1.上海海关动植物与食品检验检疫技术中心,上海 200135
2.复旦大学 公共卫生学院,上海 200433
曾静,工程师,硕士,研究方向:食品安全,E-mail:zengjingzyq@126.com
扫 描 看 全 文
曾静,伊雄海,曲栗等.基于脂肪酸含量分析结合化学计量学的橄榄油等级鉴别方法[J].分析测试学报,2021,40(10):1432-1438.
ZENG Jing,YI Xiong-hai,QU Li,et al.Grade Identification of Olive Oil Based on Fatty Acids Analysis Combined with Chemometrics[J].Journal of Instrumental Analysis,2021,40(10):1432-1438.
曾静,伊雄海,曲栗等.基于脂肪酸含量分析结合化学计量学的橄榄油等级鉴别方法[J].分析测试学报,2021,40(10):1432-1438. DOI: 10.19969/j.fxcsxb.21032803.
ZENG Jing,YI Xiong-hai,QU Li,et al.Grade Identification of Olive Oil Based on Fatty Acids Analysis Combined with Chemometrics[J].Journal of Instrumental Analysis,2021,40(10):1432-1438. DOI: 10.19969/j.fxcsxb.21032803.
建立了一种基于脂肪酸含量分析结合化学计量学技术的橄榄油等级判别方法。以经确认属性的特级初榨橄榄油和精炼橄榄油作为测试集,采用气相色谱法分别测定两类橄榄油中的脂肪酸含量,通过主成分分析(PCA)、聚类分析(HCA)及偏最小二乘判别分析(PLS-DA)法建立橄榄油的等级鉴别模型。结果表明,PCA能成功区分特级初榨橄榄油和精炼橄榄油,HCA也能有效对两种等级橄榄油进行鉴别,最终筛选出VIP值(重要贡献值)大于1的6种特征组分:C23∶0、C18∶2n6t、C24∶0、C18∶1/C18∶2、C20∶1和C18∶1n9c。同时以98个未知属性的橄榄油样品为验证集,对建立的橄榄油等级判别模型进行交叉验证(CV),模型预测评估值(,Q,2,)及相关系数(,R,2,)均大于0.96,说明所建的橄榄油等级鉴别预测模型较可靠。因此,采用脂肪酸含量分析结合化学计量学技术可用于特级初榨橄榄油和精炼橄榄油的等级鉴别。
Extra virgin olive oil is favored by consumers for its high nutritional value,but its prices is relatively expensive.In order to increase profits,some illegal merchants have taken some concealed means to mix refined olive oil into extra virgin olive oil,or pass off refined olive oil as extra virgin olive oil to cheat consumers.At present,domestic studies on adulteration of olive oil mainly focus on the adulteration of olive oil with other edible oils,and few studies involve in grade identification of extra virgin olive oil and low-grade olive oil.Foreign studies on the identification of olive oil grades are mainly based on spectral technology,while the spectral method could only provide the relevant information of the whole fingerprint characteristics,but not the information of its specific components.Therefore,it is significant to establish a method to distinguish the grades of extra virgin olive oil and low-grade olive oils based on the characteristic components in olive oil.In this paper,a method was established to distinguish the grade of olive oil based on the content analysis of fatty acids combined with chemometrics.Extra virgin olive oil and refined olive oil with confirmed properties were used as test set.Fatty acids contents in the two grades of olive oil were determined by gas chromatography(GC) using SP-2560(100 m × 0.25 mm,0.2 μm) column.Olive oil grade discrimination model was established by three chemometrics,i.e. primary component analysis(PCA),hierarchical cluster analysis(HCA) and partial least squares-discrimination analysis(PLS-DA).Results showed that,PCA could successfully distinguish extra virgin olive oil and refined olive oil,and HCA could also effectively identify two grades of olive oil.Through PLS-DA,six characteristic components with variable importance in the projection(VIP) greater than 1 were selected as follows:C23∶0,C18∶2n6t,C24∶0,C18∶1/C18∶2,C20∶1 and C18∶1n9c. Meanwhile,98 olive oil samples with unknown properties were taken as the validation set,and cross validation(CV) was carried out on the established olive oil grade discrimination model.The model prediction evaluation value(,Q,2,),and correlation coefficient(,R,2,) were greater than 0.96.The results indicated that the established model of olive oil grade discrimination and prediction was reliable.Therefore,analysis of fatty acids and multiple element contents combined with chemometrics could be used to identify the grades of extra virgin olive oil and refined olive oil.
脂肪酸特级初榨橄榄油精炼橄榄油化学计量学等级鉴别气相色谱
fatty acidsextra virgin olive oilrefined olive oilchemometricsgrade identificationgas chromatography
Maggio R M,Cerretani L,Chiavaro E,Kaufman T S,Bendini A.Food Control,2010,21(2):890-895.
Torrecilia J S,Rojo E,Dominguez J C,Rodriguez F.J. Agric. Food Chem.,2010,58(3):1679-1684.
Liu W H,Bie W,Zhang Z H,Liang N N,Lü M L,Han S.J. Food Saf. Qual. (刘伟华,别玮,张朝晖,梁娜娜,吕美玲,韩深.食品安全质量检测学报),2014,5(10):3197-3202.
Sun X D.Quality Analysis of Extra Virgin Olive Oil by Chemometrics Methods and FT-IR Spectra.Zhengzhou:Zhengzhou University(孙晓丹.基于化学计量学方法和FT-IR光谱的橄榄油品质分析.郑州:郑州大学),2015.
Harhar H,Gharby S,Pioch D,Kartah B,Ibrahimi M,Charrouf Z.Moroccan J. Chem.,2016,4(2):279-284.
Yang Y,Ferro M D,Cavaco I,Liang Y Z.J. Agric. Food Chem.,2013,61(15):3693-3702.
Dais P,Hatzakis E.Anal. Chim. Acta,2013,765:1-27.
Krichene D,Allalout A,Salvador M D,Fregapane G,Zarrouk M.Eur. J. Lipid Sci. Technol.,2010,112:400-409.
Beltran M,Astudillo M S,Aparicio R,Garcia-Gonzalez D L.Food Chem.,2015,169:350-357.
Yang Z D,Ren X M,Wang J,Yu Y Y,Tian H Y,Zhang H X.J. Food Saf. Qual. (杨振东,任雪梅,王键,于艳艳,田洪芸,张红霞.食品安全质量检测学报),2014,5(10):3197-3202.
Yu Q,Wang Y X.J. Nanchang Univ. (喻晴,王远兴.南昌大学学报),2019,4(3):231-245.
Zhang F Y,Wu L T,Lin C,Cai D C,Wang L P,Fang L,Lin Z P.J. Chin. Anal. Lab. 张方圆,吴凌涛,林晨, 蔡大川,王李平,方丽,林泽鹏.分析试验室), 2016,35(11):1254-1258.
Jabeur H,Zribi A,Makni J,Rebai A,Abdelhedi R.Food Chem.,2014,62:4893-4904.
Quintanilla-Casas B,Bustamante J,Guardiola F,Garcia-gonzalez D L,Barbieri S,Bendini A,Toschi T G,Vichi S,Tres A.LWT-Food Sci. Technol.,2020,121(3):108396.
Mustorgi E,Malegori C,Oliveri P,Hooshyary M,Bounneche H,Mondello L,Oteri M,Casale M.Chemom. Intell. Lab. Syst.,2020,199(2020):103974.
Qi X P,Chen T,Liu P,Liu J.Food Sci. Technol. (祁兴普,陈通,刘萍,刘靖.食品科技),2019,44(8):312-321.
Lou T T,Liu C,Wang Y,Zhang H.Food Res. Dev. (娄婷婷,刘畅,王禹,章骅.食品研究与开发),2020,41(1):218-224.
Han J X,Sun R X,Chen Y,Sun C D,Wen Z G.Food Ferment Ind. (韩建勋,孙瑞雪,陈颖,孙崇德,温志刚.食品与发酵工业),2019,45(18):222-227.
Xiang Q Q,Zhang Y Q,Wang X H,Zhang X T,Huang W Y.Jiangsu J. Agric. Sci. (相倩倩, 张云权, 王小花, 张晓甜,黄文耀.江苏农业学报),2020,48(8):32-40.
Xu C H,Wang Y X.Food Sci. (徐春晖,王远兴.食品科学),2020,41 (20):141-150.
Ranamukaarachchi S A,Peiris R H,Moresoli C.Food Chem.,2017,217:469-475.
0
浏览量
4
下载量
2
CSCD
关联资源
相关文章
相关作者
相关机构