امکان سنجی کاربرد طیف سنج تحرک یونی در تلفیق با روش‌های ‏شیمی سنجی در تشخیص رنگ‌های سنتزی در آب آلبالو و زرشک‎ ‎‏‌‏

این مطالعه با هدف استفاده از طیف‌سنج تحرک یونی مجهز به سامانه یونیزاسیون تخلیه کرونا (‏ims-cdi‏) همراه با روش‌های ‏شیمی سنجی برای تشخیص تقلب در آب آلبالو و زرشک با سه رنگ مصنوعی رایج شامل آلورا قرمز، پونسو ‏‎4r‎‏ و کارموزین انجام ‏شد. ابتدا دمای محفظه‌ی تزریق، دمای محفظه‌ی رانش، پالس دروازه یونی، سرعت جریان گاز حامل و سرعت جریان گاز رانش به ‏ترتیب روی ‏c˚ 260 (به جز ‏c˚ 200 برای رنگ‌ها)، ‏c˚ 180 (به جز ‏c˚ 200 برای آب آلبالو)، 60 میکروثانیه، 200 و 900 میلی ‏لیتر در دقیقه تنظیم گردید. ابتدا طیف ‏ims‏ آب میوه‌های خالص و رنگ‌های مصنوعی ثبت گردید. تجزیه و تحلیل مولفه اصلی، ‏‎ ‎الگوهای منطقی را برای تمایز بین آب میوه ها و رنگ‌ها از یکدیگر ارائه کرد. این تفکیک معتبر و قابل اعتماد بود زیرا 91.15 % از ‏کل واریانس داده‌های جمع‌آوری‌شده توسط سه مولفه‌ی اول توصیف شد. آب زرشک خالص و آلبالو به صورت جداگانه با نسبت‌های ‏مختلف (10، 30 و 50 درصد وزنی/وزنی) با هر یک از رنگ‌های مصنوعی مخلوط شدند و طیف های تحرک یونی آن‌ها ثبت گردید. ‏افزون رنگ‌های مصنوعی با تغییرات مشخص در طیف ‏ims‏ نمونه‌های آب میوه همراه بود. داده‌های طیفی نمونه‌های تقلبی به ‏روش‌های مختلف تجزیه و تحلیل داده‌های چند متغیره مورد بررسی قرار گرفتند. نقاط مشخص مختلفی با استفاده از شاخص ‏تعیین متغیرهای مهم در مدلسازی به عنوان ویژگی‌های متمایز برای ساخت مدل‌های رگرسیونی حداقل مربعات جزئی برای پیش ‏بینی نسبت‌های مختلف از تقلبات افزوده شده، انتخاب شدند. کارایی پیش بینی مدل‌ها در شناسایی کمی مقادیر تقلبات رنگی ‏افزوده شده به نمونه‌های آب زرشک و آب آلبالو براساس مقادیر ضریب تبیین در سه حالت درجه بندی، اعتبار سنجی متقابل، و ‏آزمون و هم چنین بر اساس مقادیر خطای میانگین ریشه مربعات در سه حالت درجه بندی، اعتبارسنجی متقابل و آزمون تعیین ‏گردید.

feasibility of utilizing ion mobility spectrometry combined with chemometric methods to detect synthetic colorants in cherry and barberry juices

introduction: color is a key organoleptic attribute that significantly influences consumers' acceptance and preference for foods. however, synthetic colorants have been linked to various adverse effects, including toxicity, allergic reactions, and behavioral and neurocognitive disturbances. many commercially available fruit juices may contain synthetic colorants, raising serious health concerns for consumers. red fruit juices, such as cherry and barberry juices, have garnered considerable consumer interest in recent years due to their vibrant color, rich phytochemical content, and associated health benefits. however, these juices are highly susceptible to adulteration with artificial colorants, especially when produced and distributed through retail channels. consequently, there is an increasing demand for rapid, efficient techniques with minimal sample preparation to detect and identify such adulterations accurately. this study proposes utilizing spectral fingerprints generated by ion mobility spectrometry (ims) combined with multivariate data analysis as an accessible and efficient method for detecting the adulteration of cherry and barberry juices with various synthetic colorants, including allura red, ponceau 4r, and carmoisine.material and methods: the experimental conditions were optimized, including the injection port temperature (170–230°c), drift tube temperature (140–200°c), ion shutter pulse width (40–100 μs), carrier gas flow rate (50–150 ml/min), and drift gas flow rate (500–900 ml/min). subsequently, pure and natural juices, along with synthetic colorants, were diluted with water, analyzed using ims, and a comprehensive data set was collected. pure barberry and cherry juices were adulterated with varying proportions (10%, 30%, and 50% w/w) of the specified synthetic colorants. a total of 90 adulterated samples for each juice were analyzed using various multivariate data processing techniques, including principal component analysis (pca) and partial least squares regression (plsr). plsr was applied to the pretreated ims spectra to develop predictive models for quantifying the contents of allura red, ponceau 4r, and carmoisine in each juice. following calibration, an independent data set (30% of the spectral data) was used to evaluate the performance of the optimized plsr models. the accuracy of these models was assessed using the coefficient of multiple determination for calibration (r²c), cross-validation (r²cv), and testing (r²test). additionally, the root mean square error (rmse) was calculated for the calibration set (rmsec), cross-validation set (rmsecv), and test set (rmsetest). the best plsr model was identified based on the lowest rmsecv and the highest r²cv values, indicating optimal predictive performance.results and discussion: the injection port temperature, drift tube temperature, ion shutter pulse width, carrier gas flow rate, and drift gas flow rate were optimized and set at 260 °c (except 200 °c for colorants), 180 °c (except 200 °c for cherry juice), 60 μs, 200 ml/min, and 900 ml/min, respectively. each juice and synthetic colorant exhibited distinct ion mobility spectra, with the spectral fingerprints of the juices showing significant changes as the adulteration ratio increased. principal component analysis (pca) demonstrated effective discrimination patterns, enabling differentiation between the juices and between barberry juice and synthetic colorants. this discrimination was both valid and reliable, as 91.15% of the total variance in the collected data was explained by the first three principal components (pcs), with 77.67% attributed to the 1st pc, 9.17% to the 2nd pc, and 4.31% to the 3rd pc. additionally, distinctive characteristic ions were identified using the variable importance in projection (vip > 1) method, which were then used as discriminative features to develop the partial least squares regression (plsr) model for the adulterated juices. furthermore, good results were obtained for predicting the adulteration ratio using plsr. the models developed to quantify the levels of the colorant allura red in barberry juice demonstrated the best performance, with the r2cv ≥ 0.704 and the rmsecv ≤ 10.44%. moreover, for the test set mixtures of juice and synthetic colorants, the root mean square error (rmse) ranged from 11.05% to 13.19%, and the coefficient of multiple determination (r2r^2r2) values ranged from 0.548 to 0.793.conclusion: the ims-cdi+ technology, combined with chemometric tools such as pca and vip-plsr, proved to be an effective approach for detecting various synthetic colorants in cherry and barberry fruit juices, as well as for assessing quality and quantifying potential adulterations. as a result, it presents a robust and reliable alternative to traditional methods for detecting adulteration in fruit juices, delivering results in just a few milliseconds with minimal sample preparation.