本文選題：拉曼光譜技術(shù) + 頭孢菌素類抗生素��； 參考：《天津大學(xué)》2014年碩士論文

【摘要】：抗生素是目前應(yīng)用最廣泛的預(yù)防和治療感染性疾病的藥物，在醫(yī)療和畜牧業(yè)上起著不可替代的作用。我國(guó)是抗生素生產(chǎn)和使用的大國(guó)，人均消費(fèi)量高達(dá)其他國(guó)家的10倍。水體或食物中的抗生素殘留通過(guò)食物鏈進(jìn)入人體，對(duì)人類的健康構(gòu)成了嚴(yán)重威脅，發(fā)展快速準(zhǔn)確的抗生素殘留檢測(cè)方法具有重要意義。拉曼光譜技術(shù)是基于拉曼散射效應(yīng)的分子結(jié)構(gòu)表征技術(shù)，以其快速無(wú)損、無(wú)需樣品制備、適用于水溶液樣品等優(yōu)點(diǎn)被迅速應(yīng)用于檢測(cè)分析領(lǐng)域。 本文研究了拉曼光譜技術(shù)的特征及其應(yīng)用于抗生素檢測(cè)的優(yōu)勢(shì)，拉曼散射效應(yīng)的原理以及利用拉曼光譜技術(shù)進(jìn)行定量和定性分析的原理，光譜數(shù)據(jù)預(yù)處理方法和多元校正方法應(yīng)用于拉曼光譜分析的原理。通過(guò)科研型拉曼光譜儀和多元校正方法進(jìn)行了三種頭孢菌素類抗生素頭孢曲松、頭孢噻肟鈉和頭孢唑林鈉三元混合溶液的拉曼光譜檢測(cè)和定量分析。 本文分別測(cè)量了頭孢曲松、頭孢噻肟鈉和頭孢唑林鈉三種抗生素的固體和溶液的拉曼光譜，扣除背景提取特征拉曼光譜，并進(jìn)行了頭孢類抗生素的拉曼特征峰振動(dòng)模式解析。本文利用拉曼光譜技術(shù)對(duì)三種抗生素的混合溶液進(jìn)行分析，基于正交實(shí)驗(yàn)設(shè)計(jì)方法建立了用于數(shù)據(jù)分析的校正集和預(yù)測(cè)集，研究了不同預(yù)處理方法對(duì)該混合溶液體系的偏最小二乘模型性能的影響。 本文對(duì)頭孢曲松、頭孢噻肟鈉和頭孢唑林鈉三種抗生素混合溶液的拉曼光譜體系進(jìn)行了定量分析研究。通過(guò)各種預(yù)處理方法，包括剔除樣本集中的奇異樣本，提取光譜中的特征變量，，預(yù)處理校正等方面，對(duì)模型進(jìn)行優(yōu)化和改進(jìn)，分析模型的參數(shù)和結(jié)果得出最優(yōu)的預(yù)處理方法。利用最優(yōu)模型可以實(shí)現(xiàn)對(duì)外部未知樣本的預(yù)測(cè)分析。 本文介紹的方法改進(jìn)了現(xiàn)有的光譜數(shù)據(jù)預(yù)處理方法，建立了穩(wěn)定的校正模型，可以實(shí)現(xiàn)快速、同時(shí)檢測(cè)抗生素混合溶液中各組分的濃度。
[Abstract]:Antibiotics are the most widely used drugs for the prevention and treatment of infectious diseases, which play an irreplaceable role in medicine and animal husbandry. China is a large country producing and using antibiotics, per capita consumption is 10 times higher than other countries. Antibiotic residues in water or food enter the human body through the food chain, which poses a serious threat to human health. It is of great significance to develop a rapid and accurate method for the detection of antibiotic residues. Raman spectroscopy is a molecular structure characterization technique based on Raman scattering effect, which is rapidly applied in the field of detection and analysis because of its advantages of fast nondestructive, no sample preparation, and suitable for aqueous solution samples. In this paper, the characteristics of Raman spectroscopy and its advantages in antibiotic detection, the principle of Raman scattering effect and the principle of quantitative and qualitative analysis using Raman spectroscopy are studied. Spectral data preprocessing method and multivariate correction method are applied to the principle of Raman spectrum analysis. Three kinds of cephalosporins, ceftriaxone, cefotaxime sodium and cefazolin sodium ternary mixed solution were detected and quantitatively analyzed by Raman spectrometer and multivariate correction method. In this paper, the Raman spectra of ceftriaxone, cefotaxime sodium and cefazolin sodium were measured, the characteristic Raman spectra of ceftriaxone, cefotaxime sodium and cefazolin sodium were subtracted from the background characteristic Raman spectra, and the vibrational mode of characteristic Raman peaks of ceftriaxone antibiotics were analyzed. In this paper, Raman spectroscopy was used to analyze the mixed solution of three antibiotics. Based on the orthogonal experimental design method, the calibration set and prediction set for data analysis were established. The effects of different pretreatment methods on the performance of the partial least squares model of the mixed solution system were studied. The Raman spectra of ceftriaxone, cefotaxime sodium and cefazolin sodium were studied quantitatively. The model is optimized and improved by various preprocessing methods, including eliminating the singular samples in the sample set, extracting the characteristic variables in the spectrum and preprocessing correction. The optimal pretreatment method is obtained by analyzing the parameters and results of the model. The optimal model can be used to predict and analyze external unknown samples. The method introduced in this paper improves the existing spectral data pretreatment methods and establishes a stable calibration model which can be used to detect the concentration of each component in the mixed antibiotic solution.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：R917;O657.37

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本文編號(hào)：2061973