| 光谱学与光谱分析 |
|
|
|
|
|
| Study on Component Detection of Cheese Wrapped by Polyethylene Film Based on NIRS |
| PI Fu-wei1,WANG Jia-hua1,SUN Xu-dong2,HAN Dong-hai1* |
1. College of Food Science and Nutrition Engineering, China Agricultural University, Beijing 100083, China
2. College of Engineering, China Agricultural University, Beijing 100083，China |
|
|
|
|
Abstract The possibility of direct determination of fat and protein of wrapped cheese by near infrared spectroscopy was studied. The influences of polyethylene film on the spectra were discussed in order to detect the components of wrapped cheese. And the influences were eliminated using Norris derivation filter pretreatment means. The models for fat and protein of wrapped cheese were calibrated by partial least squares regression (PLS) following eliminating outline, spectral pretreatment, and PLS factors optimization. The best models gave standard errors for calibration of 0.240 and 0.355, standard errors for prediction of 0.326 and 0.219, and correlation coefficients of 0.928 and 0.952 for fat and protein of wrapped cheese, respectively. The results showed no difference from those by non-wrapped cheese’s models, and were better than wrapped cheese’s models without Norris derivation filter pretreatment. Based on the results, it was concluded that near infrared spectroscopy is a reliable, accurate and fast method for non-invasive measurement of wrapped cheese fat and protein.
|
|
Received: 2007-08-08
Accepted: 2007-11-18
|
|
|
|
Corresponding Authors:
HAN Dong-hai
E-mail: caundt@cau.edu.cn
|
|
[1] Chen Jie Yu, Iyo C, Terada F, et al. Journal of Near Infrared Spectroscopy,2002, 10(4): 301.
[2] LIU Rong, CHEN Wen-liang, XU Ke-xin, et al(刘 蓉, 陈文亮, 徐可欣, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2005,25(2): 207.
[3] HAN Dong-hai, LU Chao, LIU Yi, et al(韩东海，鲁 超，刘 毅, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2007,27(3): 465.
[4] Tsenkova R, Atanassova S, Kawano S. Journal of Animal Science,2001, 79(10): 2550.
[5] Pravdova V, Walczak B, Massart D L, et al. Analytica Chimica Acta,2001, 450(1-2): 131.
[6] HAN Dong-hai, LU Chao, LIU Yi(韩东海，鲁 超，刘 毅). Dairy Industry Review(乳业导报)，2005, 8: 158.
[7] Karoui R, Pillonel L, Schaller E, et al. Food Chemistry,2007, 101(3)：1121.
[8] Karoui R, Mouazen A M, ric D, et al. International Dairy Journal,2006, 16(10)：1211.
[9] Skeie S, Feten G, Almoy T. International Dairy Journal,2006, 16(3): 236.
[10] Cattaneo T M P, Giardina C, Sinelli N. International Dairy Journal,2005, 15(9): 693.
[11] Curda L, Kukackova O. Journal of Food Engineering,2004, 61(3): 557.
[12] Lambert K, Sorensen, Rita J. International Dairy Journal, 1998, 8(10-11)：863.
[13] Adamopoulos Konstantinos G, Athanasia M Goula, Heracles J. Journal of Food Composition and Analysis,2001, 14: 431.
[14] Health Ministry of the People’s Republic of China(中华人民共和国卫生部编). Methods of Food Hygienic Analysis-Physical and Chemistry Section(1), GB/T 5009.1～5009.100—2003.(中华人民共和国国家标准(食品卫生检验方法, 理化部分(1))). Beijing: Standard Press of China(北京：中国标准出版社),2004.
[15] LU Chao, HAN Dong-hai. Journal of Near Infrared Spectroscopy,2005, 13：139.
[16] CHU Xiao-li, YUAN Hong-fu, LU Wan-zhen(褚小立，袁洪福，陆婉珍). Progress in Chemistry(化学进展),2004, 16(4): 28. |
| [1] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
| [2] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [3] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
| [4] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
| [5] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
| [6] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
| [7] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
| [8] |
ZHANG Shu-fang1, LEI Lei2, LEI Shun-xin2, TAN Xue-cai1, LIU Shao-gang1, YAN Jun1*. Traceability of Geographical Origin of Jasmine Based on Near
Infrared Diffuse Reflectance Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3389-3395. |
| [9] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
| [10] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
| [11] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
| [12] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
| [13] |
HUANG Hua1, LIU Ya2, KUERBANGULI·Dulikun1, ZENG Fan-lin1, MAYIRAN·Maimaiti1, AWAGULI·Maimaiti1, MAIDINUERHAN·Aizezi1, GUO Jun-xian3*. Ensemble Learning Model Incorporating Fractional Differential and
PIMP-RF Algorithm to Predict Soluble Solids Content of Apples
During Maturing Period[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3059-3066. |
| [14] |
CHEN Jia-wei1, 2, ZHOU De-qiang1, 2*, CUI Chen-hao3, REN Zhi-jun1, ZUO Wen-juan1. Prediction Model of Farinograph Characteristics of Wheat Flour Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3089-3097. |
| [15] |
GUO Ge1, 3, 4, ZHANG Meng-ling3, 4, GONG Zhi-jie3, 4, ZHANG Shi-zhuang3, 4, WANG Xiao-yu2, 5, 6*, ZHOU Zhong-hua1*, YANG Yu2, 5, 6, XIE Guang-hui3, 4. Construction of Biomass Ash Content Model Based on Near-Infrared
Spectroscopy and Complex Sample Set Partitioning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3143-3149. |
|
|
|
|
