Please use this identifier to cite or link to this item: https://nswdpe.intersearch.com.au/nswdpejspui/handle/1/15114
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dc.contributor.authorDunn, Brianen
dc.contributor.authorDunn, Tinaen
dc.contributor.authorHodges, Craigen
dc.contributor.authorDawe, Chrisen
dc.date.accessioned2024-09-18T01:19:26Zen
dc.date.available2024-09-18T01:19:26Zen
dc.date.issued2021en
dc.identifier.issn2652-6948en
dc.identifier.urihttps://nswdpe.intersearch.com.au/nswdpejspui/handle/1/15114en
dc.description.abstractKey findings • Grain moisture content was predicted with a high level of accuracy (R2 = 0.88 to 0.94) for each variety using normalised difference vegetation index (NDVI), but predictions were different across varieties. • This research is valuable as proof of concept, highlighting that the opportunity exists to potentially use NDVI to predict grain maturity across a rice field. • The difficult decision of when to drain a rice crop could be improved by using remote sensing and within-field variability could be accounted for in the decision-making process.en
dc.publisherDepartment of Primary Industriesen
dc.subjectLeeton, nitrogen, remote sensing, rice, self mulching clay, varietyen
dc.titlePredicting rice crop maturity using remote sensingen
dc.title.alternativeNorthern NSW research results 2021en
dc.typeBook chapteren
Appears in Collections:DPI Agriculture - Southern and Northern Research Results [2011-present]

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