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| Web URL(s): | https://www.researchgate.net/publication/265598847
Last checked: 03/07/2016 |
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| Publication Type:
| Refereed |
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| Author(s): | Keskin, M.;
Han, Y. J.;
Dodd, R. B.;
Khalilian, A. |
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| Author Affiliation: | Keskin: Assistant Professor, Department of Agricultural Machinery, Faculty of Agriculture, Mustafa Kemal University, Hatay, Turkey; Han, Dodd and Khalilian: Professors, Department of Agricultural and Biological Engineering, Clemson University, Clemson, South Carolina |
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| Title: | Reflectance-based sensor to predict visual quality ratings of turfgrass plots |
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| Section: | Information & electrical technologies
Other records with the "Information & electrical technologies" Section
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| Source: | Applied Engineering in Agriculture. Vol. 24, No. 6, 2008, p. 855-860. |
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| Publishing Information: | St. Joseph, MI: American Society of Agricultural Engineers |
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| # of Pages: | 6 |
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| Keywords: | TIC Keywords: Aesthetic values; Cynodon; Evaluative methods; Poa; Quality evaluation; Spectral reflectance; Turfgrass quality; Visual evaluation
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| Abstract/Contents: | "Turfgrass quality is visually evaluated by human assessors based on a scale of 1 to 9. This evaluation practice is subjective and does not provide accurate and reproducible measure of the turf quality. The aim of this research was to design a portable optical sensor to predict the quality ratings of turfgrass research plots from spectral reflectance. Reflectance data were collected using a dual spectroradiometer covering a spectrum of 350-1050 nm from bermudagrass and bluegrass research plots. Two different regression methods, Multiple Linear Regression (MLR) and Partial Least Squares Regression (PLSR), were used and compared. Two wavelength bands centered at 680 nm (Red) and 780 nm (NIR) were identified since these bands carry useful information in the prediction of turfgrass visual quality. The average Standard Error of Cross Validation (SECV) was found to be about 0.76 and 0.88 by using the model with Red and NIR bands for bermudagrass and bluegrass data sets, respectively. A simple prototype sensor using the two identified bands was fabricated and tested. The prototype sensor predicted the visual quality ratings as well as the spectroradiometer with a SECV of about 0.57 using two bands." |
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| Language: | English |
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| References: | 16 |
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| Note: | Pictures, color
Tables
Graphs |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Keskin, M., Y. J. Han, R. B. Dodd, and A. Khalilian. 2008. Reflectance-based sensor to predict visual quality ratings of turfgrass plots. Appl. Eng. Agric. 24(6):p. 855-860. |
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| Web URL(s):
https://www.researchgate.net/publication/265598847
Last checked: 03/07/2016 |
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MSU catalog number: b3269147 |
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