Rapid Determination of the Oil and Moisture Contents in Camellia gauchowensis Chang and Camellia semiserrata Chi Seeds Kernels by Near-infrared Reflectance Spectroscopy
| Autor: | Minghuai Wang, Baohua Xu, Liangbo Zhang, Yingzhong Zhang, Jianwei Li, Mengyu Zhang, Xuxiao Tang, Jing Wang, Hong Wu, Yijuan Huang, Qihui Mo, Wu Zeng, Yongquan Li |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Quality Control
Pharmaceutical Science Camellia gauchowensis 01 natural sciences Article Analytical Chemistry near infrared reflectance spectroscopy lcsh:QD241-441 0404 agricultural biotechnology lcsh:Organic chemistry Drug Discovery Partial least squares regression Plant Oils Physical and Theoretical Chemistry Least-Squares Analysis Water content Mathematics moisture content Principal Component Analysis Spectroscopy Near-Infrared Moisture 010401 analytical chemistry Organic Chemistry Water Camellia seeds kernel Camellia 04 agricultural and veterinary sciences 040401 food science plant_sciences 0104 chemical sciences Horticulture Chemistry (miscellaneous) Camellia semiserrata Principal component analysis Seeds Molecular Medicine oil content Near infrared reflectance spectroscopy |
| Zdroj: | Molecules Volume 23 Issue 9 Molecules : A Journal of Synthetic Chemistry and Natural Product Chemistry Molecules, Vol 23, Iss 9, p 2332 (2018) |
| ISSN: | 1420-3049 |
| DOI: | 10.3390/molecules23092332 |
| Popis: | A fast and effective determination method of different species of vegetable seeds oil is vital in the plant oil industry. The near-infrared reflectance spectroscopy (NIRS) method was developed in this study to analyze the oil and moisture contents of Camellia gauchowensis Chang and C. semiserrata Chi seeds kernels. Calibration and validation models were established using principal component analysis (PCA) and partial least squares (PLS) regression methods. In the prediction models of NIRS, the levels of accuracy obtained were sufficient for C. gauchowensis Chang and C. semiserrata Chi, the correlation coefficients of which for oil were 0.98 and 0.95, respectively, and those for moisture were 0.92 and 0.89, respectively. The near infrared spectrum of crush seeds kernels was more precise compared to intact kernels. Based on the calibration models of the two Camellia species, the NIRS predictive oil contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels were 48.71 ± 8.94% and 58.37 ± 7.39%, and the NIRS predictive moisture contents were 4.39 ± 1.08% and 3.49 ± 0.71%, respectively. The NIRS technique could determine successfully the oil and moisture contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|