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| DOI: | 10.2134/agronj2006.0022 |
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| Web URL(s): | https://dl.sciencesocieties.org/publications/aj/articles/98/6/1640
Last checked: 11/02/2016
Access conditions: Item is within a limited-access website
https://dl.sciencesocieties.org/publications/aj/pdfs/98/6/1640
Last checked: 11/04/2016
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Access conditions: Item is within a limited-access website |
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| Publication Type:
| Refereed |
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| Author(s): | Kruse, Jason K.;
Christians, Nick E.;
Chaplin, Michael H. |
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| Author Affiliation: | Kruse: University of Wisconsin Extension, Oshkosh, Wisconsin; Christians and Chaplin: Department of Horticulture, Iowa State University, Ames, Iowa |
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| Title: | Remote sensing of Nitrogen stress in creeping bentgrass |
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| Section: | Remote sensing
Other records with the "Remote sensing" Section
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| Source: | Agronomy Journal. Vol. 98, No. 6, November/December 2006, p. 1640-1645. |
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| Publishing Information: | Madison, WI: American Society of Agronomy |
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| # of Pages: | 6 |
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| Keywords: | TIC Keywords: Remote sensing; Agrostis stolonifera; Nutrient deficiency; Fertilization; Nitrogen level; Biomass; Chlorophyll content; Visual evaluation
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| Abstract/Contents: | "Development of a remote sensing system that can reliably identify nutrient deficiencies may reduce time spent sampling turfgrass areas and allow for site-specific applications of fertilizers. The objectives of this research were to evaluate the use of a ground-based remote sensing system and partial least-squares (PLS) regression to predict the N concentration, biomass production, chlorophyll content, and visual quality of creeping bentgrass (Agrostis stolonifera L. 'Penncross') growing under varying N rates, and to compare PLS regression to other vegetative indices. The study consisted of three N treatments (0.0, 12.2, and 24.4 kg ha-1 15 d-1) arranged in a randomized complete block design. Spectral radiance measurements were obtained from plots using a fiber-optic spectrometer to calculate vegetative indices. The PLS regression analysis yielded a strong relationship between actual and predicted N concentration of creeping bentgrass plant tissue during 2002 and 2003 (r2 = 0.95 and 0.71 respectively). However, PLS regression failed to produce a prediction for the chlorophyll concentration. Regressing the normalized vegetation index (NDVI), Stress1 (R706/R760), and Stress2 (R706/R813) ratios against N concentration yielded better results in 2003 when there were distinct differences in N concentration between the N rates. These results indicate that the traditional vegetation indices like NDVI might be better suited for determining the relative N status of turfgrass plants when compared against a well-fertilized control. More research will be required to determine if the PLS regression analysis produces prediction models that are able to specifically identify a particular nutrient deficiency or plant stress, and how the results will vary between grass species." |
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| Language: | English |
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| References: | 32 |
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| See Also: | See also related abstract, "Nitrogen stress level in creeping bentgrass can be detected via remote sensing", 2004 Annual Meeting Abstracts, 2004, p. [1] R=102748 R=102748 |
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| Note: | Tables
Graphs |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Kruse, J. K., N. E. Christians, and M. H. Chaplin. 2006. Remote sensing of Nitrogen stress in creeping bentgrass. Agron. J. 98(6):p. 1640-1645. |
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| DOI: 10.2134/agronj2006.0022 |
| Web URL(s):
https://dl.sciencesocieties.org/publications/aj/articles/98/6/1640
Last checked: 11/02/2016
Access conditions: Item is within a limited-access website
https://dl.sciencesocieties.org/publications/aj/pdfs/98/6/1640
Last checked: 11/04/2016
Requires: PDF Reader
Access conditions: Item is within a limited-access website |
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MSU catalog number: b2212646a |
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