發(fā)布時(shí)間：2018-10-30 13:05

【摘要】：近幾年,農(nóng)產(chǎn)品安全問題越來越備受人們的關(guān)注,重金屬污染是其中之一,重金屬進(jìn)入人體后不易排出,長期積累會(huì)嚴(yán)重影響人們的身體健康。食用植物油是人們的日常用品,且每日消耗量巨大,因此,加強(qiáng)食用油中重金屬的監(jiān)測和檢測具有非常重大的意義。激光誘導(dǎo)擊穿光譜(LIBS)技術(shù)因具有快速、實(shí)時(shí)、在線、多種元素同時(shí)檢測等優(yōu)點(diǎn),本文利用LIBS技術(shù)研究植物油中的重金屬鉛和鉻的光譜特性,并結(jié)合不同的分析方法對(duì)其進(jìn)行定量分析,主要研究內(nèi)容及結(jié)果如下:應(yīng)用單、雙脈沖LIBS技術(shù)對(duì)大豆油中的Pb元素進(jìn)行檢測,其中鉛含量范圍在17.63~770.73 ppm。研究中采用木片作為Pb的富集基體,經(jīng)LIBS實(shí)驗(yàn)后,比較了單、雙脈沖LIBS技術(shù)的性能。結(jié)果表明,雙脈沖LIBS技術(shù)的綜合性能(譜線強(qiáng)度、穩(wěn)定性、靈敏性、檢測限)優(yōu)于單脈沖;然后,使用雙脈沖采集的光譜數(shù)據(jù)對(duì)大豆油中的Pb元素含量進(jìn)行定量分析。結(jié)果表明,采用多元線性回歸模型得到的建模樣本平均相對(duì)誤差為7.25%,三個(gè)驗(yàn)證樣品的預(yù)測相對(duì)誤差分別為5.05%、5.75%和0.13%。應(yīng)用共軸雙脈沖LIBS技術(shù)對(duì)三種植物油中的重金屬Cr進(jìn)行定量分析,其中Cr含量范圍在11.98~139.83 ppm。首先,采用CN分子線、Ca原子線及(CN+Ca)譜線強(qiáng)度之和為內(nèi)標(biāo)線建立Cr含量的定標(biāo)模型。結(jié)果表明,采用雙譜線內(nèi)標(biāo)法效果最佳,大豆油、花生油和玉米油建立的定標(biāo)曲線擬合度R2分別為0.995、0.992和0.996,兩個(gè)驗(yàn)證樣品的平均預(yù)測相對(duì)誤差分別為7.27%、7.62%和6.46%;其次,分別對(duì)兩種不同品牌的混合大豆油、花生油、玉米油進(jìn)行建模預(yù)測,利用三條Cr的原子譜線和兩條基體元素譜線(CN分子線和Ca原子線)分別建立Cr的三變量和五變量的最小二乘支持向量機(jī)(LS-SVM)定標(biāo)模型,并對(duì)其進(jìn)行預(yù)測。結(jié)果表明,引入基體元素的五變量LS-SVM模型性能更佳,驗(yàn)證樣品的平均預(yù)測相對(duì)誤差分別為7.46%、8.96%和8.95%。研究表明,LIBS技術(shù)檢測植物油中的Pb和Cr元素具有一定的可行性,LIBS技術(shù)結(jié)合多元線性回歸法、雙譜線內(nèi)標(biāo)法和LS-SVM法能有效降低實(shí)驗(yàn)參數(shù)和基體效應(yīng)對(duì)分析元素的干擾,從而提高定標(biāo)曲線的擬合度以及減小定量分析誤差。
[Abstract]:In recent years, people pay more and more attention to the safety of agricultural products. Heavy metal pollution is one of them, heavy metals are difficult to be discharged after entering human body, long-term accumulation will seriously affect the health of people. Edible vegetable oil is the daily necessities of people, and the daily consumption is huge. Therefore, it is of great significance to strengthen the monitoring and detection of heavy metals in edible oils. Laser induced breakdown spectroscopy (LIBS) has the advantages of fast, real-time, on-line and simultaneous detection of many elements. In this paper, the spectral characteristics of heavy metals lead and chromium in vegetable oil are studied by LIBS. The main contents and results are as follows: single and double pulse LIBS were used to detect Pb elements in soybean oil, and lead content was in the range of 17.63 ~ 770.73 ppm.. In this study, wood chips were used as the enriched matrix of Pb. After LIBS experiments, the properties of single and double pulse LIBS were compared. The results showed that the comprehensive performance (spectral intensity, stability, sensitivity, detection limit) of double pulse LIBS was better than that of single pulse, and then the content of Pb elements in soybean oil was quantitatively analyzed by using the spectral data collected by double pulse. The results show that the average relative error of the modeling sample is 7.25 and the prediction relative error of the three validated samples is 5.05 5.75% and 0.13% respectively. The quantitative analysis of heavy metal Cr in three kinds of vegetable oils by coaxial bipulse LIBS technique was carried out. The range of Cr content was 11.98 ~ 139.83 ppm.. Firstly, the calibration model of Cr content is established by using the sum of the intensity of CN molecular line, Ca atomic line and (CN Ca) line. The results showed that the calibration curve fitted to soybean oil, peanut oil and corn oil was 0.992 and 0.996 for soybean oil, peanut oil and corn oil, respectively, and the average prediction error was 7.27, respectively. 7.62% and 6.46%; Secondly, two different brands of mixed soybean oil, peanut oil and corn oil were modeled and predicted. Three atomic lines of Cr and two lines of matrix elements (CN molecular line and Ca atomic line) were used to establish the three-variable and five-variable least squares support vector machine (LS-SVM) calibration models of Cr, respectively, and to predict them. The results show that the five-variable LS-SVM model with matrix elements has better performance and the average relative error of prediction is 7.46% 8.96% and 8.95% respectively. The results show that LIBS technique is feasible for the detection of Pb and Cr elements in vegetable oil. LIBS technique combined with multivariate linear regression method, double spectral line internal standard method and LS-SVM method can effectively reduce the interference of experimental parameters and matrix effect on the analysis elements. Thus, the fitting degree of calibration curve is improved and the error of quantitative analysis is reduced.
【學(xué)位授予單位】：江西農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TS227;O657.31

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