Robust Ultraviolet-Visible (UV-Vis) Partial Least-Squares (PLS) Models for Tannin Quantification in Red Wine

Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples

Cider is a fermented drink obtained from apple juice. As a function of the used apple cultivar, cider can be classified in four different categories (dry, semi-dry, semi-sweet, sweet), distinguished by the attribute of "dryness," which reflects the sweetness and softness perceived. The dryness level is defined by scales (IRF, NYCA scales) based on the residual sugar, titratable acidity and tannin contents. Despite some adjustments, these scales show limitations in the prediction of actual perceived dryness, as they cannot consider the complicated interrelation between combined chemical compounds and sensory perception. After defining the perceived sensory dryness and its sensory description by using the quantitative descriptive analysis (QDA) method, a multivariate approach (PLS) was applied to define a predictive model for the dryness and to identify the chemical compounds with which it was correlated. Three models were developed, based on three different sets of chemical parameters, to provide a method that is easily applicable in the ordinary production process of cider. The comparison between the predicted rating and the relative scales scores showed that the models were able to predict the dryness rating in a more effective way. The multivariate approach was found to be the most suitable to study the relation between chemical and sensory data.

Potential of Leave and Fruit Ethanolic Extract of Etlingera hemisphaerica as Antihyperuricemic in Mice (Mus musculus)

<b>Background and Objective:</b> Hyperuricemia is a disease triggered by disorders of uric acid metabolism. Therefore, this study evaluated the potential of leaves ethanolic extract of <i>Etlingera hemisphaerica</i> (LE3H) and fruits ethanolic extract <i>E. hemisphaerica</i> (FE3H) to restore hyperuricemia in mice. <b>Materials and Methods:</b> Six groups (A0, A1, A2, A3, A4 and A5) each consisted of four male mice. Hyperuricemia in mice was induced by giving 0.3 mL of fresh chicken liver juice (FCLJ) for seven days (A1, A2, A3, A4 and A5). The condition of hyperuricemia in A1 is not neutralized. Meanwhile, hyperuricemia conditions in A2, A3, A4 and A5 were neutralized for seven days by giving 0.01 mg g<sup></sup><sup>1</sup> body weight (BW) allopurinol, 0.13, 0.26 and 0.36 mg g<sup></sup><sup>1</sup> BW LE3H. The control group (A0) only received double-distilled water in the same way. Blood uric acid levels were measured with the GCU Meter Device before and after the induction of hyperuricemia and after efforts to neutralize the hyperuricemia condition. Six groups (B0, B1, B2, B3, B4, B5) each consisting of four male mice were also provided to test the potential of FE3H. The recovery potential FE3H against hyperuricemia was tested separately in the same way as was done for LE3H. <b>Results:</b> Giving FCLJ significantly increased (140.00-187.00%) uric acid compared to the control, so hyperuricemia was achieved. Doses of 0.13, 0.26 and 0.36 mg g<sup></sup><sup>1</sup> BW LE3H significantly recovered hyperuricemia as much as 54.09, 56.14 and 60.88%, respectively. Meanwhile, doses of 0.13, 0.26 and 0.36 mg g<sup></sup><sup>1</sup> FE3H significantly recovered hyperuricemia as much as 60.37, 62.24 and 65.572%, respectively. The LE3H and FE3H at the same dose showed that FE3H had a higher potential to restore hyperuricemia than LE3H. <b>Conclusion:</b> Leave and fruit ethanolic extract of <i>E. hemisphaerica</i> can potentially restore hyperuricemia in mice.

Optimisation of PLS Calibrations for Filtered and Untreated Samples towards In-Line Monitoring of Phenolic Extraction during Red-Wine Fermentations

Infrared spectroscopy provides an efficient, robust, and multivariate means to measure phenolic levels during red-wine fermentations. However, its use is currently limited to off-line sampling. In this study, partial least squares (PLS) regression was used to investigate the possibility of using spectral data from minimally pre-treated or untreated samples for the optimisation of prediction calibrations towards an in-line monitoring set-up. The evaluation of the model performance was conducted using a variety of metrics. Limits of detection and quantification of the PLS calibrations were used to assess the ability of the models to predict lower levels of phenolics from the start of fermentation. The calibrations were shown to be useful for the quantification of phenolic compounds and phenolic parameters with minimal or no sample pre-treatment during red-wine fermentation. Upon evaluation of performance, the calibrations built for attenuated-transmission Fourier-transform mid-infrared (ATR-FT-MIR) and diffuse-reflectance Fourier-transform near-infrared (DR-FT-NIR) were shown to be the most suitable spectroscopy techniques for eventual application in an automated and in-line system with values for limits of detection and quantification being suitable for the entire duration of fermentation.

VIS-NIR Modeling of Hydrangenol and Phyllodulcin Contents in Tea-Hortensia (Hydrangea macrophylla subsp. serrata)

Hyperspectral data are commonly used for the fast and inexpensive quantification of plant constituent estimation and quality control as well as in research and development applications. Based on chemical analysis, different models for dihydroisocoumarins (DHCs), namely hydrangenol (HG) and phyllodulcin (PD), were built using a partial least squares regression (PLSR). While HG is common in Hydrangea macrophylla, PD only occurs in cultivars of Hydrangea macrophylla subsp. serrata, also known as ‘tea-hortensia’. PD content varies significantly over the course of the growing period. For maximizing yield, a targeted estimation of PD content is needed. Nowadays, DHC contents are determined via UPLC, a time-consuming and a destructive method. In this research article we investigated PLSR-based models for HG and PD using three different spectrometers. Two separate trials were conducted to test for model quality. Measurement conditions, namely fresh or dried leaves and black or white background, did not influence model quality. While highly accurate modeling of HG and PD for single plants was not possible, the determination of the mean content on a larger scale was successful. The results of this study show that hyperspectral modeling as a decision support for farmers is feasible and provides accurate results on a field scale.

Correlation analysis of physicochemical properties with anti-inflammatory activity of Andrographis paniculata (Burm.f.) Nees based on HPLC-DAD, colorimeter and multivariate statistics: A comprehensive quality evaluation strategy

Andrographis paniculata (Burm.f.) Nees is an essential traditional herbal medicine with various bioactivities in Asian countries. The quality of herbal medicines directly affects its clinical efficacy, so a comprehensive strategy, including color assay, chemical profiles, quantitative analysis, and anti-inflammatory activity assay, is constructed to evaluate the quality of A. paniculata in this paper. Here, 16 batches of commercial A. paniculata were collected, and there were noticeable differences in appearance, chemical compounds, and bioactivity among batches. Principal component analysis (PCA) indicated the color and diterpenoid lactones could be used to classify A. paniculat. And then, correlation analysis found the batches with greener color have higher contents of diterpenoid lactones and more efficient anti-inflammatory activity. Based on the results above, the partial least squares (PLS) regression models were finally established to predict the contents of diterpenoid lactones using the color assay data. All diterpenoid lactones models showed good performance, especially neoandrographolide. Notably, PLS regression models were first used for the nondestructive quantitative analysis of A. paniculata. This comprehensive quality evaluation strategy can theoretically elucidate the relationship between good appearance, high contents of diterpenoid lactones, and superior bioactivity of A. paniculata, which is meaningful for its quality control and evaluation. It also laid a theoretical basis for appearance and bioactivity evaluations of high-quality traditional herbal medicine.

QSPR Studies on the Octane Number of Toluene Primary Reference Fuel Based on the Electrotopological State Index

The quantitative structure-property relationship (QSPR) models for predicting the octane number (ON) of toluene primary reference fuel (TPRF; blends of n-heptane, isooctane, and toluene) was investigated. The electrotopological state (E-state) index of TPRF components was computed and weight-summed to generate the quantitative descriptor of TPRF samples. The partial least squares (PLS) technique was used to build up the regression model between the ON and weight-summed E-state index of the investigated samples. The QSPR models for the research octane number (RON) and motor octane number (MON) of TPRF were built. The prediction performance of the obtained PLS models was assessed by the external test set validation and leave-one-out cross-validation. The validation results demonstrate that the proposed PLS models are feasible for predicting the ON, both RON and MON, of TPRF. In addition, several other QSPR models for the ON of TPRF were developed by employing the stepwise regression and Scheffé polynomials methods, and the prediction performance of these models were compared with that of the PLS models. The comparison result shows that the proposed PLS models are slightly better than multiple linear regression models and Scheffé models. It is demonstrated that the combination of the E-state index and PLS is an easy-to-use and promising method for studying and forecasting the ON of TPRF.

Basic In-Mouth Attribute Evaluation: A Comparison of Two Panels

Astringency is often difficult to evaluate accurately in wine because of its complexity. This accuracy can improve through training sessions, but it can be time-consuming and expensive. A way to reduce these costs can be the use of wine experts, who are known to be reliable evaluators. Therefore, the aim of this work was to compare the sensory results and the panel performance obtained using trained panelists versus wine experts (winemakers). Judges evaluated twelve red wines for in-mouth basic perception (sweet, sour, bitter, astringent, and burning sensation) following the same tasting protocol and with the samples being presented in two different tasting modalities. Panels’ performance and relationship between the chemical composition and the sensory perception were investigated. Both panels showed similar consistency and repeatability, and they were able to accurately measure the astringency of the wines. However, the significant correlations between sensory scores and chemical composition varied with the panel and the tasting modality. From our results, we could see that winemakers tended to discriminate better between the samples when the differences were very small.

Spectrophotometric Analysis of Phenolic Compounds in Grapes and Wines

Phenolic compounds are of crucial importance for red wine color and mouthfeel attributes. A large number of enzymatic and chemical reactions involving phenolic compounds take place during winemaking and aging. Despite the large number of published analytical methods for phenolic analyses, the values obtained may vary considerably. In addition, the existing scientific knowledge needs to be updated, but also critically evaluated and simplified for newcomers and wine industry partners. The most used and widely cited spectrophotometric methods for grape and wine phenolic analysis were identified through a bibliometric search using the Science Citation Index-Expanded (SCIE) database accessed through the Web of Science (WOS) platform from Thompson Reuters. The selection of spectrophotometry was based on its ease of use as a routine analytical technique. On the basis of the number of citations, as well as the advantages and disadvantages reported, the modified Somers assay appears as a multistep, simple, and robust procedure that provides a good estimation of the state of the anthocyanins equilibria. Precipitation methods for total tannin levels have also been identified as preferred protocols for these types of compounds. Good reported correlations between methods (methylcellulose precipitable vs bovine serum albumin) and between these and perceived red wine astringency, in combination with the adaptation to high-throughput format, make them suitable for routine analysis. The bovine serum albumin tannin assay also allows for the estimation of the anthocyanins content with the measurement of small and large polymeric pigments. Finally, the measurement of wine color using the CIELab space approach is also suggested as the protocol of choice as it provides good insight into the wine's color properties.

Simultaneous spectrophotometric determination of trace copper, nickel, and cobalt ions in water samples using solid phase extraction coupled with partial least squares approaches

A simultaneous spectrophotometric determination method for trace heavy metal ions based on solid-phase extraction coupled with partial least squares approaches was developed. In the proposed method, trace metal ions in aqueous samples were adsorbed by cation exchange fibers and desorbed by acidic solution from the fibers. After the ion preconcentration process, the enriched solution was detected by ultraviolet and visible spectrophotometer (UV-Vis). Then, the concentration of heavy metal ions were quantified by analyzing ultraviolet and visible spectrum with the help of partial least squares (PLS) approaches. Under the optimal conditions of operation time, flow rate and detection parameters, the overlapped absorption peaks of mixed ions were obtained. The experimental data showed that the concentration, which can be calculated through chemometrics method, of each metal ion increased significantly. The heavy metal ions can be enriched more than 80-fold. The limits of detection (LOD) for the target analytes of copper ions (Cu²⁺), cobalt ions (Co²⁺) and nickel ions (Ni²⁺) mixture was 0.10μgL^-1, 0.15μgL^-1 and 0.13μgL^-1, respectively. The relative standard deviations (RSD) were less than 5%. The performance of the solid-phase extraction can enrich the ions efficiently and the combined method of spectrophotometric detection and PLS can evaluate the ions concentration accurately. The work proposed here is an interesting and promising attempt for the trace ions determination in water samples and will have much more applied field.