不同贮藏温度下滩羊肉pH值的近红外高光谱动力学模型建立
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摘要
为了比较4℃、15℃两种贮藏温度下滩羊肉pH值的变化,优选出滩羊肉贮藏期间的最优模型,采用pH酸度计测量样本pH值,建立两种贮藏温度下传统动力学的零级和一级模型;应用近红外(900～1 700 nm)高光谱成像采集两种贮藏温度下滩羊肉的光谱数据,剔除异常值后进行光谱预处理;使用连续投影算法(SPA)提取特征波长,建立全波段和特征波长的偏最小二乘(PLSR)预测模型;对比分析得到的最优光谱模型与动力学模型相结合,确定滩羊肉光谱动力学模型。结果表明,4℃和15℃的传统动力学模型的相关系数分别为0.502和0.912;4℃下原始光谱经PLSR建模后效果最优,相关系数R_c为0.821,R_p为0.863,15℃经SG-S(3,7)+De-trending(4)预处理后经PLSR建模效果最优,相关系数R_c为0.876,R_p为0.819。因此,高光谱结合传统动力学的模型检测羊肉pH值的方法是可行的,该模型可以预测15℃下滩羊肉的贮藏期。
In order to compare the change of the pH value of mutton at 4 ℃ and 15 ℃ storage temperature, the optimal model of mutton during the storage period was optimized. The pH values of the samples were measured by pH acidity meter, the zero-order and first-order models of the traditional kinetics were established under two storage temperatures. The spectral data of mutton at two storage temperatures were acquired by near-infrared hyperspectral imaging(900-1 700 nm), and the spectral pretreatment was carried out after removing outlier. The feature wavelength is extracted by successive projection algorithm(SPA), and the partial least squares(PLSR) prediction model of full wavelength and feature wavelength is established. The optimal spectral model was combined with the kinetic model, and the spectral kinetic model of mutton was determined. The results show that the correlation coefficients of the conventional kinetic models at 4 ℃ and 15 ℃ were 0.502 and 0.912, respectively. The original spectrum was the best after modeling by PLSR at 4 ℃, and the correlation coefficient R_c was 0.821, R_p was 0.863. After the SG-S(3,7)+De-trending(4) pretreatment, the model was optimized by PLSR at 15 ℃. The correlation coefficient R_c was 0.876 and R_p was 0.819. It is feasible to detect the pH value of mutton by hyperspectral and traditional kinetic model, and the model can predict the storage period of mutton at 15 ℃.
In order to compare the change of the pH value of mutton at 4 ℃ and 15 ℃ storage temperature, the optimal model of mutton during the storage period was optimized. The pH values of the samples were measured by pH acidity meter, the zero-order and first-order models of the traditional kinetics were established under two storage temperatures. The spectral data of mutton at two storage temperatures were acquired by near-infrared hyperspectral imaging(900-1 700 nm), and the spectral pretreatment was carried out after removing outlier. The feature wavelength is extracted by successive projection algorithm(SPA), and the partial least squares(PLSR) prediction model of full wavelength and feature wavelength is established. The optimal spectral model was combined with the kinetic model, and the spectral kinetic model of mutton was determined. The results show that the correlation coefficients of the conventional kinetic models at 4 ℃ and 15 ℃ were 0.502 and 0.912, respectively. The original spectrum was the best after modeling by PLSR at 4 ℃, and the correlation coefficient R_c was 0.821, R_p was 0.863. After the SG-S(3,7)+De-trending(4) pretreatment, the model was optimized by PLSR at 15 ℃. The correlation coefficient R_c was 0.876 and R_p was 0.819. It is feasible to detect the pH value of mutton by hyperspectral and traditional kinetic model, and the model can predict the storage period of mutton at 15 ℃.
引文
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[13] JIA B B,YOON S C,ZHUANG H,et al.. Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imaging [J]. J. Food Eng., 2017,208:57-65.
[14] ELMASRY G,SUN D W,ALLEN P. Near-infrared hyperspectral imaging for predicting colour,pH and tenderness of fresh beef [J]. J. Food Eng., 2012,110(1):127-140.
[15] IQBAL A,SUN D W,ALLEN P. Prediction of moisture,color and pH in cooked,pre-sliced turkey hams by NIR hyperspectral imaging system [J]. J. Food Eng., 2013,117(1):42-51.
[16] 朱荣光,姚雪东,段宏伟,等. 羊肉挥发性盐基氮的高光谱图像快速检测研究 [J]. 光谱学与光谱分析, 2016,36(3):806-810. ZHU R G,YAO X D,DUAN H W,et al.. Study on the rapid evaluation of total volatile basic nitrogen (TVB-N) of mutton by hyperspectral imaging technique [J]. Spectrosc. Spectr. Anal., 2016,36(3):806-810. (in Chinese)
[17] 徐霞,成芳,应义斌. 近红外光谱技术在肉品检测中的应用和研究进展 [J]. 光谱学与光谱分析, 2009,29(7):1876-1880. XU X,CHENG F,YING Y B. Application and recent development of research on near-infrared spectroscopy for meat quality evaluation [J]. Spectrosc. Spectr. Anal., 2009,29(7):1876-1880. (in Chinese)
[18] YANG D,HE D D,LU A X,et al.. Combination of spectral and textural information of hyperspectral imaging for the prediction of the moisture content and storage time of cooked beef [J]. Infrared Phys. Technol., 2017,83:206-216.
[19] LI X,ZHANG Y,LI Z,et al.. The effect of temperature in the range of -0.8 to 4 ℃ on lamb meat color stability [J]. Meat Sci., 2017,134:28-33.
[20] DíAZ M T,PéREZ C,SáNCHEZ C I,et al.. Feeding microalgae increases omega 3 fatty acids of fat deposits and muscles in light lambs [J]. J. Food Compos. Anal., 2017,56:115-123.
[21] CRICHTON S O J,KIRCHNER S M,PORLEY V,et al.. Classification of organic beef freshness using VNIR hyperspectral imaging [J]. Meat Sci., 2017,129:20-27.
[22] SIRIPATRAWAN U. Hyperspectral imaging for rapid evaluation and visualization of quality deterioration index of vacuum packaged dry-cured sausages [J]. Sens. Actuators B, 2018,254:1025-1032.
[23] SUKTANARAK S,TEERACHAICHAYUT S. Non-destructive quality assessment of hens' eggs using hyperspectral images [J]. J. Food Eng., 2017,215:97-103.
[24] YANG D,LU A X,REN D,et al.. Rapid determination of biogenic amines in cooked beef using hyperspectral imaging with sparse representation algorithm [J]. Infrared Phys. Technol., 2017,86:23-34.
[25] 谷芳,曾智伟,郭康权,等. 基于近红外光谱的猪肉细菌菌落总数的动力学模型 [J]. 中国农业大学学报, 2013,18(3):152-156. GU F,ZENG Z W,GUO K Q,et al.. Dynamic model of bacterial colonies on pork based on near infrared spectroscopy [J]. J. China Agric. Univ., 2013,18(3):152-156. (in Chinese)
[2] 马世榜,汤修映,徐杨,等. 可见/近红外光谱结合遗传算法无损检测牛肉pH值 [J]. 农业工程学报, 2012,28(18):263-268. MA S B,TANG X Y,XU Y,et al.. Nondestructive determination of pH value in beef using visible/near-infrared spectroscopy and genetic algorithm [J]. Chin. J. Agric. Eng., 2012,28(18):263-268. (in Chinese)
[3] CRAIGIE C R,JOHNSON P L,SHORTEN P R,et al.. Application of Hyperspectral imaging to predict the pH,intramuscular fatty acid content and composition of lamb M. longissimus lumborum at 24 h post mortem [J]. Meat Sci., 2017,132:19-28.
[4] CRICHTON S O J,KIRCHNER S M,PORLEY V,et al.. High pH thresholding of beef with VNIR hyperspectral imaging [J]. Meat Sci., 2017,134:14-17.
[5] HUANG L,ZHAO J W,CHEN Q S,et al.. Rapid detection of total viable count (TVC) in pork meat by hyperspectral imaging [J]. Food Res. Int., 2013,54(1):821-828.
[6] 邹毅峰,谢如鹤,刘广海. 生鲜食品的品质动力学模型研究综述 [J]. 包装工程, 2015,36(15):9-15. ZOU Y F,XIE R H,LIU G H. Review on quality kinetic model for fresh food [J]. Packag. Eng., 2015,36(15):9-15. (in Chinese)
[7] 陈晓宇,朱志强,张小栓,等. 食品货架期预测研究进展与趋势 [J]. 农业机械学报, 2015,46(8):192-199. CHEN X Y,ZHU Z Q,ZHANG X S,et al.. Research progress and trend of food shelf life prediction [J]. Trans. Chin. Soc. Agric. Mach., 2015,46(8):192-199. (in Chinese)
[8] 柴春祥. 猪肉品质变化的动力学模型 [J]. 食品与发酵工业, 2004,30(6):10-12. CHAI C X. Research on the kinetics model of pork quality [J]. Food Ferment. Ind., 2004,30(6):10-12. (in Chinese)
[9] 丁婷,李婷婷,励建荣,等. 冷藏三文鱼片微生物生长动力学模型适用性分析及货架期模型的建立 [J]. 中国食品学报, 2015,15(5):63-73. DING T,LI T T,LI J R,et al.. Applicability analysis of microbial growth dynamics models and establishment of shelf-life model for salmon slices duing the cold storage [J]. J. Chin. Inst. Food Sci. Technol., 2015,15(5):63-73. (in Chinese)
[10] FENG C H,MAKINO Y,OSHITA S,et al.. Hyperspectral imaging and multispectral imaging as the novel techniques for detecting defects in raw and processed meat products:current state-of-the-art research advances [J]. Food Control, 2018,84:165-176.
[11] 冯愈钦,吴龙国,何建国,等. 基于高光谱成像技术的长枣不同保藏温度的可溶性固形物含量检测方法 [J]. 发光学报, 2016,37(8):1014-1022. FENG Y Q,WU L G,HE J G,et al.. Detection method of soluble solid of jujube at different preservative temperature based on hyper-spectral imaging technology [J]. Chin. J. Lumin., 2016,37(8):1014-1022. (in Chinese)
[12] 张雷蕾,李永玉,彭彦昆,等. 基于高光谱成像技术的猪肉新鲜度评价 [J]. 农业工程学报, 2012,28(7):254-259. ZHANG L L,LI Y Y,PENG Y K,et al.. Determination of pork freshness attributes by hyperspectral imaging technique [J]. Trans. Chin. Soc. Agric. Eng., 2012,28(7):254-259. (in Chinese)
[13] JIA B B,YOON S C,ZHUANG H,et al.. Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imaging [J]. J. Food Eng., 2017,208:57-65.
[14] ELMASRY G,SUN D W,ALLEN P. Near-infrared hyperspectral imaging for predicting colour,pH and tenderness of fresh beef [J]. J. Food Eng., 2012,110(1):127-140.
[15] IQBAL A,SUN D W,ALLEN P. Prediction of moisture,color and pH in cooked,pre-sliced turkey hams by NIR hyperspectral imaging system [J]. J. Food Eng., 2013,117(1):42-51.
[16] 朱荣光,姚雪东,段宏伟,等. 羊肉挥发性盐基氮的高光谱图像快速检测研究 [J]. 光谱学与光谱分析, 2016,36(3):806-810. ZHU R G,YAO X D,DUAN H W,et al.. Study on the rapid evaluation of total volatile basic nitrogen (TVB-N) of mutton by hyperspectral imaging technique [J]. Spectrosc. Spectr. Anal., 2016,36(3):806-810. (in Chinese)
[17] 徐霞,成芳,应义斌. 近红外光谱技术在肉品检测中的应用和研究进展 [J]. 光谱学与光谱分析, 2009,29(7):1876-1880. XU X,CHENG F,YING Y B. Application and recent development of research on near-infrared spectroscopy for meat quality evaluation [J]. Spectrosc. Spectr. Anal., 2009,29(7):1876-1880. (in Chinese)
[18] YANG D,HE D D,LU A X,et al.. Combination of spectral and textural information of hyperspectral imaging for the prediction of the moisture content and storage time of cooked beef [J]. Infrared Phys. Technol., 2017,83:206-216.
[19] LI X,ZHANG Y,LI Z,et al.. The effect of temperature in the range of -0.8 to 4 ℃ on lamb meat color stability [J]. Meat Sci., 2017,134:28-33.
[20] DíAZ M T,PéREZ C,SáNCHEZ C I,et al.. Feeding microalgae increases omega 3 fatty acids of fat deposits and muscles in light lambs [J]. J. Food Compos. Anal., 2017,56:115-123.
[21] CRICHTON S O J,KIRCHNER S M,PORLEY V,et al.. Classification of organic beef freshness using VNIR hyperspectral imaging [J]. Meat Sci., 2017,129:20-27.
[22] SIRIPATRAWAN U. Hyperspectral imaging for rapid evaluation and visualization of quality deterioration index of vacuum packaged dry-cured sausages [J]. Sens. Actuators B, 2018,254:1025-1032.
[23] SUKTANARAK S,TEERACHAICHAYUT S. Non-destructive quality assessment of hens' eggs using hyperspectral images [J]. J. Food Eng., 2017,215:97-103.
[24] YANG D,LU A X,REN D,et al.. Rapid determination of biogenic amines in cooked beef using hyperspectral imaging with sparse representation algorithm [J]. Infrared Phys. Technol., 2017,86:23-34.
[25] 谷芳,曾智伟,郭康权,等. 基于近红外光谱的猪肉细菌菌落总数的动力学模型 [J]. 中国农业大学学报, 2013,18(3):152-156. GU F,ZENG Z W,GUO K Q,et al.. Dynamic model of bacterial colonies on pork based on near infrared spectroscopy [J]. J. China Agric. Univ., 2013,18(3):152-156. (in Chinese)
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