Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/22501
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Robson, Andrew | en |
dc.contributor.author | Rahman, Muhammad Moshiur | en |
dc.contributor.author | Muir, Jasmine | en |
dc.date.accessioned | 2018-02-12T17:06:00Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Remote Sensing, 9(12), p. 1-20 | en |
dc.identifier.issn | 2072-4292 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/22501 | - |
dc.description.abstract | Accurate pre-harvest estimation of avocado (Persea americana cv. Haas) yield offers a range of benefits to industry and growers. Currently there is no commercial yield monitor available for avocado tree crops and the manual count method used for yield forecasting can be highly inaccurate. Remote sensing using satellite imagery offers a potential means to achieve accurate pre-harvest yield forecasting. This study evaluated the accuracies of high resolution WorldView (WV) 2 and 3 satellite imagery and targeted field sampling for the pre-harvest prediction of total fruit weight (kg·tree⁻¹) and average fruit size (g) and for mapping the spatial distribution of these yield parameters across the orchard block. WV 2 satellite imagery was acquired over two avocado orchards during 2014, and WV3 imagery was acquired in 2016 and 2017 over these same two orchards plus an additional three orchards. Sample trees representing high, medium and low vigour zones were selected from normalised difference vegetation index (NDVI) derived from the WV images and sampled for total fruit weight (kg·tree⁻¹) and average fruit size (g) per tree. For each sample tree, spectral reflectance data was extracted from the eight band multispectral WV imagery and 18 vegetation indices (VIs) derived. Principal component analysis (PCA) and non-linear regression analysis was applied to each of the derived VIs to determine the index with the strongest relationship to the measured total fruit weight and average fruit size. For all trees measured over the three year period (2014, 2016, and 2017) a consistent positive relationship was identified between the VI using near infrared band one and the red edge band (RENDVI1) to both total fruit weight (kg·tree⁻¹) (R² = 0.45, 0.28, and 0.29 respectively) and average fruit size (g) (R² = 0.56, 0.37, and 0.29 respectively) across all orchard blocks. Separate analysis of each orchard block produced higher R² values as well as identifying different optimal VIs for each orchard block and year. This suggests orchard location and growing season are influencing the relationship of spectral reflectance to total fruit weight and average fruit size. Classified maps of avocado yield (kg·tree⁻¹) and average fruit size per tree (g) were produced using the relationships developed for each orchard block. Using the relationships derived between the measured yield parameters and the optimal VIs, total fruit yield (kg) was calculated for each of the five sampled blocks for the 2016 and 2017 seasons and compared to actual yield at time of harvest and pre-season grower estimates. Prediction accuracies achieved for each block far exceeded those provided by the grower estimates. | en |
dc.language | en | en |
dc.publisher | MDPI AG | en |
dc.relation.ispartof | Remote Sensing | en |
dc.title | Using Worldview Satellite Imagery to Map Yield in Avocado (Persea americana): A Case Study in Bundaberg, Australia | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.3390/rs9121223 | en |
dcterms.accessRights | Gold | en |
dc.subject.keywords | Farm Management, Rural Management and Agribusiness | en |
dc.subject.keywords | Agricultural Spatial Analysis and Modelling | en |
dc.subject.keywords | Horticultural Production | en |
local.contributor.firstname | Andrew | en |
local.contributor.firstname | Muhammad Moshiur | en |
local.contributor.firstname | Jasmine | en |
local.subject.for2008 | 070104 Agricultural Spatial Analysis and Modelling | en |
local.subject.for2008 | 070106 Farm Management, Rural Management and Agribusiness | en |
local.subject.for2008 | 070699 Horticultural Production not elsewhere classified | en |
local.subject.seo2008 | 829999 Plant Production and Plant Primary Products not elsewhere classified | en |
local.subject.seo2008 | 820299 Horticultural Crops not elsewhere classified | en |
local.subject.seo2008 | 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences | en |
local.profile.school | School of Science and Technology | en |
local.profile.school | School of Science and Technology | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | arobson7@une.edu.au | en |
local.profile.email | mrahma37@une.edu.au | en |
local.profile.email | jmuir6@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.identifier.epublicationsrecord | une-20171128-095851 | en |
local.publisher.place | Switzerland | en |
local.identifier.runningnumber | 1223 | en |
local.format.startpage | 1 | en |
local.format.endpage | 20 | en |
local.identifier.scopusid | 85038213616 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 9 | en |
local.identifier.issue | 12 | en |
local.title.subtitle | A Case Study in Bundaberg, Australia | en |
local.access.fulltext | Yes | en |
local.contributor.lastname | Robson | en |
local.contributor.lastname | Rahman | en |
local.contributor.lastname | Muir | en |
dc.identifier.staff | une-id:arobson7 | en |
dc.identifier.staff | une-id:mrahma37 | en |
dc.identifier.staff | une-id:jmuir6 | en |
local.profile.orcid | 0000-0001-5762-8980 | en |
local.profile.orcid | 0000-0001-6430-0588 | en |
local.profile.orcid | 0000-0001-6114-0670 | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:22690 | en |
local.identifier.handle | https://hdl.handle.net/1959.11/22501 | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Using Worldview Satellite Imagery to Map Yield in Avocado (Persea americana) | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Robson, Andrew | en |
local.search.author | Rahman, Muhammad Moshiur | en |
local.search.author | Muir, Jasmine | en |
local.uneassociation | Unknown | en |
local.identifier.wosid | 000419235700019 | en |
local.year.published | 2017 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/b9876cc7-7e02-400d-aedc-19df5834ef44 | en |
local.subject.for2020 | 300206 Agricultural spatial analysis and modelling | en |
local.subject.for2020 | 300208 Farm management, rural management and agribusiness | en |
local.subject.seo2020 | 280101 Expanding knowledge in the agricultural, food and veterinary sciences | en |
dc.notification.token | 00fb895f-55fc-48f9-8031-07d79b426975 | en |
local.codeupdate.date | 2022-02-09T16:51:42.683 | en |
local.codeupdate.eperson | mrahma37@une.edu.au | en |
local.codeupdate.finalised | true | en |
local.original.for2020 | 300208 Farm management, rural management and agribusiness | en |
local.original.for2020 | undefined | en |
local.original.for2020 | 300206 Agricultural spatial analysis and modelling | en |
local.original.seo2020 | undefined | en |
local.original.seo2020 | 280101 Expanding knowledge in the agricultural, food and veterinary sciences | en |
local.original.seo2020 | undefined | en |
Appears in Collections: | Journal Article School of Science and Technology |
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