光谱学与光谱分析 |
|
|
|
|
|
Online Determination of pH in Fresh Pork by Visible/Near-Infrared Spectroscopy |
LIAO Yi-tao, FAN Yu-xia,WU Xue-qian,CHENG Fang* |
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China |
|
|
Abstract The present research was focused on determination of the pH value online by visible and near-infrared spectroscopy. In the part of data gathering, fresh pork longissimus dorsi was moving at the constant velocity of 0.25 m·s-1 on the conveyor belt, and the visible and near-infrared diffuse reflectance spectrum (350-1 000 nm) was captured. In the part of data processing, band of 510-980 nm of the spectra was chosen to calibrate reflex distance, then to set up online detection model of pH value in fresh pork by partial least squares regression (PLSR). Kennard-stone algorithm was applied to divide the samples to the calibration set and validation set. The performances of several PLSR models employing various preprocessing methods including multiple scatter correction, derivative and both of them combined were compared. Further, the best performance model was optimized by interval PLSR to decrease the modeling variables of wavelength. The results indicated that the PLSR model based on preprocessing of multiple scatter correction (MSC) combined with first derivative gave the best performance with 0.905 of the correlation coefficient for validation set and 0.051 of the root of mean square errors for validation set. For the best PLSR model performance, the correlation coefficient of validation set increased to 0.926 and the root of mean square errors for validation set to 0.045 in the optimization interval PLSR model. However, only half of variables were used. The research demonstrates that using visible and near-infrared spectroscopy to determine fresh pork pH online is feasible.
|
Received: 2009-03-29
Accepted: 2009-06-30
|
|
Corresponding Authors:
CHENG Fang
E-mail: fcheng@zju.edu.cn
|
|
[1] Brewer M S, Novakofski J, Freise K. Meat Science, 2006,72(4): 596. [2] Andrews B S, Hutchison S, Unruh J A, et al. Journal of Muscle Foods, 2007,18(4): 401. [3] Van Laack R L, Stevens S G, Stalder K J. Journal of Animal Science, 2001,79(2): 392. [4] Bryhni E A, Byrne D V, Rodbotten M, et al. Meat Science, 2003,65(2): 737. [5] Knox B L, Van Laack R L J M, Davidson P M. Journal of Food Science, 2008,73(3): 104. [6] Joseph K, John K, David L. Meat Processing Improving Quality. Cambridge: Woodhead Publishing Ltd, 2002. 157. [7] Woodcock T, Downey G, O’Donnell C P. Journal of Near Infrared Spectroscopy, 2008, 16(1): 1. [8] Del Moral F G, Guillen A, Del Moral L G, et al. Journal of Food Engineering, 2009,90(4): 540. [9] Damez J L, Clerjon S. Meat Science, 2008,80(1): 132. [10] Anderson J R, Borggaard C, Rasmussen A J, et al. Meat Science, 1999,53(2): 135. [11] Josell A, Martinsson L, Borggaard C, et al. Meat Science, 2000,55(3): 273. [12] Chan D E, Walker P N, Mills E W. Transactions of the ASABE, 2002,45(5): 1519. [13] Savenije B, Geesink G H, Vander Palen J G P, et al. Meat Science, 2006,73(1): 181. [14] Kennard R W, Stone L A. Technometrics, 1969,11(1): 137. [15] Daszykowski M, Walczak B, Massart D L. Analytica Chimica Acta, 2002,468(1): 91. [16] Geesink G H, Schreutelkamp F H, Frankhuizen R, et al. Meat Science, 2003,65(1): 661. [17] Geladi P, Macdougall D, Martens H. Applied Spectroscopy, 1985,39(3): 491. [18] LU Wan-zhen, YUAN Hong-fu, XU Guang-tong, et al(陆婉珍,袁洪福,徐广通,等). Modern Near Infrared Spectroscopy Analytical Technology(现代近红外光谱分析技术). Beijing: China Petrochemical Press(北京:中国石化出版社), 2006. 33. [19] Wold S, Sjostrom M, Eriksson L. Chemometrics and Intelligent Laboratory Systems, 2001,58(2): 109. [20] Leardi R, Norgaard L. Journal of Chemometrics, 2004,18(11): 486. [21] Norgaard L, Saudland A, Wagner J, et al. Applied Spectroscopy, 2000,54(3): 413.
|
[1] |
LI Yu1, ZHANG Ke-can1, PENG Li-juan2*, ZHU Zheng-liang1, HE Liang1*. Simultaneous Detection of Glucose and Xylose in Tobacco by Using Partial Least Squares Assisted UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 103-110. |
[2] |
JIA Hao1, 3, 4, ZHANG Wei-fang1, 3, LEI Jing-wei1, 3*, LI Ying-ying1, 3, YANG Chun-jing2, 3*, XIE Cai-xia1, 3, GONG Hai-yan1, 3, DING Xin-yu1, YAO Tian-yi1. Study on Infrared Fingerprint of the Classical Famous
Prescription Yiguanjian[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3202-3210. |
[3] |
WU Yong-qing1, 2, TANG Na1, HUANG Lu-yao1, CUI Yu-tong1, ZHANG Bo1, GUO Bo-li1, ZHANG Ying-quan1*. Model Construction for Detecting Water Absorption in Wheat Flour Using Vis-NIR Spectroscopy and Combined With Multivariate Statistical #br#
Analyses[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2825-2831. |
[4] |
GUO Yuan1, 2, HUANG Yi-xiang3, 4, HUANG Chang-ping3, 4, SUN Xue-jian3, 5, LUAN Qing-xian1*, ZHANG Li-fu3, 5*. Analysis of Blood Oxygen Content in Gingival Tissue of Patients With
Periodontitis Based on Visible and Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2563-2567. |
[5] |
LUO Dong-jie, WANG Meng, ZHANG Xiao-shuan, XIAO Xin-qing*. Vis/NIR Based Spectral Sensing for SSC of Table Grapes[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2146-2152. |
[6] |
WANG Bin1, 2, ZHENG Shao-feng2, GAN Jiu-lin1, LIU Shu3, LI Wei-cai2, YANG Zhong-min1, SONG Wu-yuan4*. Plastic Reference Material (PRM) Combined With Partial Least Square (PLS) in Laser-Induced Breakdown Spectroscopy (LIBS) in the Field of Quantitative Elemental Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2124-2131. |
[7] |
CHENG Xiao-xiang1, WU Na2, LIU Wei2*, WANG Ke-qing2, LI Chen-yuan1, CHEN Kun-long1, LI Yan-xiang1*. Research on Quantitative Model of Corrosion Products of Iron Artefacts Based on Raman Spectroscopic Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2166-2173. |
[8] |
ZHANG Mei-zhi1, ZHANG Ning1, 2, QIAO Cong1, XU Huang-rong2, GAO Bo2, MENG Qing-yang2, YU Wei-xing2*. High-Efficient and Accurate Testing of Egg Freshness Based on
IPLS-XGBoost Algorithm and VIS-NIR Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1711-1718. |
[9] |
YAN Zhong-wei1, 2, 3, TIAN Xi2, 3, ZHANG Yi-fei2, 3, LI Lian-jie2, 3, LIU San-qing1, 2, 3, HUANG Wen-qian2, 3*. Online Detection of Soluble Solids Content in Different Parts of
Watermelons Based on Full Transmission Near Infrared
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1800-1808. |
[10] |
XU Wei-xin, XIA Jing-jing, WEI Yun, CHEN Yue-yao, MAO Xin-ran, MIN Shun-geng*, XIONG Yan-mei*. Rapid Determination of Oxytetracycline Hydrochloride Illegally Added in Cattle Premix by ATR-FTIR[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 842-847. |
[11] |
LI Zi-yi1, LI Rui-lan1, LI Can-lin1, WANG Ke-ru2, FAN Jiu-yu3, GU Rui1*. Identification of Tibetan Medicine Zhaxun by Infrared Spectroscopy
Combined With Chemometrics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 526-532. |
[12] |
WANG Chao1, LIU Yan1*, XIA Zhen-zhen2, WANG Qiao1, DUAN Shuo1. Fast Evaluation of Freshness in Crayfish (Prokaryophyllus clarkii) Cased on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 156-161. |
[13] |
ZHAO Jian-ming, YANG Chang-bao, HAN Li-guo*, ZHU Meng-yao. The Inversion of Muscovite Content Based on Spectral Absorption
Characteristics of Rocks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 220-224. |
[14] |
LI Qing-bo1, BI Zhi-qi1, CUI Hou-xin2, LANG Jia-ye2, SHEN Zhong-kai2. Detection of Total Organic Carbon in Surface Water Based on UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3423-3427. |
[15] |
OUYANG Ai-guo, LIN Tong-zheng, HU Jun, YU Bin, LIU Yan-de. Optimization of Hardness Testing Model of High-Speed Iron Wheel by Laser-Induced Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3109-3115. |
|
|
|
|