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| Web URL(s): | http://img.kisti.re.kr/soc_img/society//tsk/JDHHBF/2009/v23n1/JDHHBF_2009_v23n1_77.pdf
Last checked: 01/28/2013
Requires: PDF Reader |
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| Publication Type:
| Refereed |
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| Author(s): | Cha, Jung-Hoon;
Kim, Kyung-Duck;
Park, Dae-Sup |
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| Author Affiliation: | Turfgrass & Environment Research Institute, Samsung Everland Inc., Gunpo, Korea |
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| Title: | Prediction from linear regression equation for nitrogen content measurement in bentgrasses leaves using Near Infrared Reflectance Spectroscopy |
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| Source: | Korean Journal of Turfgrass Science. Vol. 23, No. 1, 2009, p. 77-90. |
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| Publishing Information: | Korea: Turfgrass Society of Korea |
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| # of Pages: | 14 |
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| Keywords: | TIC Keywords: Agrostis stolonifera; Evaluative methods; Models; Near-infrared reflectance spectroscopy; Nutrient concentration
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| Cultivar Names: | CY2 |
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| Abstract/Contents: | "Near Infrared Reflectance Spectroscopy(NIRS) is a quick, accurate, and non-destructive method to measure multiple nutrient components in plant leaves. This study was to acquire a liner regression equation by evaluating the nutrient contents of 'CY2' creeping bentgrass rapidly and accurately using NIRS. In particular, nitrogen fertility is a primary element to keep maintaining good quality of turfgrass. Nitrogen, moisture, carbohydrate, and starch were assessed and analyzed from 'CY2' creeping bentgrass clippings. A linear regression equation was obtained from accessing NIRS values from NIR spectrophotometer(NIR system, Model XDS, XM-1100 series, FOSS, Sweden) programmed with WinISI III project manager v1.50e and ISIscan® (Infrasoft International) and calibrated with laboratory values via chemical analysis from an authorized institute. The equation was formulated as MPLS(modified partial least squares) analyzing laboratory values and mathematically pre-treated spectra. The accuracy of the acquired equation was confirmed with SEP(standard error of prediction), which indicated as correlation coefficient(r2) and prediction error of sample unacquainted, followed by the verification of model equation of real values and these monitoring results. As results of monitoring, r2 of nitrogen, moisture, and carbohydrate in 'CY2' creeping bentgrass was 0.840, 0.904, and 0.944, respectively. SEP was 0.066, 1.868, and 0.601, respectively. After outlier treatment, r2 was 0.892, 0.925, and 0.971, while SEP was 0.052, 1.577, and 0.394, respectively, which totally showed a high correlation. However, r2 of starch was 0.464, which appeared a low correlation. Thereof, the verified equation appearing higher r2 of nitrogen, moisture, and carbohydrate showed its higher accuracy of prediction model, which finally could be put into practical use for turf management system." |
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| Language: | English |
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| References: | 26 |
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| Note: | Abstract also appears in Korean
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Cha, J.-H., K.-D. Kim, and D.-S. Park. 2009. Prediction from linear regression equation for nitrogen content measurement in bentgrasses leaves using Near Infrared Reflectance Spectroscopy. Korean Journal of Turfgrass Science. 23(1):p. 77-90. |
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| Web URL(s):
http://img.kisti.re.kr/soc_img/society//tsk/JDHHBF/2009/v23n1/JDHHBF_2009_v23n1_77.pdf
Last checked: 01/28/2013
Requires: PDF Reader |
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MSU catalog number: b5472572a |
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