Fourier transform infrared spectroscopy and chemometrics as a tool for the rapid detection of other vegetable fats mixed in cocoa butter

Chromatographic and spectroscopic methods for the detection of cocoa butter in cocoa and its derivatives: A review

Currently, there is fierce competition in the cocoa industry to develop products that possess distinctive sensory characteristics and flavours. This is because cocoa and its derivatives provide numerous health and functional advantages, which is essential to their economics. The fatty acid and triglyceride composition of cocoa determines its quality. This review emphasises the necessity of developing precise, adaptable analytical techniques to identify and quantify cocoa butter in cocoa and its derived products, from cocoa beans to chocolate bars. Key chromatographic and spectroscopic techniques play crucial roles in understanding the fundamental principles underlying the production of cocoa with desirable flavours. This significantly impacts the sustainability, traceability, and authenticity of cocoa products while also supporting the battle against adulteration.

Regeneration of Pancreatic Cells Using Optimized Nanoparticles and l-Glutamic Acid-Gelatin Scaffolds with Controlled Topography and Grafted Activin A/BMP4

Regeneration of insulin-producing cells (IPCs) from induced pluripotent stem cells (iPSCs) under controlled conditions has a lot of promise to emulate the pancreatic mechanism in vivo as a foundation of cell-based diabetic therapy. l-Glutamic acid-gelatin scaffolds with orderly pore sizes of 160 and 200 μm were grafted with activin A and bone morphogenic proteins 4 (BMP4) to differentiate iPSCs into definitive endoderm (DE) cells, which were then guided with fibroblast growth factor 7 (FGF7)-grafted retinoic acid (RA)-loaded solid lipid nanoparticles (FR-SLNs) to harvest IPCs. Response surface methodology was adopted to optimize the l-glutamic acid-to-gelatin ratio of scaffolds and to optimize surfactant concentration and lipid proportion in FR-SLNs. Experimental results of immunofluorescence, flow cytometry, and western blots revealed that activin A (100 ng/mL)-BMP4 (50 ng/mL)-l-glutamic acid (5%)-gelatin (95%) scaffolds provoked the largest number of SOX17-positive DE cells from iPSCs. Treatment with FGF7 (50 ng/mL)-RA (600 ng/mL)-SLNs elicited the highest number of PDX1-positive β-cells from differentiated DE cells. To imitate the natural pancreas, the scaffolds with controlled topography were appropriate for IPC production with sufficient insulin secretion. Hence, the current scheme using FR-SLNs and activin A-BMP4-l-glutamic acid-gelatin scaffolds in the two-stage differentiation of iPSCs can be promising for replacing impaired β-cells in diabetic management.

Development and characterization of novel bigels based on monoglyceride-beeswax oleogel and high acyl gellan gum hydrogel for lycopene delivery

The aim of present study was to develop novel bigels as a semi-solid vehicle for lycopene delivery. Bigels were prepared by using the mixture of glycerol monostearate (GMS)-beeswax based oleogel and high acyl gellan gum hydrogel in different proportions. The confocal microscopic observations showed that the obtained bigels were oleogel-in-hydrogel, and droplets became larger with increased contents of oleogel. Higher fractions of oleogel increased the mechanical strength (storage modulus, firmness) of bigels. According to the rheological results, all bigels exhibited solid-like characteristics since the storage modulus were larger than loss modulus. DSC results showed that the melting temperature of bigel was higher than that of oleogel. During in vitro simulated gastrointestinal digestion, the total release percentages varied from 60% to 80%, and a higher content of oleogel within bigels could slower down the release of lycopene, suggesting that a higher proportion of oleogel was beneficial for delivery of fat-soluble nutraceuticals.

Distinction of Ecuadorian varieties of fermented cocoa beans using Raman spectroscopy

Cocoa (Theobroma cacao) is a crop of economic importance. In Ecuador, there are two predominant cocoa varieties: National and CCN-51. The National variety is the most demanded, since its cocoa beans are used to produce the finest chocolates. Raman measurements of fermented, dried and unpeeled cocoa beans were performed using a handheld spectrometer. Samples of the National and CCN-51 varieties were collected from different provinces and studied in this work. For each sample, 25 cocoa beans were considered and each bean was measured at 4 different spots. The most important Raman features of the spectra were assigned and discussed. The spectroscopic data were processed using chemometrics, resulting in a distinction of varieties with 91.8% of total accuracy. Differences in the average Raman spectra of cocoa beans from different sites but within the same variety can be attributed to environmental factors affecting the cocoa beans during the fermentation and drying processes.

Nuclear Magnetic Resonance (NMR) Spectroscopy For Metabolic Profiling of Medicinal Plants and Their Products

NMR spectroscopy has multidisciplinary applications, including excellent impact in metabolomics. The analytical capacity of NMR spectroscopy provides information for easy qualitative and quantitative assessment of both endogenous and exogenous metabolites present in biological samples. The complexity of a particular metabolite and its contribution in a biological system are critically important for understanding the functional state that governs the organism's phenotypes. This review covers historical aspects of developments in the NMR field, its applications in chemical profiling, metabolomics, and quality control of plants and their derived medicines, foods, and other products. The bottlenecks of NMR in metabolic profiling are also discussed, keeping in view the future scope and further technological interventions.

Infrared spectroscopy and outer product analysis for quantification of fat, nitrogen, and moisture of cocoa powder

The combination of the near infrared (NIR) and Fourier-transform infrared (FTIR) absorbance spectra (1100-2500nm and 4000-600cm(-1)) of 100 cocoa powder samples was used to build calibration models for the determination of the content of fat, nitrogen, and moisture. The samples that comprised the dataset had an average composition of 13.51% of fat, 3.77% nitrogen, and 3.98% moisture. The fat content ranged from 2.42 to 22.00%, the nitrogen from 0.88 to 4.48%, and moisture from 1.60 to 7.80%. For NIR, the relative root mean square error of cross-validation (RMSECV) was 7.0% (R(2)=0.96) for fat, 1.7% (R(2)=0.98) for nitrogen, and 5.2% (R(2)=0.94) for moisture. For FTIR, the relative RMSECV was 10.4% (R(2)=0.94) for fat and 3.9% (R(2)=0.95) for nitrogen. However, for moisture, it was not possible to build a calibration model with suitable predictability. The combination of the NIR and FTIR domains (data fusion) by outer product analysis PLS1 allowed to predict these parameters and to characterise frequencies in one domain based on the information of the other domain. This work allows to conclude that the second derivative of NIR is the recommended procedure to quantify fat, nitrogen, and moisture content in cocoa powders by infrared spectroscopy.

Measuring the metabolome: current analytical technologies

The post-genomics era has brought with it ever increasing demands to observe and characterise variation within biological systems. This variation has been studied at the genomic (gene function), proteomic (protein regulation) and the metabolomic (small molecular weight metabolite) levels. Whilst genomics and proteomics are generally studied using microarrays (genomics) and 2D-gels or mass spectrometry (proteomics), the technique of choice is less obvious in the area of metabolomics. Much work has been published employing mass spectrometry, NMR spectroscopy and vibrational spectroscopic techniques, amongst others, for the study of variations within the metabolome in many animal, plant and microbial systems. This review discusses the advantages and disadvantages of each technique, putting the current status of the field of metabolomics in context, and providing examples of applications for each technique employed.

Cluster analysis for the systematic grouping of genuine cocoa butter and cocoa butter equivalent samples based on triglyceride patterns

The triglyceride profile of cocoa butters (CBs) from different geographical origins, varieties, growing seasons, and a number of cocoa butter equivalents (CBEs) was determined by capillary gas liquid chromatography. Hierarchical cluster analysis was applied to the five main triglycerides of the samples for the ability to find natural groupings among (a) CBs of various provenance and (b) CBE samples of different types. The samples were clustered using Ward's method, and the similarity values of the linkages were represented by dendrograms. The five triglycerides contained adequate information to obtain a meaningful sample differentiation. This information can be used to assess the purity and the origin of the CB sample examined.

Investigating plant-plant interference by metabolic fingerprinting

New analytical developments in post-genomic technologies are being introduced to the field of plant ecology. FT-IR fingerprinting coupled with chemometrics via cluster analysis is proposed as a tool for correlating global metabolic changes with abiotic or biotic perturbation and/or interactions. The current study concentrates on detecting chemical responses by inter-species competition between a monocotyledon Brachypodium distachyion and a dicotyledon Arabidopsis thaliana. Growth analysis of 42 days old plants showed differences in both species under competition. Clear changes in the FT-IR metabolic fingerprints of B. distachyion in competition with A. thaliana were observed, whilst there were no apparent chemical differences in the A. thaliana plant tissues. This study demonstrates the power of this approach in detecting changes in the global metabolic profiles of plants in response to biotic interactions, and we believe FT-IR is appropriate for rapid screening (10 s per sample) prior to targeted metabolite analyses.

Assessment of 1H NMR spectroscopy and multivariate analysis as a technique for metabolite fingerprinting of Arabidopsis thaliana

An approach to metabolite fingerprinting of crude plant extracts that utilizes 1H nuclear magnetic resonance (NMR) spectroscopy and multivariate statistics has been tested. Using ecotypes of Arabidopsis thaliana as experimental material, a method has been developed for the rapid analysis of unfractionated polar plant extracts, enabling the creation of reproducible metabolite fingerprints. These fingerprints could be readily stored and compared by a variety of chemometric methods. Comparison by principal component analysis using SIMCA-P allowed the generation of residual NMR spectra of the compounds that contributed significantly to the differences between samples. From these plots, conclusions were drawn with respect to the identity and relative levels of metabolites differing between samples.