扩展青霉和展青霉素的近红外检测技术研究
|
摘要
展青霉素是一种神经毒性真菌毒素,广泛存在于苹果浓缩汁中。扩展青霉是苹果中主要的展青霉素产生菌。开发快速简便的扩展青霉和展青霉素检测技术有助于及时控制产品中展青霉素的水平。近红外光谱检测法具有对样品无损、速度快、重现性好等优点,适用于在线检测。为了开发扩展青霉和展青霉素的近红外检测技术,论文研究了近红外光谱分析技术在纯培养、单菌种污染苹果、多菌种污染苹果及不同污染深度时对扩展青霉的定性定量检测特性,以及其对水溶液、鲜榨苹果汁和浓缩苹果汁中展青霉素的定性定量检测特性:确定了近红外光谱法检测扩展青霉和展青霉素的条件与方法。获得以下主要研究结果:
(1)平皿纯培养的条件下,利用全谱区信息就能有效地将扩展青霉与其它苹果致腐菌区分开来,对数据进行矢量归一化法+一阶导数法处理以后,区分效果更好。在孢子悬浮液和苹果污染体系,需要对数据进行矢量归一化法+一阶导数法处理,选取5883～5342 cm~(-1),4579～4324-cm~(-1)。波段信息,才能有效地将扩展青霉与其它霉菌区分开来,而且对表层污染(3mm)的区分效果优于深层污染(6mm)。在孢子悬浮液中,近红外对扩展青霉的检测限为1.5×10~1个/ml;在污染苹果的情况下,对扩展青霉的检测限为1.5×10~3个/ml;与其它霉菌污染苹果时,检测限为1.5×10~3个/ml。
(2)近红外光谱用于展青霉素检测时,需要对光谱进行适当的预处理,并选择最适主成分数及5883～5342 cm~(-1),4579～4324 cm~(-1)。波段范围内信息才能实现对不同体系中展青霉素进行定性定量分析。不同体系中结果如下:
水溶液中,用矢量归一化法预处理光谱,主成分数为3,所得模型的决定系数(R~2)为94.03%,交互检验方根差(RMSECV)为0.152μg/L;内部交叉验证的预测集决定系数(R~2)为93.1%,预测标准偏差(RMSEP)为0_3lμg/L。检测限为9.29μg/I.,
浓缩苹果汁中,用最大最小归一化法预处理光谱,主成分数6,所得模型的R~2=93.53%, RMSECV=0.42μg/L;内部交叉验证的预测集的R~2=92.65%, RMSEP=0.532μg/L,平均样品回收率为99.97%;检测限为9.76μg/L
鲜榨苹果汁中,用矢量一化法预处理光谱,主成分数7,所得模型的R~2=92.01%, RMSECV=0.7μg/L;内部交叉验证的预测集的R~2=90.73%, RMSEP=0.264μg/L;检测限为9.54μg/L
上述结果表明,近红外光谱法可以很好地应用于扩展青霉和展青霉素的定性定量检测。
Patulin is a mycotoxin with neurotoxicity, widely found in apple juice concentrate. Penicillium expansum was reported as the major patulin-producing fungus in apple. Development of quick and easy method for testing Penicillium expansum and patulin is important to effectively control of the two harmful factors. Near infrared spectroscopy method has great potential in online detection due to its no damage to sample, quick and good reproducibility. In order to explore good method in test of Penicillium expansum and patulin, the thesis investigated the ability of near-infrared spectroscopy in detecting Penicillium expansum under different conditions including pure culture, solely contamination and multiple contamination of different mould in apple. The capability was evaluated in quality and quantity. The application of near infrared-spectroscopy in detection of patulin was also evaluated in different conditions including water solution, fresh apple juice and apple juice concentrates. The cluster analysis and predicting model establishment were used in quality test evaluation and quantity test evaluation, respectively. The main results were obtained are listed as following:
(1)In the case of pure culture in solid medium, Penicillium expansum can be effectively distingushed from other fungi by using the information in whole wavelength region without any data pretreatment method, while the data pretreatment of first derivative method and vector normalization gave better results. In cases of spore suspension and contamination in apple, data pretreatment of first derivative method and vector normalization was needed to yield most effective distinguish when information was extracted from the wavelength regions of 5883~5342 cm~(-1) and 4579~4324 cm~(-1). The result was better to the contamination shallow under apple surface (3 mm) than that deeper (6mm). The testing limit of Penicillium expansum showed as 1.5x101 per ml for spore suspension and single mold contamination and 1.5x103 per ml for simultaneous contamination of different molds in apple.
(2) In order to give good distinguish and quantitive test of patulin in different conditions, it is necessary to use suitable data pretreatment, main factor number and extraction of information from the spectroscopy in the wavelength regions of 5883~5342 cm~(-1). Results obtained for different conditions are listed in the follows.
For water solution system, the best data pretreatment method is vector normalization at main factor number of 3. The best predicting model was obtained with coefficient of determination( R~2 )of 94.03% and cross-validation root deviation ( RMSECV )of 0.152 ug/L. The internal cross-validation of the predicting model yielded coefficient of determination (R~2) of 93.1%, standard deviation of prediction (RMSEP) of 0.31μg/L. The detection limit was calculated as 9.29μg/L.
For the apple juice concentrates, the best data pretreatment method was maximum and minimum normalized pretreatment with main factor number of 6. The predicting model was obtained as R~2=93.53% and RMSECV=0.42μg/L. The internal cross-validation of the predicting model showed R~2=92.65% and RMSEP=0.532μg/L with the detection limit of 9.76μg/L.
For the fresh apple juice, the best data pretreatment showed as vector normalization with main factor number of 7. The best predicting model yield R~2=92.01%, RMSECV=0.7 ug/L and internal cross-validation of R~2=90.73% and RMSEP=0.264μg/L with the detection limit of 9.54μg/L.
(1)平皿纯培养的条件下,利用全谱区信息就能有效地将扩展青霉与其它苹果致腐菌区分开来,对数据进行矢量归一化法+一阶导数法处理以后,区分效果更好。在孢子悬浮液和苹果污染体系,需要对数据进行矢量归一化法+一阶导数法处理,选取5883～5342 cm~(-1),4579～4324-cm~(-1)。波段信息,才能有效地将扩展青霉与其它霉菌区分开来,而且对表层污染(3mm)的区分效果优于深层污染(6mm)。在孢子悬浮液中,近红外对扩展青霉的检测限为1.5×10~1个/ml;在污染苹果的情况下,对扩展青霉的检测限为1.5×10~3个/ml;与其它霉菌污染苹果时,检测限为1.5×10~3个/ml。
(2)近红外光谱用于展青霉素检测时,需要对光谱进行适当的预处理,并选择最适主成分数及5883～5342 cm~(-1),4579～4324 cm~(-1)。波段范围内信息才能实现对不同体系中展青霉素进行定性定量分析。不同体系中结果如下:
水溶液中,用矢量归一化法预处理光谱,主成分数为3,所得模型的决定系数(R~2)为94.03%,交互检验方根差(RMSECV)为0.152μg/L;内部交叉验证的预测集决定系数(R~2)为93.1%,预测标准偏差(RMSEP)为0_3lμg/L。检测限为9.29μg/I.,
浓缩苹果汁中,用最大最小归一化法预处理光谱,主成分数6,所得模型的R~2=93.53%, RMSECV=0.42μg/L;内部交叉验证的预测集的R~2=92.65%, RMSEP=0.532μg/L,平均样品回收率为99.97%;检测限为9.76μg/L
鲜榨苹果汁中,用矢量一化法预处理光谱,主成分数7,所得模型的R~2=92.01%, RMSECV=0.7μg/L;内部交叉验证的预测集的R~2=90.73%, RMSEP=0.264μg/L;检测限为9.54μg/L
上述结果表明,近红外光谱法可以很好地应用于扩展青霉和展青霉素的定性定量检测。
Patulin is a mycotoxin with neurotoxicity, widely found in apple juice concentrate. Penicillium expansum was reported as the major patulin-producing fungus in apple. Development of quick and easy method for testing Penicillium expansum and patulin is important to effectively control of the two harmful factors. Near infrared spectroscopy method has great potential in online detection due to its no damage to sample, quick and good reproducibility. In order to explore good method in test of Penicillium expansum and patulin, the thesis investigated the ability of near-infrared spectroscopy in detecting Penicillium expansum under different conditions including pure culture, solely contamination and multiple contamination of different mould in apple. The capability was evaluated in quality and quantity. The application of near infrared-spectroscopy in detection of patulin was also evaluated in different conditions including water solution, fresh apple juice and apple juice concentrates. The cluster analysis and predicting model establishment were used in quality test evaluation and quantity test evaluation, respectively. The main results were obtained are listed as following:
(1)In the case of pure culture in solid medium, Penicillium expansum can be effectively distingushed from other fungi by using the information in whole wavelength region without any data pretreatment method, while the data pretreatment of first derivative method and vector normalization gave better results. In cases of spore suspension and contamination in apple, data pretreatment of first derivative method and vector normalization was needed to yield most effective distinguish when information was extracted from the wavelength regions of 5883~5342 cm~(-1) and 4579~4324 cm~(-1). The result was better to the contamination shallow under apple surface (3 mm) than that deeper (6mm). The testing limit of Penicillium expansum showed as 1.5x101 per ml for spore suspension and single mold contamination and 1.5x103 per ml for simultaneous contamination of different molds in apple.
(2) In order to give good distinguish and quantitive test of patulin in different conditions, it is necessary to use suitable data pretreatment, main factor number and extraction of information from the spectroscopy in the wavelength regions of 5883~5342 cm~(-1). Results obtained for different conditions are listed in the follows.
For water solution system, the best data pretreatment method is vector normalization at main factor number of 3. The best predicting model was obtained with coefficient of determination( R~2 )of 94.03% and cross-validation root deviation ( RMSECV )of 0.152 ug/L. The internal cross-validation of the predicting model yielded coefficient of determination (R~2) of 93.1%, standard deviation of prediction (RMSEP) of 0.31μg/L. The detection limit was calculated as 9.29μg/L.
For the apple juice concentrates, the best data pretreatment method was maximum and minimum normalized pretreatment with main factor number of 6. The predicting model was obtained as R~2=93.53% and RMSECV=0.42μg/L. The internal cross-validation of the predicting model showed R~2=92.65% and RMSEP=0.532μg/L with the detection limit of 9.76μg/L.
For the fresh apple juice, the best data pretreatment showed as vector normalization with main factor number of 7. The best predicting model yield R~2=92.01%, RMSECV=0.7 ug/L and internal cross-validation of R~2=90.73% and RMSEP=0.264μg/L with the detection limit of 9.54μg/L.
引文
白琪林,陈绍江,董晓玲等.近红外漫反射光谱法测定玉米秸秆NDF与ADF含量[J].光谱学与光谱分析,2004,24(11):1345～1347.
白琪林,陈绍江,董晓玲等.近红外漫反射光谱法测定玉米秸秆体外干物质消化率[J].光谱学与光谱分析,2006,26 (2): 271～274.
陈斌,方如明,赵文杰等.食醋主要成分近红外光谱快速侧定法[J].食品科学,2000,21 (5):55～57.
陈庆宁主编.实用生物毒素学[M].北京:中国科技技术出版社,2001:442-447.
陈文杰,谭小力,王竹云.用傅里叶变换近红外光谱仪测定油菜种子品质指标的研究[J].陕西农业科学,2002,(8):6～8.
费坚.近红外光谱技术在苹果汁加工领域的研究[D].西安,西北农林科技大学,2005.
费坚等.果品果汁加工中的近红外光谱技术[J].西北农业学报2005,14(1):88～93.
郭萍,熊平,袁亚莉.乳糖的傅里叶变换红外光谱分析[J].光谱学与光谱分析,2002,22 (4):603～606
阂顺耕,李宁,张明祥.近红外光谱分析中异常值的判别与定量模型优化[J].光谱学与光谱分析,2004,24(10): 1205～1209
贺玉梅,董葵,杜娟等.展青霉素产生菌产毒性能研究[J].中国卫生检验杂志,2001,11(3):302-303.
吉海彦,严衍禄.在国产近红外光谱仪试验样机上用偏最小二乘法定量分析大麦成分[J].分析化学,1998,26 (5):607～61
蒋雄图,虞左向.棒曲霉素[J].无锡轻工业学院学报,1989,8(2):73-84.
李华北,陈斌,赵杰文等.用小波变换技术提高食醋近红外光谱分析的精度[J].农业工程学报,2000,16(6):114～117.
李庆波,汪燕,徐可欣.牛奶主要成分含量近红外光谱快速测量法食品科学[J].2002, 23,(6) :121～124.
李庆波,徐可欣,王斌.牛奶主要成分含量近红外光谱快速测量法[J].食品科学,2002,23 (6):121～122.
梁逸曾,俞汝勤.化学计量学[M].北京:高等教育出版社,2003,118～119.
林春国,周元忻,李兰.果蔬汁中棒曲霉素的来源及检测[J].中外葡萄与葡萄酒, 1999(1):43-47.
林水,吴平平.实用傅里叶近红外光谱学[M].北京:中国环境科学出版社,1991,318～319.
刘桂宾,刘志华.近红外光谱法同时测定葵花粕中油、蛋白质、水分和粗纤维[J].光谱实验室,1996,13 (2): 16～19
刘桂宾,刘志华.近红外光谱法同时测定葵花粕中油、蛋白质、水分和粗纤维[J].光谱实验室,1996,13 (2): 16～19.
刘国林,陈国广,相秉仁等.近红外光谱技术在元胡止痛散定量分析中的初步应用研究[J].中国现代应用药学杂志,2000,17 (5): 383～385.
刘贤.基于近红外光谱的青贮饲料快速分析方法与模型的研究[D].济南,山东农业大学,2006
陆婉珍,袁洪福,徐广通等.现代近红外光谱分析技术[M].北京:中国石化出版社,2000,62～100,105～150
逯家辉,滕利荣,蒋富明等.短波近红外光谱法分析酒中乙醇含量[J].吉林大学学报(理学版),2002,41:245～247.
蒲登鑫,王文茂,李军会,等.近红外在线质量监控技术在中药葛根素生产中的应用[J].现代仪器,2003,(5): 27～29.
史永刚,冯新沪,李子存.化学计量学[M].北京:中国石化出版社,2002,139～144.
苏青峰.苹果浓缩汁(AJC)生产中棒曲霉素产生菌的分离鉴定及控制技术研究[D].杨凌:西北农林科技大学,2005.
王东丹,李天飞.近红外光谱分析技术在烟草化学分析上的应用研究[J].云南大学学报,2001,23(2):135～137.
魏良明.普通玉米籽粒品质性状的遗传及其近红外测定方法的研究[D].北京:中国农业大学,2003,7～12.
吴瑾光.近代博里叶变换红外光谱技术及应用(上卷) [M].北京:科学技术文献出版社,I994,251～281
徐广通,陆婉珍,袁洪福,等.CCD近红外光谱仪在柴油生产控制分析中的应用[J].石油炼制与化工,1999,30 (9): 57～61.
徐广通,袁洪福,陆婉珍.现代近红外光谱技术及应用进展[J].光谱学与光谱分析,2000,20 (2):134～142
许禄,邵学广.化学计量学方法[M].北京:科学出版社,2004,130～175
严衍禄,赵龙莲,韩东海,等.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005,31～39,113～217
杨玉兰.基于近红外方法的银杏叶品质的研究[D].郑州,河南科技大学,2005.
袁洪福,褚小立,陆婉珍,等.一种新型在线近红外光谱分析仪的研制[J].分析化学,2003,32 (2):255～261.
赵龙莲,阂顺耕.傅立叶变换近红外光谱法测定烟草中9种品质参数[J].光谱学与光谱分析,1998, 18 (4): 89～90.
周克权.展青霉素的化学检测方法[J].国外医学卫生学分册,2001,28(1):29-32.
朱振宝,易建华,寇晓康.苹果汁中棒曲霉素的吸附动力学研究[J].食品科学.2006, 27(6):91-95.
Acar. J., V. Gokmen and E.E. Taydas. The effects of Processing technology on the patulin content of juice during commercial apple juice concentrate production[J]. Zeitschrift fuer Lebensmittel Untersuchung und Forschung,1998,207(4):328-331.
Artik N, Cemeroglu B, Aydar G. et al, Use of activated carbon for patulin control in apple juice concentrate[J]. Turkish Journal of Agriculture and Forestry, 1995,19(4):259-265.
Biing-Hui Liu*, Feng-Yih Yu, Ting-Shuan Wu et al, Evaluation of genotoxic risk and oxidative DNA damage in mammalian cells exposed to mycotoxins, patulin and citrinin[J]. Toxicology and Applied Pharmacology, 2003,191: 255–263.
Bisessur. J., K.Permaul, and B. Odhav. Reduction of Patulin during apple juice clarification[J]. Journal of food protection, 2001:1216-1219.
Bruna D., M. Voldrich, M. Marek et al, Effect of processing and storage conditions on patulin content in apple juice concentrate[J]. Czech Journal of Food Science, 1999,17(4):127-132.
Casadio S. and I. Niola. Patulin destabilization in fruit juices using micowaves[J]. Industrie delle Bevande,1993,22(123):10-11.
David M. Schumacher, Manfred Metzler, Leane Lehmann. Mutagenicity of the mycotoxin patulin in cultured Chinese hamster V79 cells, and its modulation by intracellular glutathione [J]. Arch Toxicol, 2005 ,79: 110–121.
Ellen C.Hopmans. Patulin:a Mycotoxin in Apples[J]. Perishables Handing Quarterly Issue. 1997,91:5-6.
Essa H A, Ayesh A M. Mycotoxins reduction and inhibition ofenzymatic browning during apple juice processing[J]. Egyptian Journal of Food Science,2002,30 (1):1-21.
G. C. LLEWELLYN, J. A. McCAY, R. D. BROWN et al, Immunological Evaluation of the Mycotoxin Patulin in female B6C3F1 Mice[J]. Food and Chemical Toxicology,1998,36:1107-1115.
Garcia-wass F,Hammond D,Mottram D S,et al.Detection of fruit juice authenticity using pyrolysis mass spectroscopy. [J] Food Chemistry,2000,69:215～220
Gokmen V., N. Artik, J.,Acar et al, Effects of various clarification treatments on patulin, phenolic compoundandorganic acid compositions of apple juice[J]. European Food and technology,2001,213:194-199.
Güldeniz Selmanoglu*, E.Arzu Kockaya. Investigation of the effects of patulin on thyroid and testis, and hormone levels in growing male rats [J]. Food and Chemical Toxicology, 2004,42 :721–727.
HammondD.Synergy between liquid chromatographic-pulsed amperometric detection and capillary-gas chromatographic methods for the datection of juice adulteration.J.of AOAC,2001,84(3):964～975
Huebner. H.J., K. Mayura, L.Pallaroni et al, Development and characterization of a carbon-based composite material for reducing patulin levers in apple juice[J]. Journal of food protection,2000,63:106-110.
Jezek J,Suhaj M.Application of capillary isotachphoresis for fruit juice authentication.J.of Chromatography,2001,916:185～189.
Kadakal C, Nas S. Effect of activated charcoal on patulin, fumaricacid and some other properties of apple juice[J]. Nahrung,2002,46:31-33.
Keiko Iizuka,Tetsuo Aishima1. Differentiation of Soy Sauce by Pattern Recognition Analysis of Mid-and Near-IR Spectra[J].Journal of food composition and analysis,1999,12:197～209.
L.J. McELROY, C.M. WEISS .The Production of Polyclnal Antibodies against the Mycotoxin Derivative patulin hemiglutarate[J].J.Microbiol,1993,39:861-863.
Leggott, N. L., G.S. Shephard and S.Stockenstrom .The reduction of patulin in apple Juice by three different types of actived carbon[J].Food Additives﹠Contaminants, 2001,18:825-829.
Lovett J., Thompson R.G. and Boutin B.K.. Trimming as a means of removing patulin from fungus-rotted apples[J]. Journal of the Association of Official Analytical Chemists,1975,58:909-911.
Low N H.Datermination of fruit juice authenticity by capillary gas chromatography with flameionization ddection.J.of AOAC,1996,79(3):724～737
Mary Ann , Dombrink-Kurtzman*, Judy A. Blackburn. Evaluation of several culture media for production of patulin by Penicillium species[J]. International Journal of Food Microbiology,2005 ,98:241-248.
Michael Rychlik, Peter Schieberle. Model studies on the diffusion behavior of the mycotoxin patulin in apples, tomatoes, and wheat bread[J]. Eur Food Res Technol, 2001,212:274–278.
Mutlu, M., N. Hizarcioglu and V. Gokmen. Patulin adsorption kinetics on activated carbon, activation energy and heat of adsorption[J].Journal of Food Science, 1997,62:128-130.
Robert A Kryger. Volatility of Patulin in Apple Juice[J]. J Agric Food Chem. 2001,49:4141-4143.
白琪林,陈绍江,董晓玲等.近红外漫反射光谱法测定玉米秸秆体外干物质消化率[J].光谱学与光谱分析,2006,26 (2): 271～274.
陈斌,方如明,赵文杰等.食醋主要成分近红外光谱快速侧定法[J].食品科学,2000,21 (5):55～57.
陈庆宁主编.实用生物毒素学[M].北京:中国科技技术出版社,2001:442-447.
陈文杰,谭小力,王竹云.用傅里叶变换近红外光谱仪测定油菜种子品质指标的研究[J].陕西农业科学,2002,(8):6～8.
费坚.近红外光谱技术在苹果汁加工领域的研究[D].西安,西北农林科技大学,2005.
费坚等.果品果汁加工中的近红外光谱技术[J].西北农业学报2005,14(1):88～93.
郭萍,熊平,袁亚莉.乳糖的傅里叶变换红外光谱分析[J].光谱学与光谱分析,2002,22 (4):603～606
阂顺耕,李宁,张明祥.近红外光谱分析中异常值的判别与定量模型优化[J].光谱学与光谱分析,2004,24(10): 1205～1209
贺玉梅,董葵,杜娟等.展青霉素产生菌产毒性能研究[J].中国卫生检验杂志,2001,11(3):302-303.
吉海彦,严衍禄.在国产近红外光谱仪试验样机上用偏最小二乘法定量分析大麦成分[J].分析化学,1998,26 (5):607～61
蒋雄图,虞左向.棒曲霉素[J].无锡轻工业学院学报,1989,8(2):73-84.
李华北,陈斌,赵杰文等.用小波变换技术提高食醋近红外光谱分析的精度[J].农业工程学报,2000,16(6):114～117.
李庆波,汪燕,徐可欣.牛奶主要成分含量近红外光谱快速测量法食品科学[J].2002, 23,(6) :121～124.
李庆波,徐可欣,王斌.牛奶主要成分含量近红外光谱快速测量法[J].食品科学,2002,23 (6):121～122.
梁逸曾,俞汝勤.化学计量学[M].北京:高等教育出版社,2003,118～119.
林春国,周元忻,李兰.果蔬汁中棒曲霉素的来源及检测[J].中外葡萄与葡萄酒, 1999(1):43-47.
林水,吴平平.实用傅里叶近红外光谱学[M].北京:中国环境科学出版社,1991,318～319.
刘桂宾,刘志华.近红外光谱法同时测定葵花粕中油、蛋白质、水分和粗纤维[J].光谱实验室,1996,13 (2): 16～19
刘桂宾,刘志华.近红外光谱法同时测定葵花粕中油、蛋白质、水分和粗纤维[J].光谱实验室,1996,13 (2): 16～19.
刘国林,陈国广,相秉仁等.近红外光谱技术在元胡止痛散定量分析中的初步应用研究[J].中国现代应用药学杂志,2000,17 (5): 383～385.
刘贤.基于近红外光谱的青贮饲料快速分析方法与模型的研究[D].济南,山东农业大学,2006
陆婉珍,袁洪福,徐广通等.现代近红外光谱分析技术[M].北京:中国石化出版社,2000,62～100,105～150
逯家辉,滕利荣,蒋富明等.短波近红外光谱法分析酒中乙醇含量[J].吉林大学学报(理学版),2002,41:245～247.
蒲登鑫,王文茂,李军会,等.近红外在线质量监控技术在中药葛根素生产中的应用[J].现代仪器,2003,(5): 27～29.
史永刚,冯新沪,李子存.化学计量学[M].北京:中国石化出版社,2002,139～144.
苏青峰.苹果浓缩汁(AJC)生产中棒曲霉素产生菌的分离鉴定及控制技术研究[D].杨凌:西北农林科技大学,2005.
王东丹,李天飞.近红外光谱分析技术在烟草化学分析上的应用研究[J].云南大学学报,2001,23(2):135～137.
魏良明.普通玉米籽粒品质性状的遗传及其近红外测定方法的研究[D].北京:中国农业大学,2003,7～12.
吴瑾光.近代博里叶变换红外光谱技术及应用(上卷) [M].北京:科学技术文献出版社,I994,251～281
徐广通,陆婉珍,袁洪福,等.CCD近红外光谱仪在柴油生产控制分析中的应用[J].石油炼制与化工,1999,30 (9): 57～61.
徐广通,袁洪福,陆婉珍.现代近红外光谱技术及应用进展[J].光谱学与光谱分析,2000,20 (2):134～142
许禄,邵学广.化学计量学方法[M].北京:科学出版社,2004,130～175
严衍禄,赵龙莲,韩东海,等.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005,31～39,113～217
杨玉兰.基于近红外方法的银杏叶品质的研究[D].郑州,河南科技大学,2005.
袁洪福,褚小立,陆婉珍,等.一种新型在线近红外光谱分析仪的研制[J].分析化学,2003,32 (2):255～261.
赵龙莲,阂顺耕.傅立叶变换近红外光谱法测定烟草中9种品质参数[J].光谱学与光谱分析,1998, 18 (4): 89～90.
周克权.展青霉素的化学检测方法[J].国外医学卫生学分册,2001,28(1):29-32.
朱振宝,易建华,寇晓康.苹果汁中棒曲霉素的吸附动力学研究[J].食品科学.2006, 27(6):91-95.
Acar. J., V. Gokmen and E.E. Taydas. The effects of Processing technology on the patulin content of juice during commercial apple juice concentrate production[J]. Zeitschrift fuer Lebensmittel Untersuchung und Forschung,1998,207(4):328-331.
Artik N, Cemeroglu B, Aydar G. et al, Use of activated carbon for patulin control in apple juice concentrate[J]. Turkish Journal of Agriculture and Forestry, 1995,19(4):259-265.
Biing-Hui Liu*, Feng-Yih Yu, Ting-Shuan Wu et al, Evaluation of genotoxic risk and oxidative DNA damage in mammalian cells exposed to mycotoxins, patulin and citrinin[J]. Toxicology and Applied Pharmacology, 2003,191: 255–263.
Bisessur. J., K.Permaul, and B. Odhav. Reduction of Patulin during apple juice clarification[J]. Journal of food protection, 2001:1216-1219.
Bruna D., M. Voldrich, M. Marek et al, Effect of processing and storage conditions on patulin content in apple juice concentrate[J]. Czech Journal of Food Science, 1999,17(4):127-132.
Casadio S. and I. Niola. Patulin destabilization in fruit juices using micowaves[J]. Industrie delle Bevande,1993,22(123):10-11.
David M. Schumacher, Manfred Metzler, Leane Lehmann. Mutagenicity of the mycotoxin patulin in cultured Chinese hamster V79 cells, and its modulation by intracellular glutathione [J]. Arch Toxicol, 2005 ,79: 110–121.
Ellen C.Hopmans. Patulin:a Mycotoxin in Apples[J]. Perishables Handing Quarterly Issue. 1997,91:5-6.
Essa H A, Ayesh A M. Mycotoxins reduction and inhibition ofenzymatic browning during apple juice processing[J]. Egyptian Journal of Food Science,2002,30 (1):1-21.
G. C. LLEWELLYN, J. A. McCAY, R. D. BROWN et al, Immunological Evaluation of the Mycotoxin Patulin in female B6C3F1 Mice[J]. Food and Chemical Toxicology,1998,36:1107-1115.
Garcia-wass F,Hammond D,Mottram D S,et al.Detection of fruit juice authenticity using pyrolysis mass spectroscopy. [J] Food Chemistry,2000,69:215～220
Gokmen V., N. Artik, J.,Acar et al, Effects of various clarification treatments on patulin, phenolic compoundandorganic acid compositions of apple juice[J]. European Food and technology,2001,213:194-199.
Güldeniz Selmanoglu*, E.Arzu Kockaya. Investigation of the effects of patulin on thyroid and testis, and hormone levels in growing male rats [J]. Food and Chemical Toxicology, 2004,42 :721–727.
HammondD.Synergy between liquid chromatographic-pulsed amperometric detection and capillary-gas chromatographic methods for the datection of juice adulteration.J.of AOAC,2001,84(3):964～975
Huebner. H.J., K. Mayura, L.Pallaroni et al, Development and characterization of a carbon-based composite material for reducing patulin levers in apple juice[J]. Journal of food protection,2000,63:106-110.
Jezek J,Suhaj M.Application of capillary isotachphoresis for fruit juice authentication.J.of Chromatography,2001,916:185～189.
Kadakal C, Nas S. Effect of activated charcoal on patulin, fumaricacid and some other properties of apple juice[J]. Nahrung,2002,46:31-33.
Keiko Iizuka,Tetsuo Aishima1. Differentiation of Soy Sauce by Pattern Recognition Analysis of Mid-and Near-IR Spectra[J].Journal of food composition and analysis,1999,12:197～209.
L.J. McELROY, C.M. WEISS .The Production of Polyclnal Antibodies against the Mycotoxin Derivative patulin hemiglutarate[J].J.Microbiol,1993,39:861-863.
Leggott, N. L., G.S. Shephard and S.Stockenstrom .The reduction of patulin in apple Juice by three different types of actived carbon[J].Food Additives﹠Contaminants, 2001,18:825-829.
Lovett J., Thompson R.G. and Boutin B.K.. Trimming as a means of removing patulin from fungus-rotted apples[J]. Journal of the Association of Official Analytical Chemists,1975,58:909-911.
Low N H.Datermination of fruit juice authenticity by capillary gas chromatography with flameionization ddection.J.of AOAC,1996,79(3):724～737
Mary Ann , Dombrink-Kurtzman*, Judy A. Blackburn. Evaluation of several culture media for production of patulin by Penicillium species[J]. International Journal of Food Microbiology,2005 ,98:241-248.
Michael Rychlik, Peter Schieberle. Model studies on the diffusion behavior of the mycotoxin patulin in apples, tomatoes, and wheat bread[J]. Eur Food Res Technol, 2001,212:274–278.
Mutlu, M., N. Hizarcioglu and V. Gokmen. Patulin adsorption kinetics on activated carbon, activation energy and heat of adsorption[J].Journal of Food Science, 1997,62:128-130.
Robert A Kryger. Volatility of Patulin in Apple Juice[J]. J Agric Food Chem. 2001,49:4141-4143.