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dc.contributor.authorParr, Ben_US
dc.contributor.authorLegg, Men_US
dc.contributor.authorBradley, Sen_US
dc.contributor.authorAlam, Fen_US
dc.coverage.spatialSwitzerlanden_US
dc.date.available2021-03-20en_US
dc.date.available2021-03-17en_US
dc.date.issued2021-03-20en_US
dc.identifierhttps://www.ncbi.nlm.nih.gov/pubmed/33804742en_US
dc.identifiers21062182en_US
dc.identifier.citationSensors (Basel), 2021, 21 (6)en_US
dc.descriptionPublished source must be acknowledged with citationen_US
dc.description.abstractGrape yield estimation has traditionally been performed using manual techniques. However, these tend to be labour intensive and can be inaccurate. Computer vision techniques have therefore been developed for automated grape yield estimation. However, errors occur when grapes are occluded by leaves, other bunches, etc. Synthetic aperture radar has been investigated to allow imaging through leaves to detect occluded grapes. However, such equipment can be expensive. This paper investigates the potential for using ultrasound to image through leaves and identify occluded grapes. A highly directional low frequency ultrasonic array composed of ultrasonic air-coupled transducers and microphones is used to image grapes through leaves. A fan is used to help differentiate between ultrasonic reflections from grapes and leaves. Improved resolution and detail are achieved with chirp excitation waveforms and near-field focusing of the array. The overestimation in grape volume estimation using ultrasound reduced from 222% to 112% compared to the 3D scan obtained using photogrammetry or from 56% to 2.5% compared to a convex hull of this 3D scan. This also has the added benefit of producing more accurate canopy volume estimations which are important for common precision viticulture management processes such as variable rate applications.en_US
dc.languageengen_US
dc.relation.urihttps://www.mdpi.com/1424-8220/21/6/2182en_US
dc.rightsThe Author(s) CC BY 4.0en_US
dc.subjectarrayen_US
dc.subjectcanopy estimationen_US
dc.subjectnondestructiveen_US
dc.subjectremote sensingen_US
dc.subjectsmart agricultureen_US
dc.subjectultrasounden_US
dc.subjectvine yielden_US
dc.titleOccluded Grape Cluster Detection and Vine Canopy Visualisation Using an Ultrasonic Phased Array.en_US
dc.typeJournal Article
dc.citation.volume21en_US
dc.identifier.doi10.3390/s21062182en_US
dc.identifier.elements-id441675
dc.relation.isPartOfSensors (Basel)en_US
dc.citation.issue6en_US
dc.identifier.eissn1424-8220en_US
dc.description.publication-statusPublished onlineen_US
pubs.organisational-group/Massey University
pubs.organisational-group/Massey University/College of Sciences
pubs.organisational-group/Massey University/College of Sciences/School of Food & Advanced Technology Albany
dc.identifier.harvestedMassey_Dark
pubs.notesNot knownen_US
dc.subject.anzsrc0301 Analytical Chemistryen_US
dc.subject.anzsrc0805 Distributed Computingen_US
dc.subject.anzsrc0906 Electrical and Electronic Engineeringen_US
dc.subject.anzsrc0502 Environmental Science and Managementen_US
dc.subject.anzsrc0602 Ecologyen_US


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