Citation: PENG Dan, CHEN Ming-Yang, SHI Cui-Yi, SU Min, CHEN Jing-Nan, XU Rui. Synchronous Evaluation of Rapeseed Frying Oil Quality Indexes Based on Low-field Nuclear Magnetic Resonance Relaxation Properties Combined With Multiple Linear Regression[J]. Chinese Journal of Analytical Chemistry, ;2023, 51(6): 1042-1050. doi: 10.19756/j.issn.0253-3820.221388 shu

Synchronous Evaluation of Rapeseed Frying Oil Quality Indexes Based on Low-field Nuclear Magnetic Resonance Relaxation Properties Combined With Multiple Linear Regression

College of Food Science and Engineering, Henan University of Technology, Zhengzhou 450001, China

Corresponding author: PENG Dan, pengdantju@163.com
Received Date: 30 July 2022
Revised Date: 24 February 2023

Fund Project: Supported by the Henan Provincial Science and Technology Project (No. 212102110341), the National Natural Science Foundation of China (No. 31801501) and the Henan University of Technology Student Academic and Scientific Innovation Cultivation Project (No. GJXY202213).

As an important ingredient of fried food, the quality of oil is of great significance to product safety and industry development. To explore the feasibility of synchronous evaluation of oil frying quality indexes based on low-field nuclear magnetic resonance (LF-NMR) technology, rapeseed oil was taken as the research object, and the changes of quality indexes as well as the variations on LF-NMR relaxation signals during frying were systematically analyzed. Then, the correlation between the quality indexes and the relaxation properties of rapeseed oil was studied. At last, the synchronous evaluation model for rapeseed oil frying quality indexes was established by LF-NMR relaxation properties combined with multiple linear regression, and the influence of the number of independent variables on the model performance was also investigated. The experimental results showed that the acid value, polar component, p-anisidine value, carbonyl value, viscosity and the absorbance of rapeseed oil increased with the increase of frying time, while the iodine value gradually decreased. During frying, the attenuation rate of the Carr-Purcell-Meiboom-Gill (CPMG) echo attenuation curve of rapeseed oil gradually increased. In addition, the relaxation parameters (T_2w, T₂₁, T₂₂, S₂₂, S₂₃) were significantly related to the frying quality indexes of rapeseed oil (Acid value, polar component, p-anisidine value, carbonyl value, viscosity, absorbance and iodine value) with p<0.05. Moreover, the determination coefficient (R²) of the LF-NMR-based synchronous prediction model for frying quality indexes of rapeseed oil was greater than 0.93, and the relative average deviation (RAD) was less than 0.15. Compared with the univariate model, except p-anisidine value, the RAD and the root mean square error of prediction (RMSEP) value of other indexes were reduced by more than 55%. It could be seen that it was feasible to synchronously detect multiple indicators of oil frying quality based on LF-NMR, and this technique could also provide the theoretical basis and technical support for rapid online monitoring of complex systems.
- Low-field nuclear magnetic resonance,
- Rapeseed oil,
- Quality indexes,
- Synchronous evaluation,
- Relaxation properties
1. [1]
2. [2]
  HUANG C F, LIN Y S, CHIANG Z C, LU S Y, KUO Y H, CHANG S L Y, CHAO P M. J. Nutr. Biochem., 2014, 25(5):549-556.
3. [3]
4. [4]
  KAIMAL A M, DHINGRA M, SINGHAL R S. J. Food Process. Preserv., 2021, 46(1):1-14.
5. [5]
  ZRIBI A, JABEUR H, FLAMINI G, BOUAZIZ M. Int. J. Food Sci. Technol., 2016, 51(7):1594-1603.
6. [6]
  TOUFFET M, PATSIOURA A, ZIAIIFAR A M, EVELEIGH L, VITRAC O. J. Food Eng., 2018, 224:1-16.
7. [7]
  BANSAL G, ZHOU W, BARLOW P J, JOSHI P, NEO F L, LO H L. Food Chem., 2010, 121(2):621-626.
8. [8]
  CHEN W A, CHIU C P, CHENG W C, HSU C K, KUO M I. J. Food Drug Anal., 2013, 21(1):58-65.
9. [9]
  SUN Y, ZHANG M, FAN D. Ultrason. Sonochem., 2019, 51:77-89.
10. [10]
  YANG D, WU G, LU Y, LI P, QI X, ZHANG H, WANG X, JIN Q. Food Control, 2021, 128:108195.
11. [11]
  LI P, YANG X, LEE W J, HUANG F, WANG Y, LI Y. Food Chem., 2021, 335:127638.
12. [12]
  WANG J, LIU C, SUN D. J. Food. Nutr. Res., 2018, 6(7):433-438.
13. [13]
  ZHAO L, ZHANG M, WANG H, MUJUMDAR A S. Food Control, 2022, 133:108599.
14. [14]
15. [15]
16. [16]
17. [17]
18. [18]
19. [19]
20. [20]
21. [21]
22. [22]
  LEONG Y, KER P, JAMALUDIN M, NOMANBHAY S, ISMAIL A, ABDULLAH F, LOOE H, LO C. Sensors, 2018, 18(7):2175.
23. [23]
24. [24]
25. [25]
  WANG C, SU G, WANG X, NIE S. J. Agric. Food Chem., 2019, 67(8):2361-2368.
26. [26]
1. [1]
  Liangsen Zhu , Caiyun Cui , Tao Jing , Shihao Tan , Xianguo Liu , Menglin Yu . Strong and broadband microwave absorption under thin thickness induced by multiple dielectric relaxation and multiple magnetic resonances through the dual nanocrystalline phases in amorphous FeSiBCr flakes. Acta Physico-Chimica Sinica, 2026, 42(9): 100331-0. doi: 10.1016/j.actphy.2026.100331
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19. [19]
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20. [20]
  Ming Guan , Xi Bai , Yuhua Ma , Fang Mi , Weigang Fan , Junjie Guo , Guixin Li , Yingbo Wang , Han Zeng , Jing Zeng , Lu Xiao , Yinping Li , Hong Du , Ya Gao . Exploration and Practice of Multi-School, Multi-Directional Synchronous Classrooms and Smart Teaching for Core Chemistry Courses at Xinjiang Normal University under the MOOC Westward Journey Initiative. University Chemistry, 2025, 40(11): 59-65. doi: 10.12461/PKU.DXHX202412123

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