Fastlink to record 333353
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| Full TGIF Record # 333353 Item 1 of 1 |
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| Web URL(s): | https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/149620 Last checked: 11/29/2023 |
| Publication Type: | Report |
| Content Type: | Abstract or Summary only |
| Author(s): | Yang, Haoguang |
| Author Affiliation: | Presenting Author and Plant Biology, Rutgers University, New Brunswick, NJ |
| Title: | Remote sensing for high throughput phenotyping and detection of stress from deficit irrigation for creeping bentgrass |
| Section: | Turfgrass water conservation and management oral (includes student competition) Other records with the "Turfgrass water conservation and management oral (includes student competition)" Section C05 turfgrass science Other records with the "C05 turfgrass science" Section |
| Meeting Info.: | St. Louis, Missouri: October 29-November 1, 2023 |
| Source: | ASA, CSSA, SSSA International Annual Meeting. 2023, p. 149620. |
| Publishing Information: | [Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America] |
| # of Pages: | 1 |
| Abstract/Contents: | "Preventing drought stress is an essential aspect in turfgrass management as well as one of the major costs in regular turf maintainace. For turfgrass research, reducing cost of irrigation has been one of the major focuses of the field. In recent years, many advancements in turfgrass physiology, remote-sensing and high-throughput phenotyping have enabled us to develop a noval way to predict and monitor turfgrass drought status. In this study, we intend to develop a Unmanned Aircraft System (UAS)-based, precision turfgrass manangement system for water conservation. We used hyperspectral imaging system in lab environment to analyze various vegetation and photochemical indices for predictibility of drought stress in Kentucky Bluegrass (Poa pratensis) and tested candidate vegetation indices in a gradient-irrigation field of Creeping Bentgrass (Agrostis stolonifera) using UAS-based multispectral imaging system." |
| Language: | English |
| References: | 0 |
| Note: | "39-2" This item is an abstract only! |
| ASA/CSSA/SSSA Citation (Crop Science-like – may be incomplete): | Yang, H. 2023. Remote sensing for high throughput phenotyping and detection of stress from deficit irrigation for creeping bentgrass. Agron. Abr. p. 149620. |
| Fastlink to access this record outside TGIF: | http://tic.msu.edu/tgif/flink/RECNO/333353 |
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| Web URL(s) : | https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/149620 Last checked: 11/29/2023 |
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