饲用苎麻与玉米混合青贮饲料的气味分析
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摘要
以饲用苎麻和全株玉米为混合青贮原料,利用电子鼻技术对饲用苎麻与全株玉米按不同比例混合青贮时发酵饲料气味进行检测分析,并对其信号响应值进行主成分分析、线性判别分析、传感器区分贡献率分析及雷达图分析,可实现7种不同混合比例青贮发酵样品的良好区分。结果还表明,饲用苎麻与全株玉米按不同比例混合青贮时,全株玉米的添加量对最终青贮饲料的气味组成有重要影响。因此,选取青贮效果正常的样品作为参考对象,利用电子鼻检测技术可有望快速鉴别出待检样品是否青贮成功。
In this paper,the fodder ramie and whole-plant corn were chosen as the fermented materials of mixture silage,the smell of silage after mixed fermentation by the fodder ramie and whole-plant corn with a different ratio was tested and analyzed with the help of electronic nose,and then the response values of the sensor signal were deeply analyzed by the means of principal component analysis(PCA),linear discriminant analysis(LDA),sensors to distinguish the contribution analysis(LOADING) and radar map.The results showed that according to the smell analysis by the use of electronic nose,the 7 silage investigated in this paper could be well differentiated.In addition,the results also showed that the additive amount of whole-plant corn had a significant influence on the overall smell structure for the final silage.Consequently,when the silage which was well fermented was chosen as the reference object,whether the detecting silage was well fermented or not could be identified quickly by the use of electronic nose technology.
In this paper,the fodder ramie and whole-plant corn were chosen as the fermented materials of mixture silage,the smell of silage after mixed fermentation by the fodder ramie and whole-plant corn with a different ratio was tested and analyzed with the help of electronic nose,and then the response values of the sensor signal were deeply analyzed by the means of principal component analysis(PCA),linear discriminant analysis(LDA),sensors to distinguish the contribution analysis(LOADING) and radar map.The results showed that according to the smell analysis by the use of electronic nose,the 7 silage investigated in this paper could be well differentiated.In addition,the results also showed that the additive amount of whole-plant corn had a significant influence on the overall smell structure for the final silage.Consequently,when the silage which was well fermented was chosen as the reference object,whether the detecting silage was well fermented or not could be identified quickly by the use of electronic nose technology.
引文
[1]陈丽萍,徐茂琴,何红萍,等.应用PEN3型电子鼻传感器快速检测食源性致病菌[J].食品科学,2014,35(8):187~192.
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[18]谢安国,王金水,渠琛玲,等.电子鼻在食品风味分析中的应用研究进展[J].农产品加工:学刊,2011,1:71~73.
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[21]杨曾平,张爱武,谢坚,等.适合南方的养牛牧草研究进展[J].湖南农业科学,2013,3:101~104.
[22]于杰,郑琛,李发弟,等.向日葵秸秆与全株玉米混合青贮饲料品质评定[J].草业学报,2013,22(5):198~204.
[23]邹慧琴,刘勇,林辉,等.电子鼻技术及应用研究进展[J].传感器世界,2011,17(11):4~5.
[24]Barbri N E,Llobet E,Bari N E,et al.Electronic Nose Based on Metal Oxide Semiconductor Sensors as an Alternative Technique for the Spoilage Classification of Red Meat[J].Sensors,2008,8(1):142~156.
[25]Labreche S,Bazzo S,Cade S,et al.Shelf life determination by electronic nose:application to milk[J].Sensor Actuat B-Chem,2005,106(1):199~206.
[26]Doleman B J,Lewis N S.Comparison of odor detection thresholds and odor discriminablities of a conducting polymer composite electronic nose versus mammalian olfaction[J].Sensor Actuat B-Chem,2015,72(1):41~50.
[27]Drake M A,Gerard P D,Kleinhenz J P,et al.Application of an electronic nose to correlate with descriptive sensory analysis of aged,Cheddar cheese[J].LWT-Food Sci Technol,2003,36(1):13~20.
[28]Dutta R,Kashwan K R,Bhuyan M,et al.Electronic nose based tea quality standardization[J].Neural Networks,2003,16(5~6):847~853.
[29]Ganho R,Estévez M,Morcuende D.Suitability of the TBA method for assessing lipid oxidation in a meat system with added phenolic-rich materials[J].Food Chem,2011,126(2):772~778.
[30]Grigioni G M,Margar A C A,Pensel N A,et al.Warmed-over flavour analysis in low temperature-long time processed meat by an“electronic nose”[J].Meat Sci,2000,56(3):221~228.
[31]Natale C D,Zude-Sasse M,Macagnano A,et al.Outer product analysis of electronic nose and visible spectra:application to the measurement of peach fruit characteristics[J].Anal Chim Acta,2002,459(1):107~117.
[32]Wang Z,Yue T,Yuan Y,et al.Development of polyclonal antibodybased indirect enzyme-linked immunosorbent assay for the detection of Alicyclobacillus strains in apple juice[J].J Food Sci,2012,77(11):643~649.
[2]丁玉勇.基于电子鼻和多种模式识别算法的不同种食用香辛料的鉴别[J].食品科学,2013,34(16):274~278.
[3]高永梅,刘远方,李艳霞,等.主要香型白酒的电子鼻指纹图谱[J].酿酒科技,2008,5:38~40.
[4]郭兆阳.感官与化学统计分析技术剖析白酒风味物质[D].山东轻工业学院,2011.
[5]贾洪锋,邓红,梁爱华.电子鼻在芝麻油掺芝麻油香精识别中的应用[J].中国调味品,2012,28(5):83~86.
[6]李文杨,陈鑫珠,刘远,等.不同添加剂对苎麻青贮品质的影响[J].家畜生态学报,2016,37(7):56~59.
[7]李照,邢黎明,云战友,等.电子鼻测定牛奶中掺入外来脂肪[J].乳业科学与技术,2008,31(1):42~44.
[8]柳茜,孙启忠,刘晓波,等.红三叶与全株玉米混合比例对青贮品质的影响[J].草业与畜牧,2017,2:33~37.
[9]田耀伟,杨雷玉,朱先约,等.电子鼻在卷烟真伪鉴别中的应用[J].食品工业科技,2011,4:376~378.
[10]王储炎,熊国远,贾敬敏,等.利用电子鼻检测不同香辛料熬制的卤汤[J].江苏农业科学,2017,45(10):136~140.
[11]王俊,崔绍庆,陈新伟,等.电子鼻传感技术与应用研究进展[J].农业机械学报,2013,44(11):160~167.
[12]王满生,王延周,杨晶,等.基于Web of Science核心合集的青贮技术研究动态及引文可视化分析[J].粮食与饲料工业,2017,9:50~55.
[13]王满生,王延周,邓欣,等.基于Innography专利数据库平台的青贮加工技术态势分析[J].粮食与饲料工业,2017,8:34~39.
[14]王文,李晓林,向必勇.青贮技术变迁史[J].中国畜牧业,2016,23:53~55.
[15]王玉芬,周晓茹,刘晓晨,等.应用电子鼻技术对鸡肉香精美拉德反应条件的优化[J].食品研究与开发,2016,37(8):220~224.
[16]吴端钦,唐守伟,朱四元,等.饲用苎麻产量和品质的影响因素及其在动物生产中的应用[J].中国饲料,2015,7:35~37.
[17]吴端钦,王郝为,侯振平,等.几种南方非常规饲料作物的营养成分及氨基酸组成[J].草业科学,2017,34(6):1332~1336.
[18]谢安国,王金水,渠琛玲,等.电子鼻在食品风味分析中的应用研究进展[J].农产品加工:学刊,2011,1:71~73.
[19]徐亚丹,王俊,赵国军.基于电子鼻的对掺假的"伊利"牛奶的检测[J].中国食品学报,2006,6(5):111~118.
[20]杨晶,王建辉,刘永乐,等.草鱼肌肉风味变化与品质间的关联[J].食品科学,2015,36(12):82~86.
[21]杨曾平,张爱武,谢坚,等.适合南方的养牛牧草研究进展[J].湖南农业科学,2013,3:101~104.
[22]于杰,郑琛,李发弟,等.向日葵秸秆与全株玉米混合青贮饲料品质评定[J].草业学报,2013,22(5):198~204.
[23]邹慧琴,刘勇,林辉,等.电子鼻技术及应用研究进展[J].传感器世界,2011,17(11):4~5.
[24]Barbri N E,Llobet E,Bari N E,et al.Electronic Nose Based on Metal Oxide Semiconductor Sensors as an Alternative Technique for the Spoilage Classification of Red Meat[J].Sensors,2008,8(1):142~156.
[25]Labreche S,Bazzo S,Cade S,et al.Shelf life determination by electronic nose:application to milk[J].Sensor Actuat B-Chem,2005,106(1):199~206.
[26]Doleman B J,Lewis N S.Comparison of odor detection thresholds and odor discriminablities of a conducting polymer composite electronic nose versus mammalian olfaction[J].Sensor Actuat B-Chem,2015,72(1):41~50.
[27]Drake M A,Gerard P D,Kleinhenz J P,et al.Application of an electronic nose to correlate with descriptive sensory analysis of aged,Cheddar cheese[J].LWT-Food Sci Technol,2003,36(1):13~20.
[28]Dutta R,Kashwan K R,Bhuyan M,et al.Electronic nose based tea quality standardization[J].Neural Networks,2003,16(5~6):847~853.
[29]Ganho R,Estévez M,Morcuende D.Suitability of the TBA method for assessing lipid oxidation in a meat system with added phenolic-rich materials[J].Food Chem,2011,126(2):772~778.
[30]Grigioni G M,Margar A C A,Pensel N A,et al.Warmed-over flavour analysis in low temperature-long time processed meat by an“electronic nose”[J].Meat Sci,2000,56(3):221~228.
[31]Natale C D,Zude-Sasse M,Macagnano A,et al.Outer product analysis of electronic nose and visible spectra:application to the measurement of peach fruit characteristics[J].Anal Chim Acta,2002,459(1):107~117.
[32]Wang Z,Yue T,Yuan Y,et al.Development of polyclonal antibodybased indirect enzyme-linked immunosorbent assay for the detection of Alicyclobacillus strains in apple juice[J].J Food Sci,2012,77(11):643~649.