Single Origin Coffee Aroma: From Optimized Flavor Protocols and Coffee Customization to Instrumental Volatile Characterization and Chemometrics

In this study, the aroma profile of 10 single origin Arabica coffees originating from eight different growing locations, from Central America to Indonesia, was analyzed using Headspace SPME-GC-MS as the analytical method. Their roasting was performed under temperature–time conditions, customized for each sample to reach specific sensory brew characteristics in an attempt to underline the customization of roast profiles and implementation of separate roastings followed by subsequent blending as a means to tailor cup quality. A total of 138 volatile compounds were identified in all coffee samples, mainly furan (~24–41%) and pyrazine (~25–39%) derivatives, many of which are recognized as coffee key odorants, while the main formation mechanism was the Maillard reaction. Volatile compounds’ composition data were also chemometrically processed using the HCA Heatmap, PCA and HCA aiming to explore if they meet the expected aroma quality attributes and if they can be an indicator of coffee origin. The desired brew characteristics of the samples were satisfactorily captured from the volatile compounds formed, contributing to the aroma potential of each sample. Furthermore, the volatile compounds presented a strong variation with the applied roasting conditions, meaning lighter roasted samples were efficiently differentiated from darker roasted samples, while roasting degree exceeded the geographical origin of the coffee. The coffee samples were distinguished into two groups, with the first two PCs accounting for 73.66% of the total variation, attributed mainly to the presence of higher quantities of furans and pyrazines, as well as to other chemical classes (e.g., dihydrofuranone and phenol derivatives), while HCA confirmed the above results rendering roasting conditions as the underlying criterion for differentiation.     

Micro-Raman Spectroscopy and X-ray Diffraction Analyses of the Core and Shell Compartments of an Iron-Rich Fulgurite

Fulgurites are naturally occurring structures that are formed when lightning discharges reach the ground. In this investigation, the mineralogical compositions of core and shell compartments of a rare, iron-rich fulgurite from the Mongolian Gobi Desert were investigated by X-ray diffraction and micro-Raman spectroscopy. The interpretation of the Raman data was helped by chemometric analysis, using both multivariate curve resolution (MCR) and principal component analysis (PCA), which allowed for the fast identification of the minerals present in each region of the fulgurite. In the core of the fulgurite, quartz, microcline, albite, hematite, and barite were first identified based on the Raman spectroscopy and chemometrics analyses. In contrast, in the shell compartment of the fulgurite, the detected minerals were quartz, a mixture of the K-feldspars orthoclase and microcline, albite, hematite, and goethite. The Raman spectroscopy results were confirmed by X-ray diffraction analysis of powdered samples of the two fulgurite regions, and are consistent with infrared spectroscopy data, being also in agreement with the petrographic analysis of the fulgurite, including scanning electron microscopy with backscattering electrons (SEM-BSE) and scanning electron microscopy with energy dispersive X-ray (SEM-EDX) data. The observed differences in the mineralogical composition of the core and shell regions of the studied fulgurite can be explained by taking into account the effects of both the diffusion of the melted material to the periphery of the fulgurite following the lightning and the faster cooling at the external shell region, together with the differential properties of the various minerals. The heavier materials diffused slower, leading to the concentration in the core of the fulgurite of the iron and barium containing minerals, hematite, and barite. They first underwent subsequent partial transformation into goethite due to meteoric water within the shell of the fulgurite. The faster cooling of the shell region kinetically trapped orthoclase, while the slower cooling in the core area allowed for the extensive formation of microcline, a lower temperature polymorph of orthoclase, thus justifying the prevalence of microcline in the core and a mixture of the two polymorphs in the shell. The total amount of the K-feldspars decreases only slightly in the shell, while quartz and albite appeared in somewhat larger amounts in this compartment of the fulgurite. On the other hand, at the surface of the fulgurite, barite could not be stabilized due to sulfate lost (in the form of SO₂ plus O₂ gaseous products). The conjugation of the performed Raman spectroscopy experiments with the chemometrics analysis (PCA and, in particular, MCR analyses) was shown to allow for the fast identification of the minerals present in the two compartments (shell and core) of the sample. This way, the XRD experiments could be done while knowing in advance the minerals that were present in the samples, strongly facilitating the data analysis, which for compositionally complex samples, such as that studied in the present investigation, would have been very much challenging, if possible.     

利用显微拉曼光谱结合化学计量学检验包装物中的毒品

利用显微拉曼光谱对包装物中的常见毒品进行了检验,分别分析了同种包装物中的五种常见毒品,以及同种毒品在物证袋、塑料袋、半透明文件夹、玻璃片、牛皮纸袋等五种不同的包装物中的拉曼光谱.并测量了硅片上的毒品样品粉末作为对照.实验结果表明,通过将激光光斑聚焦于包装物中的毒品,可以通过其特征峰对毒品的种类进行识别,但是需要排除28...     

化学计量学在毒物化学归因中的应用

近十年来,化学计量学方法与分析技术相结合,对样品进行了表征和鉴别,产生了信息量大、代表性强的样品检测方法.在法医学案件鉴定处理中,使用这些新技术和数学/统计学方法,可获得统计可信度的结果,从而有助于法医学案件以及毒性化合物中毒事件的追踪溯源.该文对毒物检测中使用的化学计量学方法进行了详细讨论,对其优缺点进行了比较总结,...     

Application of a genomic model for high‐dimensional chemometric analysis

The rapid development of new technologies for large‐scale analysis of genetic variation in the genomes of individuals and populations has presented statistical geneticists with a grand challenge to develop efficient methods for identifying the small proportion of all identified genetic polymorphisms that have effects on traits of interest. To address such a “large p small n” problem, we have developed a heteroscedastic effects model (HEM) that has been shown to be powerful in high‐throughput genetic analyses. Here, we describe how this whole‐genome model can also be utilized in chemometric analysis. As a proof of concept, we use HEM to predict analyte concentrations in silage using Fourier transform infrared spectroscopy signals. The results show that HEM often outperforms the classic methods and in addition to this presents a substantial computational advantage in the analyses of such high‐dimensional data. The results thus show the value of taking an interdisciplinary approach to chemometric analysis and indicate that large‐scale genomic models can be a promising new approach for chemometric analysis that deserve to be evaluated more by experts in the field. The software used for our analyses is freely available as an R package at http://cran.r‐project.org/web/packages/bigRR/ . Copyright © 2014 John Wiley & Sons, Ltd.     

QSAR‐based targeting anaplastic lymphoma kinase (ALK) variants with noncognate inhibitors in pediatric acute lymphoblastic leukemia

Human anaplastic lymphoma kinase (ALK) is a potential target for the treatment of pediatric acute lymphoblastic leukemia. However, a number of residue mutations in ALK kinase domain have been observed to cause drug resistance in pediatric acute lymphoblastic leukemia chemotherapy. Here, a chemometrics quantitative structure‐activity relationship predictor was developed using a structure‐based panel of kinase‐inhibitor activity data. The predictor was validated rigorously through internal cross‐validation and external blind test to ensure its statistical reliability, which was then used to computationally construct a systematic activity profile of 13 noncognate kinase inhibitors against both wild‐type ALK^wt and cancer‐related variants ALK^vt. It is revealed that most noncognate inhibitors exhibit weak potency on ALK^wt, but some of them are able to selectively target ALK^vt over ALK^wt. The chemometrics findings were then evaluated by using a kinase inhibition protocol; results showed that few noncognate inhibitors are 2‐ to 5‐fold higher potent against ALK variant than wild‐type kinase.     

An innovative impurity profiling of esmolol hydrochloride injection using UPLC-MS based multiple mass defect filter,chemometrics and in-silico toxicity prediction

Esmolol hydrochloride injection is indicated for the rapid control of ventricular rate in patients with atrial fibrillation or atrial flutter in perioperative, postoperative, or other emergent circumstances where short term control of ventricular rate with a short-acting agent is desirable. The potential toxic impurities in pharmaceuticals at micro levels or trace levels are of increasing concern to both pharmaceutical industries and regulatory agencies, due to their potential risk to human health. The impurity investigation of esmolol   remains incomplete. Thereby, efficient impurities monitoring and potential toxicity assessment should be emphasized to assure drug safety. Impurity profiling methods of esmolol were developed using ultraperformance liquid chromatography plus Q-Exactive Orbitrap tandem mass spectrometry (UPLC-QE-MS) based multiple mass defect filter and chemometrics. Impurities were characterized by both UPLC-QE-MS and reference substance comparison. The toxicities of esmolol impurities were predicted by employing quantitative structure–activity relationship. The results showed that a total of 20 impurities were detected and identified using the above integrated strategy, 14 impurities (EP2-3, EP5-6, EP8-9, EP12-13, EP15-20) have firstly found. EP20 was predicted as hepatotoxic and mutagenic using QSAR model, and its hepatotoxicity were verified in vivo. The EP1 contents showed maximum volatility in all batches, and varied by sample. EP1 and its accompanying product of methanol were measured. This UPLC-MS/MS based chemometrics strategy is useful for monitoring the manufacturing process and quality control of esmolol hydrochloride injection.