Show simple record

dc.contributor.authorHolmes, Wayne
dc.contributor.authorLook, Morgan
dc.contributor.authorLai, Anthony
dc.contributor.authorSidhu, Deepinder
dc.date.accessioned2021-03-18T23:40:54Z
dc.date.available2021-03-18T23:40:54Z
dc.date.issued2020-12-07
dc.identifier.urihttps://hdl.handle.net/10652/5214
dc.description.abstractThis study looks at the classification of plant species and components using Hyperspectral cameras in the Near Infrared region of the spectrum as part of a move towards precision agriculture. The NIR region of the electromagnetic spectrum lies just below the visible spectrum. Its longer wavelength has several advantages over visible light such as the ability to penetrate significantly below the surface of a material and along with absorption peaks for many chemical groups present in this region. In this work proximal spectral reflectance images were used of common New Zealand pasture weeds in order to determine the inter- and intra- species proximal spectral reflectance variations. It examined the ability and extent of accuracy when using hyperspectral cameras to uniquely identify three common species of weeds that grow in pastures based on their reflectance spectra alone. The use of these cameras showed that considerable measurement noise in the spectral data was present. This noise was due to using uncontrolled lighting i.e. solar illumination in field applications and the effect of scattered light on shading in the image. It was shown that a significant reduction of noise can be achieved by careful experimental design prior to acquiring the images. Despite the noise the study was successful in identifying weed species based purely on the reflectance spectra. This work also showed the ability of hyperspectral near-infrared imaging to identify the plant components such as flowers, stems and leaves on individual plantsen_NZ
dc.language.isoenen_NZ
dc.subjectNew Zealanden_NZ
dc.subjectweed detection and identificationen_NZ
dc.subjectweedsen_NZ
dc.subjectpasturesen_NZ
dc.subjectspectral reflectanceen_NZ
dc.subjectfield spectroscopyen_NZ
dc.subjectproximal imagingen_NZ
dc.subjectspectral imagingen_NZ
dc.titleHyperspectral NIR imaging of plant materialen_NZ
dc.typeConference Contribution - Oral Presentationen_NZ
dc.date.updated2021-03-18T13:30:07Z
dc.rights.holderAuthorsen_NZ
dc.subject.marsden070308 Crop and Pasture Protection (Pests, Diseases and Weeds)en_NZ
dc.identifier.bibliographicCitationHolmes, W., Look, M., Lai, A., & Sidhu, D. (2020, December). Hyperspectral NIR imaging of Plant Material. Paper presented at the Unitec Research Symposium, Mount Albert Campus, Unitec.en_NZ
unitec.publication.titleUnitec Research Symposium 2020en_NZ
unitec.conference.titleAnnual Unitec Research Symposium 2020en_NZ
unitec.conference.orgUnitec Institute of Technologyen_NZ
unitec.conference.locationMount Albert, Auckland, New Zealanden_NZ
unitec.conference.sdate2020-12-07
unitec.conference.edate2020-12-07
unitec.peerreviewedyesen_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
dc.contributor.affiliationUniversity of Waikatoen_NZ
dc.contributor.affiliationCallaghan Innovation (N.Z.)en_NZ
unitec.identifier.roms65458en_NZ
unitec.identifier.roms65408
unitec.identifier.roms65478
unitec.publication.placeMount Albert, Auckland, New Zealanden_NZ
unitec.institution.studyareaConstruction + Engineeringen_NZ


Files in this item

Thumbnail

This item appears in

Show simple record


© Unitec Institute of Technology, Private Bag 92025, Victoria Street West, Auckland 1142