Identification of Adulterated Cocoa Powder Using Chromatographic Fingerprints of Polysaccharides Coupled with Principal Component Analysis

Detection and quantification of cocoa powder adulteration using Vis-NIR spectroscopy with chemometrics approach

The rising demand for cocoa powder has resulted in an upsurge in market prices, leading to the emergence of adulteration practices aimed at achieving economic benefits. This study aimed to detect and quantify cocoa powder adulteration using visible and near-infrared spectroscopy (Vis-NIRS). The adulterants used in this study were powdered carob, cocoa shell, foxtail millet, soybean, and whole wheat. The NIRS data could not be resolved using Savitzky-Golay smoothing. Nevertheless, the application of a random forest and support vector machine successfully classified the samples with 100% accuracy. Quantification of adulteration using partial least squares (PLS), Lasso, Ridge, elastic Net, and RF regressions provided R2 higher than 0.96 and root mean square error <2.6. Coupling PLS with the Boruta algorithm produced the most reliable regression model (R2 = 1, RMSE = 0.0000). Finally, an online application was prepared to facilitate the determination of adulterants in the cocoa powder.

Assessment of Peanut Protein Powder Quality by Near-Infrared Spectroscopy and Generalized Regression Neural Network-Based Approach

The global demand for protein is on an upward trajectory, and peanut protein powder has emerged as a significant player, owing to its affordability and high quality, with great future market potential. However, the industry currently lacks efficient methods for rapid quality testing. This research paper addressed this gap by introducing a portable device with employed near-infrared spectroscopy (NIR) to quickly assess the quality of peanut protein powder. The principal component analysis (PCA), partial least squares (PLS), and generalized regression neural network (GRNN) methods were used to construct the model to further enhance the accuracy and efficiency of the device. The results demonstrated that the newly established NIR method with PLS and GRNN analysis simultaneously predicted the fat, protein, and moisture of peanut protein powder. The GRNN model showed better predictive performance than the PLS model, the correlation coefficient in calibration (Rcal) of the fat, the protein, and the moisture of peanut protein powder were 0.995, 0.990, and 0.990, respectively, and the residual prediction deviation (RPD) were 10.82, 10.03, and 8.41, respectively. The findings unveiled that the portable NIR spectroscopic equipment combined with the GRNN method achieved rapid quantitative analysis of peanut protein powder. This advancement holds a significant application of this device for the industry, potentially revolutionizing quality testing procedures and ensuring the consistent delivery of high-quality products to fulfil consumer desires.

An introductory review on the application of principal component analysis in the data exploration of the chemical analysis of food samples

Principal component analysis (PCA) is currently one of the most used multivariate data analysis techniques for evaluating information from food analysis. In this review, a brief introduction to the theoretical principles that underlie PCA will be given, in addition to presenting the most commonly used computer programs. An example from the literature was discussed to illustrate the use of this chemometric tool and interpretation of graphs and parameters obtained. A list of recently published articles will also be presented, in order to show the applicability and potential of the technique in the food analysis field.

Handheld and benchtop vis/NIR spectrometer combined with PLS regression for fast prediction of cocoa shell in cocoa powder

The fermented and dried cocoa beans are peeled, either before or after the roasting process, as peeled nibs are used for chocolate production, and shell content in cocoa powders may result from economically motivated adulteration (EMA), cross-contamination or misfits in equipment in the peeling process. The performance of this process is carefully evaluated, as values above 5% (w/w) of cocoa shell can directly affect the sensory quality of cocoa products. In this study chemometric methods were applied to near-infrared (NIR) spectra from a handheld (900-1700 nm) and a benchtop (400-1700 nm) spectrometers to predict cocoa shell content in cocoa powders. A total of 132 binary mixtures of cocoa powders with cocoa shell were prepared at several proportions (0 to 10% w/w). Partial least squares regression (PLSR) was used to develop the calibration models and different spectral preprocessing were investigated to improve the predictive performance of the models. The ensemble Monte Carlo variable selection (EMCVS) method was used to select the most informative spectral variables. Based on the results obtained with both benchtop (R²_P = 0.939, RMSE_P = 0.687% and RPD_P = 4.14) and handheld (R²_P = 0.876, RMSE_P = 1.04% and RPD_P = 2.82) spectrometers, NIR spectroscopy combined with the EMCVS method proved to be a highly accurate and reliable tool for predicting cocoa shell in cocoa powder. Even with a lower predictive performance than the benchtop spectrometer, the handheld spectrometer has potential to specify whether the amount of cocoa shell present in cocoa powders is in accordance with the Codex Alimentarius specifications.

Multiple fingerprint profiles and chemometrics analysis of polysaccharides from Sarcandra glabra

Multiple techniques including high performance size-exclusion chromatography (HPSEC), Fourier-transform infrared spectroscopy (FT-IR) and pre-column derivatization high-performance liquid chromatography (PCD-HPLC) were applied to the fingerprint analysis of the polysaccharides from Sarcandra glabra (SGPs) in different regions. Chemometrics was used to evaluate the similarity and differences of SGPs from different regions based on their fingerprints. The results of the present study showed that polysaccharides from 18 batches of Sarcandra glabra had a high degree of similarity based on the HPSEC, PCD-HPLC, and FT-IR fingerprints. The samples from different regions could be classified by clustering analysis based on their nuances. The five monosaccharides (Gal, Rha, Xyl, GlcA, and Glc) and the wavelengths of FT-IR (3371 cm^-1 and 1411 cm^-1) could be selected as herb markers for the quality control of Sarcandra glabra.

Chromatographic fingerprinting as a strategy to identify regulated plants in illegal herbal supplements

Erectile dysfunction (ED) is a sexual disorder characterized by the inability to achieve or maintain a sufficiently rigid erection. Despite the availability of non-invasive oral treatment options, many patients turn to herbal alternatives. Furthermore, herbal supplements are increasingly gaining popularity in industrialized countries and, as a consequence, quality control is a highly important issue. Unfortunately, this is not a simple task since plants are often crushed and mixed with other plants, which complicates their identification by usage of classical approaches such as microscopy. The aim of this study was to explore the potential use of chromatographic fingerprinting to identify plants present in herbal preparations intended for the treatment of ED. To achieve this goal, a HPLC-PDA and a HPLC-MS method were developed, using a full factorial experimental design in order to acquire characteristic fingerprints of three plants which are potentially beneficial for treating ED: Epimedium spp., Pausinystalia yohimbe and Tribulus terrestris. The full factorial design demonstrated that for all three plant references a C8 column (250mm×4.6mm; 5µm particle size) is best suited; methanol and an ammonium formate buffer (pH 3) were found to be the best constituents for the mobile phase. The suitability of this strategy was demonstrated by analysing several self-made triturations in three different botanical matrices, which mimic the influential effects that could be expected when analysing herbal supplements. To conclude, this study demonstrates that chromatographic fingerprinting could provide a useful means to identify plants in a complex herbal mixture.

A dietary strategy for the management of artemether-lumefantrine-induced cardiovascular and renal toxicity

BACKGROUND

Unsweetened natural cocoa has antimalarial properties. Unsweetened natural cocoa powder (UNCP), obtained as a result of the removal of cocoa butter from a cocoa bean protects against malaria episodes. Cocoa powder, which is prepared after removal of the cocoa butter, contains about 1.9 % theobromine and 0.21 % caffeine. Concomitant consumption of cocoa and artemether/lumefantrine (A/L) is a common practice in Ghana, West Africa. This study seeks to determine the elemental composition of UNCP and its protective effect on the heart and kidney against (A/L) administration.

METHODS

Energy dispersive x-ray fluorescence spectroscopy was used to detect the quality and quantity of the elemental composition in UNCP. Thereafter, 30 nonmalarious male guinea pigs were divided into five groups of six animals each. One group was administered with 75 mg/kg body weight A/L only and another group distilled water (control group). The rest received 300 mg/kg, 900 mg/kg and 1500 mg/kg body weight UNCP for 14 days orally and A/L for the last 3 days (ie day 11 to day 14). Biochemical and histopathological examinations were carried out after euthanisation of the animals.

RESULTS

A total of thirty-eight (38) micro and macro elements were detected with the ED-XRF. Macro elements like sodium (Na), magnesium (Mg), aluminium (Al), phosphorus (P), chlorine (Cl), potassium (K), calcium (Ca), manganese (Mn) and iron (Fe) and micro elements like chromium (Cr), copper (Cu), zinc (Zn), arsenic (As), and lead (Pb) were identified and evaluated. Biochemical analysis revealed increases in HDL levels (p>0.05) while there were decreases in LDL levels (p>0.05), creatine kinase and AST levels (P<0.05) in animals that received UNCP compared to A/L only administered group. Urea levels reduced significantly by 53 % (p<0.05) in group that received 1500 mg/kg UNCP. Histopathological examinations of the heart and kidney buttressed the protective effects of cocoa administration.

CONCLUSION

The percentage of recommended daily allowance of UNCP for chromium is 3750 % for men and 5250 % for women while % RDA for copper corresponds to 103.6 % in both sexes. UNCP proved to possess cardioprotective and renoprotective potential during artemether-lumefantrine administration.