Rapid Determination of the Oil and Moisture Contents in Camellia gauchowensis Chang and Camellia semiserrata Chi Seeds Kernels by Near-infrared Reflectance Spectroscopy.

Yingzhong Zhang,Jing Wang,Yijuan Huang,Liangbo Zhang,Wu Zeng,Yongquan Li,Jianwei Li,Xuxiao Tang,Mengyu Zhang,Minghuai Wang,Baohua Xu,Qihui Mo,Hong Wu

doi:10.3390/molecules23092332

Abstract

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.

Highlights

Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Institute of Bioresource and Bioenergy, Hunan Academy of Forestry, Changsha 410004, China; Department of Science and Technology, Gaozhou Institute of Forestry, Maoming 525200, China; Department of Science and Technology, Guangning Institute of Forestry, Zhaoqing 526300, China; Department of Science and Technology, Guangdong Province Forestry Science and Technology Extension
The overall spectra of Camellia seeds kernels in different treatment related with oil [26] and at 1450 nm (O–H) with moisture [31]
The raw NIR spectra of non-destruction showed strong absorption bands related with oil and water content

Summary

Introduction

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. 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. 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 ±. The NIRS technique could determine successfully the oil and moisture contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels

Methods

Results

Conclusion