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Elfadl, E., Reinbrecht, C., Claupein, W.. (1391). Development of near infrared reflectance spectroscopy (NIRS) calibration model for estimation of oil content in a worldwide safflower germplasm collection. , 4(4), 259-270. doi: 10.22069/ijpp.2012.709
E. Elfadl; C. Reinbrecht; W. Claupein. "Development of near infrared reflectance spectroscopy (NIRS) calibration model for estimation of oil content in a worldwide safflower germplasm collection". , 4, 4, 1391, 259-270. doi: 10.22069/ijpp.2012.709
Elfadl, E., Reinbrecht, C., Claupein, W.. (1391). 'Development of near infrared reflectance spectroscopy (NIRS) calibration model for estimation of oil content in a worldwide safflower germplasm collection', , 4(4), pp. 259-270. doi: 10.22069/ijpp.2012.709
Elfadl, E., Reinbrecht, C., Claupein, W.. Development of near infrared reflectance spectroscopy (NIRS) calibration model for estimation of oil content in a worldwide safflower germplasm collection. , 1391; 4(4): 259-270. doi: 10.22069/ijpp.2012.709

Development of near infrared reflectance spectroscopy (NIRS) calibration model for estimation of oil content in a worldwide safflower germplasm collection

International Journal of Plant Production
مقاله 3، دوره 4، شماره 4، دی 2012، صفحه 259-270    اصل مقاله (124.98 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22069/ijpp.2012.709
نویسندگان
E. Elfadl* 1؛ C. Reinbrecht2؛ W. Claupein1
1Institute of Crop Sciences, University of Hohenheim, Fruwirthstr. 23, 70593 Stuttgart, Germany.
2PflanzenzuchtSaKa GbR, Dorfstrasse 39, D-17495, Germany.
چکیده
The development of NIRS calibration model as a rapid, precise, robust, and cost-effective method to estimate oil content in ground seeds of worldwide safflower germplasm collection grown under different agro-climatic conditions was the key objective of this research project. The oil content was measured by accelerated solvent extraction method in a total of 328 samples collected across 2004 (165 samples) and 2005 (163) growing seasons and used as reference values. Two thirds of the measured samples were used for building the calibrations and one third for the validations. Combined and annual calibration and validation models were carried out by NIRCal 4.21 using the partial least squares (PLS) regression. Different data pretreatments such as full multiplicative scatter correction (MSC), first derivative or smoothing way of Savitzky-Golay with a gap of 9 data points were used to improve the calibration models. The optimum PLS factors for developing the best calibration were 12, 10, and 14 for combined model, annual model of 2004 and of 2005, respectively. In combined and annual models, the statistical parameters in calibration model were consistent with the respective parameters in validation model. Coefficient of variation (15.5 to 25.1) demonstrated high variability in calibration and validation models. The standard error of estimation (SEE) and standard error of prediction (SEP) for combined model were 1.40 and 1.43, respectively. Although the quality value (Q-value) of calibration was slightly higher in annual models (0.66 for both), the combined calibration model (0.64) precisely predicted oil content as indicated by higher coefficient of determination (0.90) and RPD (3.2%) compared to annual calibration. The accuracy and precision of the combined calibration model were sufficient to use NIRS as a tool for screening of oil content in a diverse safflower germplasm in the range obtained.
کلیدواژه‌ها
safflower؛ Oil content؛ Near-infrared spectroscopy؛ Calibration؛ validation
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