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| Web URL(s): | https://turf.rutgers.edu/wp-content/uploads/2024/03/symposium-2024.pdf#page=30
Last checked: 04/11/2024
Requires: PDF Reader
Notes: Item is within a single large file |
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| Publication Type:
| Report |
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| Content Type: | Abstract or Summary only |
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| Author(s): | Errickson, William;
Gaylert, Spencer;
Jin, Yanhong;
Cuite, Cara;
Huang, Bingru |
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| Author Affiliation: | Errickson: Department of Agriculture and Natural Resources, Rutgers University; Jin: Department of Agriculture, Food and Resource Economics, Rutgers University; Cuite: Department of Human Ecology, Rutgers University; Huang: Department of Plant Biology, Rutgers University |
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| Title: | Needs assessment for remote sensing- and machine learning-guided precision turfgrass irrigation programs: Findings from a socioeconomic survey |
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| Section: | Poster presentations
Other records with the "Poster presentations" Section
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| Meeting Info.: | Institute for Food, Nutrition, and Health Building, Room 101: March 14, 2024 |
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| Source: | Proceedings of the Thirty-Third Annual RutgersTurfgrass Symposium. Vol. 33, 2024, p. 30. |
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| Publishing Information: | School of Environmental and Biological Sciences, Rutgers University |
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| # of Pages: | 1 |
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| Abstract/Contents: | "New technologies including mobile remote sensing and artificial intelligence-guided precision irrigation management (PIM) programs may offer turfgrass managers additional tools to reduce water use and improve turf quality. However, adoption of these new practices may be limited by factors such as startup costs, perceived importance, and the learning curve associated with new technology. This project conducted an industry-wide survey of turfgrass professionals to investigate their current irrigation management strategies, and how likely they may be to adopt new PIM technologies. Survey participants included turfgrass researchers, superintendents, sod farmers, and landscape professionals. One hundred survey responses were received from 15 different states, with New Jersey (32%), Georgia (27%), and New York (16%) having the highest representation. Survey responses indicated current water use and cost for existing operations, importance ratings of various characteristics associated with PIM and water conservation, and likelihood of adoption based on cost-benefit scenarios. Respondents indicated that the most important factors for conserving water use in their organization were drought or infrequent rainfall, regulations, and water use restrictions. Early detection of biotic and abiotic stress emerged as a primary and practical application for PIM technology. Additionally, while only 18% of respondents were currently using PIM technology, 68% indicated they would be interested in purchasing either PIM devices or an annually renewable PIM service. These findings provide valuable insights that can steer future research, development, training, and education initiatives. This includes the advancement of Extension programs dedicated to turfgrass PIM and the associated decision support systems." |
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| Language: | English |
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| References: | 0 |
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| See Also: | Original version appears in ASA, CSSA, SSSA International Annual Meeting, 2023, p. 150720, R=333501. R=333501 |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Errickson, W., S. Gaylert, Y. Jin, C. Cuite, and B. Huang. 2024. Needs assessment for remote sensing- and machine learning-guided precision turfgrass irrigation programs: Findings from a socioeconomic survey. Proc. Rutgers Turfgrass Symp. 33:p. 30. |
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| Web URL(s):
https://turf.rutgers.edu/wp-content/uploads/2024/03/symposium-2024.pdf#page=30
Last checked: 04/11/2024
Requires: PDF Reader
Notes: Item is within a single large file |
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MSU catalog number: b3696858 |
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