegetation indices (VI) and fruit weight (kg/tree) R2 > 0.69 for Macadamia and R2 > 0.68 for Avocado; and fruit number R2 > 0.6 for Macadamia and R2 > 0.61 for Avocado. The algorithm derived between the optimum VI and yield for each block was then applied across the entire block to derive a yield map. The results show that remote sensing of tree canopy condition can be used to measure yield parameters in Macadamia and Avocado grown in the Bundaberg region.en
dc.languageenen
dc.publisherSPAA Precision Agriculture Australiaen
dc.relation.ispartof19th Precision Agriculture Symposium Proceedingsen
dc.titleEvaluating satellite remote sensing as a method for measuring yield variability in Avocado and Macadamia tree cropsen
dc.typeConference Publicationen
dc.relation.conference19th Symposium on Precision Agriculture in Australasia, Toowoomba, Australia, 12th - 13th September, 2016en
dc.subject.keywordsHorticultural Crop Growth and Developmenten
local.contributor.firstnameAndrewen
local.contributor.firstnameMuhammad Moshiuren
local.contributor.firstnameJasmineen
local.contributor.firstnameAshleyen
local.contributor.firstnameChaden
local.contributor.firstnameChrisen
local.subject.for2008070601 Horticultural Crop Growth and Developmenten
local.subject.seo2008820206 Macadamiasen
local.subject.seo2008820211 Stone Fruiten
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailarobson7@une.edu.auen
local.profile.emailmrahma37@une.edu.auen
local.profile.emailjmuir6@une.edu.auen
local.profile.emailasaint2@une.edu.auen
local.output.categoryE2en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20170112-161735en
local.publisher.placeToowoomba, Australiaen
local.format.startpage36en
local.format.endpage43en
local.contributor.lastnameRobsonen
local.contributor.lastnameRahmanen
local.contributor.lastnameMuiren
local.contributor.lastnameSainten
local.contributor.lastnameSimpsonen
local.contributor.lastnameSearleen
dc.identifier.staffune-id:arobson7en
dc.identifier.staffune-id:mrahma37en
dc.identifier.staffune-id:jmuir6en
dc.identifier.staffune-id:asaint2en
local.profile.orcid0000-0001-5762-8980en
local.profile.orcid0000-0001-6430-0588en
local.profile.orcid0000-0001-6114-0670en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
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local.identifier.unepublicationidune:20316en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleEvaluating satellite remote sensing as a method for measuring yield variability in Avocado and Macadamia tree cropsen
local.output.categorydescriptionE2 Non-Refereed Scholarly Conference Publicationen
local.relation.urlhttp://www.spaa.com.au/pdf/429_PA_Symposium_16_LR.pdfen
local.conference.details19th Symposium on Precision Agriculture in Australasia, Toowoomba, Australia, 12th - 13th September, 2016en
local.description.statisticsepubsVisitors: 67<br />Views: 69<br />Downloads: 1en
local.search.authorRobson, Andrewen
local.search.authorRahman, Muhammad Moshiuren
local.search.authorMuir, Jasmineen
local.search.authorSaint, Ashleyen
local.search.authorSimpson, Chaden
local.search.authorSearle, Chrisen
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