粮油食品科技
糧油食品科技
량유식품과기
Science and Technology of Cereals, Oils and Foods
2015年
6期
84-88
,共5页
可见-近红外光谱%花生油掺伪%定性鉴别%定量分析
可見-近紅外光譜%花生油摻偽%定性鑒彆%定量分析
가견-근홍외광보%화생유참위%정성감별%정량분석
visible -near infrared spectroscopy%adulterate peanut oil%qualitative identification%quanti-tative analysis
为了建立一种简便有效的花生油掺伪的定性和定量鉴别方法，采集花生油中分别掺伪0～90％大豆油、棕榈油和棉籽油样品的可见—近红外光谱图，结合主成分分析、判别分析、改进偏最小二乘法，建立花生油掺伪的定性鉴别和定量预测模型。结果表明，在定性鉴别中，对花生油中分别掺入大豆油、棕榈油和棉籽油的整体正确判别率分别达到了100％、96．1％和85．3％。在定量分析中，对 MPLS 法建立的花生油二元掺伪定标模型进行验证，结果表明，掺入大豆油、棉籽油和棕榈油的预测相关系数 R2p 分别为0．998、0．997和0．995，相对标准差 RSD 分别为2．33％、3．04％和3．83％，相对分析误差 RPD 分别为3．542、2．642和2．581，说明这三种掺假花生油所建立的最优定标模型的预测精度高，其中花生油中掺入大豆油的预测精度最高，检测花生油中掺入棉籽油与棕榈油的最低掺假量为3％。为花生油二元掺伪模式提供了一种简便、快速、有效的分析方法。
為瞭建立一種簡便有效的花生油摻偽的定性和定量鑒彆方法，採集花生油中分彆摻偽0～90％大豆油、棕櫚油和棉籽油樣品的可見—近紅外光譜圖，結閤主成分分析、判彆分析、改進偏最小二乘法，建立花生油摻偽的定性鑒彆和定量預測模型。結果錶明，在定性鑒彆中，對花生油中分彆摻入大豆油、棕櫚油和棉籽油的整體正確判彆率分彆達到瞭100％、96．1％和85．3％。在定量分析中，對 MPLS 法建立的花生油二元摻偽定標模型進行驗證，結果錶明，摻入大豆油、棉籽油和棕櫚油的預測相關繫數 R2p 分彆為0．998、0．997和0．995，相對標準差 RSD 分彆為2．33％、3．04％和3．83％，相對分析誤差 RPD 分彆為3．542、2．642和2．581，說明這三種摻假花生油所建立的最優定標模型的預測精度高，其中花生油中摻入大豆油的預測精度最高，檢測花生油中摻入棉籽油與棕櫚油的最低摻假量為3％。為花生油二元摻偽模式提供瞭一種簡便、快速、有效的分析方法。
위료건립일충간편유효적화생유참위적정성화정량감별방법，채집화생유중분별참위0～90％대두유、종려유화면자유양품적가견—근홍외광보도，결합주성분분석、판별분석、개진편최소이승법，건립화생유참위적정성감별화정량예측모형。결과표명，재정성감별중，대화생유중분별참입대두유、종려유화면자유적정체정학판별솔분별체도료100％、96．1％화85．3％。재정량분석중，대 MPLS 법건립적화생유이원참위정표모형진행험증，결과표명，참입대두유、면자유화종려유적예측상관계수 R2p 분별위0．998、0．997화0．995，상대표준차 RSD 분별위2．33％、3．04％화3．83％，상대분석오차 RPD 분별위3．542、2．642화2．581，설명저삼충참가화생유소건립적최우정표모형적예측정도고，기중화생유중참입대두유적예측정도최고，검측화생유중참입면자유여종려유적최저참가량위3％。위화생유이원참위모식제공료일충간편、쾌속、유효적분석방법。
Visible -Near infrared spectra of peanut oil adulterated respectively with soybean oil,palm oil and cottonseed oil in different proportion (V /V)from 0 to 90% were collected and analyzed to seek an effective and simple method for qualitative and quantitative detection of peanut oil adulteration.The result showed that in the qualitative identification the correct rate of the peanut oil mixed with soybean oil,palm oil and cottonseed oil was 100%,96.1% and 85.3%,respectively.In the quantitative analysis,the peanut oil binary adulteration calibration model established using modified partial least square (MPLS) was validated.The result showed that the correlation coefficients of cross validation for three kinds of models were 0.998,0.997 and 0.995 respectively;the relative standard deviation were 2.327%, 3.040% and 3.830%,respectively;the relative percent deviation were 3.542,2.642 and 2.581,re-spectively.The results indicated that NIR technique can be used as an effective method for quality control and adulteration identification of peanut oil,the prediction accuracy of soybean oil adulteration was high-est,and the adulteration content of palm oil and cottonseed oil above 3% can be accurately predicted by these models.This result can supply a simple,rapid and effective method for identifying the adulterated binary system of peanut oil.
