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https://nswdpe.intersearch.com.au/nswdpejspui/handle/1/15114Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dunn, Brian | en |
| dc.contributor.author | Dunn, Tina | en |
| dc.contributor.author | Hodges, Craig | en |
| dc.contributor.author | Dawe, Chris | en |
| dc.date.accessioned | 2024-09-18T01:19:26Z | en |
| dc.date.available | 2024-09-18T01:19:26Z | en |
| dc.date.issued | 2021 | en |
| dc.identifier.issn | 2652-6948 | en |
| dc.identifier.uri | https://nswdpe.intersearch.com.au/nswdpejspui/handle/1/15114 | en |
| dc.description.abstract | Key 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.publisher | Department of Primary Industries | en |
| dc.subject | Leeton, nitrogen, remote sensing, rice, self mulching clay, variety | en |
| dc.title | Predicting rice crop maturity using remote sensing | en |
| dc.title.alternative | Northern NSW research results 2021 | en |
| dc.type | Book chapter | en |
| Appears in Collections: | DPI Agriculture - Southern and Northern Research Results [2011-present] | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| SRR21-21-Dunn-rice-maturity-remotesensing-+.pdf | 169.04 kB | Adobe PDF | ![]() View/Open |
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