Determination Of Sugar Content Research Articles

PREPARATION AND NUTRITIONAL EVALUATION OF ENRICHED JAM MADE FROM BLENDS OF APPLE, STRAWBERRY AND GRAPES

The aim of this study is to prepare an acceptable jam from blends of Apple, Strawberry and Grapes. Jams were produced from blends of Apple, Strawberry and Grapes in the following ratios 30:20:10:40 (A= 30g apple, 20g strawberry, 10g grapes and 40g of sugar) and 35:10:15:40 (B= 35g apple, 10g strawberry, 15g grapes and 40g of sugar) respectively. The pulp mixtures were combined with 40g of sugar. Mixed fruit jam and strawberry jam were used as commercial control labelled as sample C and D respectively. Standard methods were used for the determination of proximate composition, sugar content, phytochemical constituents and sensory evaluation of the Jam. The proximate composition indicated that sample A (15.31±0.12) and B (16.86±0.03) had a moisture content lower than the commercial control C (27.05±0.03) and D (27.60±0.45). The ash, fiber and lipid contents showed no significant difference in the jams produced and the commercial controls. Sample A and B had higher protein 29.58±0.02 and 27.41±0.01 as compared to the commercial controls C and D (24.62±0.02 and 25.15±0.01). No significant (P>0.05) difference was observed in the glucose composition of the sample A and B and the commercial controls C and D. Fructose content in sample A (2.74±0.21) was higher than sample B (1.94±0.01) and the commercial controls C (1.85±0.00) and D (1.42±0.00). Qualitative testing for flavonoids, terpenoids, cardiac glycoside and tannin revealed potential good health benefits. The sensory evaluation revealed that sample A which comprises of 30% apple, 20% strawberry, 10% grapes and 40% sugar was rated best...

Determination of total protein and sugar content in soy-based beverages using variable selection methods applied to ATR-FTIR spectroscopy

This study explores the potential of using ATR-FTIR coupled with partial least squares (PLS) and random forest (RF) for predicting total protein (TP), total sugar (TS), reducing sugars (RS), and non-reducing sugars (NRS) in soy-based beverages (SBBs). Employing variable selection techniques such as interval PLS (iPLS), synergy interval PLS (siPLS), uninformative variable elimination (UVE), ordered predictors selection (OPS), bat algorithm (BA), genetic algorithm (GA), and particle swarm optimization (PSO). The OPS-PLS emerges as the optimal model for TS prediction, yielding an RMSEP of 0.114 wt% and R2p of 0.934. GA-PLS excels in TP, RS, and NRS prediction, achieving RMSEP values of 0.024 wt%, 0.273 wt%, and 0.339 wt%, with corresponding R2p values of 0.880, 0.847, and 0.450. In RF modeling, GA-RF is identified as the superior model for all properties. These findings underscore the potential of regression models and ATR-FTIR as effective and environmentally friendly tools for analyzing SBB composition.

Determination of sugar in tangerines by fluorescence with an Improved partial least squares (PLS) algorithm

The accurate determination of sugar content in tangerines plays a pivotal role in assessing their quality, nutritional value, and marketability. Traditional methods for sugar quantification often involve time-consuming and resource-intensive processes. In this paper, we introduce a novel approach for sugar determination in tangerines utilizing fluorescence spectroscopy in conjunction with an improved Partial Least Squares (iPLS) algorithm. A robust testing model was developed, incorporating a diverse dataset of tangerine samples with known sugar concentrations. Fluorescence spectra were acquired for 80 samples, of which 37 were used to build the iPLS model and were considered as the training dataset. The remaining 43 samples served as the validation dataset and were used to show the model’s efficacy. The training dataset was evaluated using cross-validation, and F-values were computed to determine how many main components should be utilized to build the model. The result approved validation dataset’s R-square and root-mean-square error were 0.9777 and 0.002992, respectively. These findings open the door to broader applications in the citrus industry and beyond, with the potential for automating the analysis process and improving overall quality control.

Assessment of SSC and soluble sugar content of three pear cultivars during storage using dielectric method

This study aims to develop models for predicting soluble solids content (SSC) and soluble sugar content of three different pear cultivars. The samples' SSC and soluble sugar content, as well as the dielectric spectra in the frequency range of 20–4500 MHz were first collected, then the dielectric penetration depth was analyzed using one-way ANOVA method, and finally the accuracy of different models for predicting SSC and soluble sugar contents including partial least squares regression (PLSR), support vector machine (SVM), back propagation - artificial neural network (BP-ANN), and extreme learning machines (ELM) were compared. Results showed that the mean dielectric spectra of three pear cultivars presented similar trends. The dielectric penetration depth in the researched frequency range reached the maximum sugar content determination depth (intact pears: 20 mm; pulp: 17 mm). The correlations between glucose and dielectric spectra under specific frequency for 'Yulu' (determination coefficient: R2 = 0.88) and 'Korla' (R2 = 0.94) pears were the highest, while in terms of 'Xuehua' pear, the correlation was relatively lower (R2 ≤ 0.64). The Rp2 (R2 of prediction set) of the optimal sugar prediction model based on the dielectric spectra of intact pear and pear pulp were successively between 0.77–0.88 and 0.85–0.93. This research proved the feasibility of predicting sugar content in different pear cultivars using dielectric spectra.

Determination of sugar contents in Hyacinthella Schur bulbs and identification of sugars by cluster analysis method

Türkiye has a rich floristic diversity and is accepted as the gene center of the Hyacinthella genus. Nineteen species of the Hyacinthella genus have been described in the World, and eleven of these species are distributed in Türkiye. Additionally, ten of the eleven Hyacinthella species are endemic to our country. Therefore, any study on these species will contribute to the protection, promotion and sustainability of our country's genetic resources. Plants may have different metabolite contents depending on their genetic structure and environmental conditions. Sugar content in bulbous plants depends on sucrose metabolism and varies with species and environmental effects. In this study, the sugar contents of 11 different Hyacinthella species distributed in our country were analyzed. The presence of 9 different sugar types in the species was analyzed qualitatively and quantitatively. In addition, depending on the sugar content, identification and grouping techniques were used with the Cluster Analysis Method. As a result of sugar analysis, while glucose, sucrose and fructose are found in all species, differences were detected between species in other sugar contents In cluster analysis, Hyacinthella species were divided into 3 different groups in terms of sugar content. The study both identifies the sugar contents found in the bulbs of Hyacinthella species and suggests a different identification method By combining morphological, molecular and metabolic data, a complete and accurate identification of species will be achieved.

Inheritance regularities of economic and valuable traits in selection of sugar beet simple cytoplasmic male sterile hybrids

Aim. To study the influence of parental components of the crossing on the manifestation of the traits “yield of root crops” and “sugar content” in the hybrid progeny for the production of simple CМS hybrids. To create high-yielding simple CМS hybrids as a parent component for the formation of experimental sugar beet hybrids on а CМS basіs. Methods. Field (experiments, phenological observations), laboratory (to determine sugar content), measuring and weighing (to determine the crop structure), statistical (mathematical processing of research results). Results. The nature of the inheritance of productivity traits for the formation of simple CМS sugar beet hybrids has been established. For different combinations of crossings, the value of the inheritance coefficients (h2) of the trait “yield of root crops” from the parent form (O-type line) to the hybrid varied within 0.11–0.71 and 0.52–0.63 from the maternal form (CМS line). The inheritance coefficients of the trait “sugar content” from the parental form were in the range of 0.46–0.53 and 0.42–0.55 from the maternal form. An intermediate type of inheritance was observed for the sugar content in root crops. The best CМS lines and O-type lines have been identified as sources of economic and valuable traits. Seven combining-capable simple CМS hybrids with a high level of basic productivity were created for further use as a maternal component in the selection of sugar beet hybrids on а CМS basіs. Conclusions. A significant influence of the maternal component genotype on the level of yield of root crops of simple CМS hybrids has been established. A regularity has been revealed that the higher the total combining ability of CМS lines, the lower the degree of transfer of the trait “yield of root crops” from the parental form (O-type line) to the hybrid. There is no “mother plant” effect on sugar content in root crops, and an intermediate type of inheritance was observed in hybrids. The use of simple CМS hybrids with an increased level of basic productivity as a maternal component will significantly increase the efficiency of the breeding process for creating competitive sugar beet hybrids on а CМS basіs.

Structural characterizations and α-glucosidase inhibitory activities of four Lepidium meyenii polysaccharides with different molecular weights

Four polysaccharides (MCPa, MCPb, MCPc, MCPd) were obtained from Lepidium meyenii Walp. Their structures were characterized by chemical and instrumental methods including total sugar, uronic acid and protein content determination, UV, IR and NMR spectroscopy, as well as monosaccharide composition determination and methylation analyses. Four polysaccharides were a group of glucans with different molecular weights ranging from 3.12 to 14.4 kDa, and shared a similar backbone chain consisting of (1→4)-glucose linkages with branches attached to C-3 and C-6. Furthermore, bioactivity assay showed that MCPs had concentration-dependent inhibitory activity on α-glucosidase. MCPb (Mw = 10.1 kDa) and MCPc (Mw = 5.62 kDa) with moderate molecular weights exhibited higher inhibitory activity compared with MCPa and MCPd.Graphical

Determination of Sugar Content in Cows Milk

Determination of Sugar Content in Cows Milk

Determination of sugar content in honey using LC-Raman and programmable pump-Raman methods.

We combined (i) liquid chromatography and Raman spectrometry (LC-Raman) and (ii) programmable pump and Raman spectrometry (PP-Raman) to separate and identify compounds in a mixture. These techniques were applied to conduct a quantitative analysis of the sugars in honey. The spectral and temporal axes of the LC-Raman data were analyzed using the MCR-ALS analysis procedure, which enabled the separation and identification of four sugars (glucose, fructose, sucrose, and trehalose). The PP-Raman method was employed to examine the sugar concentration dependence of the intensity pattern of the Raman spectrum, and the linear concentration dependence of the intensity was obtained. The sugar contents were quantitatively determined from the integrated area of the elution peaks. The result was consistent with those derived from mass spectrometry and previous studies. The origin of the errors in the derived sugar contents is discussed. Our study presents a novel quantitative LC-Raman spectrometric method that does not rely on resonance or surface enhancement effects.

Breeding value of multi-sprout pollinator lines of different inbreeding generations as parental components of sugar beet hybrids on а CMS basis

Aim. Creation of combination-capable lines of multi-sprout pollinators of sugar beets of different levels of homozygosity, establishment of criteria for their selection based on basic productivity, reproductive capacity and hybridization potential at various stages of the selection process for the formation of parental components of hybrids on the cytoplasmic male-sterile (CMS) basis. Methods. Field (experiments, phenological observations), laboratory (to determine sugar content), measuring and weighing (to determine the crop structure), statistical (mathematical processing of research results). The research was carried out at the Tobacco Research Station of the National Scientific Center "Institute of Agriculture of the National Academy of Agrarian Sciences" in the laboratory of sugar beet breeding during the 2015–2021. The starting material was three hybrid multi-sprout populations of sugar beet Um. 17/02-1705, Um. 21/01-33 and Um. 14/05-752. Linear materials were obtained by the inbreeding method. Results. It was established that the lines of multi-sprout pollinators of sugar beets of the second-third generations of inbreeding (I2-I3) are characterized by the highest productivity. The yield of root crops exceeded the standard by 8.1–9.3%, sugar content by 8.6–8.8% and sugar collection by 16.5–17.9%. As the depth of inbreeding increases, the quality of pollen deteriorates sharply. If in the lines of the first generation of inbreeding (I1), the fertility of pollen in plants of of multi-sprout pollinators was 95.1%, then in the lines of the fifth generation (I5) it decreased to 31.0%. The number of non-viable pollen grains in them was 72.2%, seed germination was 29%. Experimental hybrids with the best performance were obtained by using as pollinators lines of the second to third generations of inbreeding. According to the complex characteristic "sugar collection", they exceeded the group standard by 19.7–21.3%. Conclusions. It has been established that for the formation of line materials of sugar beet multi-sprout pollinators, as parent components of hybrids on а CMS basis, the main criterias for the selection of valuable plant genotypes, in addition to the hybridization potential, are high level of their basic productivity and reproductive capacity. The best experimental sugar beet hybrids were obtained by using lines of multi-sprout pollinators of the second to third inbreeding generations.

Application of Maillard Reaction Products Derived Only from Enzymatically Hydrolyzed Sesame Meal to Enhance the Flavor and Oxidative Stability of Sesame Oil.

The low-temperature roasting of sesame oil has become increasingly popular because of its nutritional benefits; however, the flavor is reduced. In order to improve the quality of sesame oil without exogenous addition, sesame meal was hydrolyzed and further used to prepare Maillard reaction products (MRPs) while protease hydrolysis (PH) and glucoamylase-protease hydrolysis (GPH) were used, and their respective Maillard products (PHM and GPHM) were added in the oils for reducing sugar and total sugar content determination, free amino acid determination, and color and descriptive sensory analysis, as well as electronic nose, SPME-GC-MS, odor activity value, and oxidative stability analyses. Results showed that the MRPs could be produced using the enzymatically hydrolyzed sesame meal without exogenous addition, and the oil flavor blended with GPHM (GPHM-SO) was significantly (p < 0.05) improved with the best sensory quality. The composition of pyrazines (119.35 μg/mL), furans (13.95 μg/mL), and sulfur substances (6.25 μg/mL) contributed positively to sensory properties in GPHM-SO, and 2,5-dimethylpyrazine, 2,6-dimethylpyrazine, and 2,3-dimethylpyrazine were characterized as the key flavor compounds with odor activity values of 7.01, 14.80, and 31.38, respectively. Furthermore, the oxidative stability of the oil was significantly improved with the addition of MRPs, and the shelf life of GPHM-SO was predicted to be extended by 1.9 times more than that of the crude oil based on the accelerated oxidation fitting analysis. In general, the MRPs derived only from sesame meal can enhance the flavor and oxidative stability of sesame oil and can be applied in the oil industry.

Improved evaluation of commercial cane sugar content in sugarcane stalk using near infrared hyperspectral imaging and stalk axis rotation technique

Determination of the commercial cane sugar (CCS) content in sugarcane stalk is an important process in the factory. A near infrared hyperspectral imaging system was investigated to develop a CCS prediction model directly from the stalk without peeling. Two scanning techniques and the presence of wax, or not, on the stalk surface were compared for prediction accuracy of the developed models based on laboratory analysis. The model was developed from the spectral data based on an axis rotation scan, which enabled rotation of the stalk around a stationary axis while being scanned. This model performed better than the model based on the data from a normal linear translation scan, especially for wax-covered samples. The axis rotation scan produced a pixel-wise CCS map that could be visualised across the whole surface of the stalk, whereas the pixel-wise CCS map based on the translation scan was able to show only the CCS values for a projected surface area and the opposite projected surface area of the stalk, with error at the curved edge of the stalk. In addition, the single colour CCS maps of each portion of the stalk, which were created by the model based on a translation scan of the wax-covered samples, could be used for visually detecting the right maturity of the sugarcane in the field. • Axis rotation-scan method to improve sugar cane stalk CCS prediction was proposed. • Slightly better prediction of CCS was obtained with the rotation scan. • Single colour map based on NIR-HSI could be used to indicate proper maturity.

Effects of monosaccharide composition on quantitative analysis of total sugar content by phenol-sulfuric acid method

Phenol-sulfuric acid method is one of the most common methods applied to the analysis of total sugar content during polysaccharides study. However, it was found that the results obtained from the phenol-sulfuric acid method was generally lower than the real total sugar content, especially when acidic monosaccharides were contained in the polysaccharides samples. Therefore, the present study focused to unveil the proposed problem. Based on the optimization of colorimetric conditions, such as optimal wave length of absorption, linearity range, color reaction time and temperature, it indicated that the phenol-sulfuric acid method was a convenient and accurate way for the total sugar content analysis. In addition, the color-rendering capabilities of 10 common monosaccharides were systematically analyzed to obtain a relative correction factor for each monosaccharide relative to glucose, which was proved to be the main reason for the deviation in the detection of total sugar content. Moreover, the key points during the application of phenol-sulfuric acid method were suggested. This study provides a scientific theoretical basis and a reliable experimental research method for the accurate determination of total sugar content by the phenol-sulfuric acid method, and which will also promote the application of this convenient method in the polysaccharides study.

Breeding of highly productive sugar beet hybrids with improved beet root shape

Purpose. Isolation of donors of valuable breeding and genetic traits and the creation of a new source material for the selection of parental components of sugar beet hybrids according to the shape of the root. Evaluation of the productive potential of experimental sugar beet hybrids with improved root shape parameters. Methods. Field (experiments, phenological observations), laboratory (determination of sugar content), measuring and weighing (determination of crop structure), statistical (mathematical processing of research results). Results. The results of the evaluation of the basic productivity of parental components of different genetic structure and productivity of experimental sugar beet hybrids with improved root shape are presented. An increase in the yield of root crops, sugar yield and sugar output per unit area in sugar beet hybrids on a cytoplasmic male-sterile (CMS) basis, created using multigerm pollinators with an improved root crop shape (oval-conical), has been established. Experimental hybrids formed on the basis of first generation of multigerm pollinators of backcross (BC1) prevailed the group standard in root crop yield by 15.2–22.8%, sugar yield and sugar output by 14.4–19.4% and 11.5–17.5%, respectively. The sugar content was below or at the level of the group standard. Similar indicators of hybrids formed on the basis of pollinators of the second generation of backcross (BC2) were 14.0–21.2%, 17.0–23.2% and 17.6–23.9%, respectively. The sugar content was at the level of the group standard. Root shape index indicators were 1.32 and 1.28, respectively. The hybrids formed using the initial multigerm pollinators were characterized by a conical root shape (shape index – 0.61). According to indicators of yield, sugar yield and sugar output per unit area, they were at the level of the group standard. Conclusions. It was established that the shape of the root crop is an important factor in improving the productive potential of sugar beets in selection for heterosis. The change in the shape of the root crop from conical to oval-conical leads to an increase in the productivity of multigerm pollinators of sugar beets by 8–19% and hybrids created with their participation by 17–23%.

Non-destructive determination of total sugar content in tobacco filament based on calibration transfer with parameter free adjustment

The advantages of near-infrared spectroscopy (NIR) for non-destructive determination have an important impact on quality assessment in the tobacco industry. However, spectral measurements are very sensitive to external conditions, such as moisture content and sample morphology. The accuracy and stability of analytical models are often affected by variations in sample spectra. In this study, an efficient non-supervised parameter-free calibration enhancement (NS-PFCE) method was proposed for the calibration transfer from dried tobacco powder to undried tobacco samples in order to correct the effects of moisture and material scattering on spectral absorption. While comparing the transfer effects of piecewise direct standardization (PDS), spectral space transformation (SST), and slope/bias correction (S/B) methods. The results showed that the best prediction (RMSEP = 0.9800) was obtained with the NS-PFCE method, with a decrease of 14.19 %, 2.26 %, and 27.19 % in RMSEP compared to the prediction results calibrated transferred by PDS, SST and S/B, respectively. In addition, to further optimize the calibration effect and improve the transfer efficiency, competitive adaptive reweighted sampling (CARS), variable combination population analysis employing the iteratively retaining informative variables (VCPA-IRIV), and variable combination population analysis genetic algorithm (VCPA-GA) were employed to select the important wavelengths to simplify the model. The results showed that the VCPA-IRIV-PLSR model combined with NS-PFCE method obtained the optimal prediction results of undried filament samples (RMSEP = 0.7252), which were 50.08 %, 6.74 % and 33.10 % lower than those RMSEP values by the other three methods under the same treatment conditions, respectively. Therefore, it can be concluded that NS-PFCE method combined with VCPA-IRIV-PLSR model can effectively compensate for the spectral differences caused by moisture and sample morphology, and achieve an excellent quantitative analysis of moist samples in non-homogeneous form. The method helps to achieve rapid non-destructive testing at-line in the tobacco industry.

A non-destructive methodology for determination of cantaloupe sugar content using machine vision and deep learning.

To determine the maturity of cantaloupe, measuring the soluble solid content (SSC) as the indicator of sugar content based on the refractometric index is commonly practised. This method, however, is destructive and limited to a small number of samples. In this study, the coupling of a convolutional neural network (CNN) with machine vision was proposed in detecting the SSC of cantaloupe. The cantaloupe images were first acquired under controlled and uncontrolled conditions and subsequently fed to the CNN to predict the class to which each cantaloupe belonged. Four hand-crafted classical machine-learning classifiers were used to compare against the performance of the CNN. Experimental results showed that the CNN method significantly outperformed others, with an improvement of >100% being achieved in terms of classification accuracy, considering the data acquired under the uncontrolled environment. The results demonstrated the potential benefit to operationalize CNNs in practice for SSC determination of cantaloupe before harvesting. © 2022 Society of Chemical Industry.

Determination of Total Free Sugar Content in Fresh Juice of Tomatoes and Strawberries Using Attenuated Total Reflection (ATR)-Micro Electro Mechanical Systems (MEMS)-Infrared (IR) Spectroscopy

ATR-MEMS-赤外分光法を用いたトマトおよびイチゴ汁液中総遊離糖含有量の迅速定量法を開発した．本法においてはトマトおよびイチゴ汁液は希釈せずに測定し，水のスペクトルを直接差し引かずに説明変数の少ない方法を目指した．併せて，糖水溶液では糖濃度を変えて測定した．赤外分光法と同様の振動分光法である近赤外分光法と異なり，糖の水溶液，トマトおよびイチゴ汁液を測定した赤外光吸収スペクトル上で，スペクトルの微分処理なしで糖の吸収帯を目視により確認できた．目的変数がトマトおよびイチゴ汁液中総遊離糖含有量の場合，他の成分による吸収を配慮すれば，それぞれ1032 cm–1，1000 cm–1の吸光度を説明変数として採用可能であった．トマトよりもイチゴで低波数側の吸光度が採用されたことは，イチゴの構成糖であるスクロースの吸収がグルコースとフルクトースに比べて低波数側にも存在することと対応する．また，トマトおよびイチゴにおいて，Bland-Altmanプロットは誤差の許容範囲（LOA）内にプロットされたことから，HPLCによる総遊離糖含有量の参照値とATR-MEMS-赤外分光法による総遊離糖含有量の定量値（説明変数は1つのみ）が同等であることを確認できた．

МЕТОДИЧНІ ОСОБЛИВОСТІ ВИЗНАЧЕННЯ ВМІСТУ ЦУКРІВ В СЕЛЕКЦІЇ ЦУКРОВОЇ КУКУРУДЗИ

A currently important task for the evaluation of breeding samples at all stages of the sweet maize selection is to control the sugar content in the sweet maize grain of technical maturity. The methodical features of the sugar content determination in the sweet maize grain using the example of the inbred line CE401 and hybrid F2(CE401 × Chornosteblova) were investigated. We compared the content of total sugar, monosaccharides and disaccharides in the grain on the twenty-first day after self-pollination (21 DAP), on the day of sampling and after storage of the same ears at subzero temperature. It was found that after storage of ears for 4.5 months at a temperature of –12 0C, total sugar content in grain of CE401 increased by 97.7 % and reached 46.84 % by mass of absolutely dry matter (ADM), and for F2(CE401 × Chornosteblova) – by 61.7 % and reached 15.93 %. Accordingly, the contents of mono- and disaccharides as components of total sugar content increased, although this increase in F2 (CE401× Chornosteblova) was very uneven for individual ears. Intact grains of the CE401 line contained 2.55 times more monosaccharides and 2.27 times more disaccharides compared to the F2 hybrid (CE401 × Chornosteblova). After keeping the ears at –12 ºC for 4.5 months, the share of total sugar content in ADM of the CE401B line grain exceeded the similar value of the F2 hybrid (CE401 × Chornosteblova) by 2.94 times, monosaccharides by 3.54 times, and disaccharides by 2.54 times. The degree of such increase depends on the genotype of the initial breeding material. For the sweet maize selection, it is recommended to determine the total sugar content and its fractions on the day of sampling, and to refuse the common practice to store of grain samples at subzero temperature before analysis. Key words: Zea mays L., grain in technical maturity, total sugar content, mono- and disaccharide contents, determination procedure, grain storage under subzero temperature

Laser-induced sound pinging for the rapid determination of total sugar or sweetener content in commercial beverages

We recently reported on fixed-path length laser-induced sound pinging (FPL-LISP) as a rapid photoacoustic technique employing an inexpensive benchtop tattoo-removal laser for reliably determining the speed of sound in low-volume fluids. In this contribution, we demonstrate the capacity of FPL-LISP to analyze representative commercial beverages for their natural or artificial sweetener contents. As a benchmark, the speed of sound was determined for solutions of sugars (glucose, fructose, sucrose), mock high fructose corn syrup (HFCS-55), and 12 household sweeteners (culinary sugars, syrups, honey, molasses) across the concentration range of 1–20% w/v in water, simulating the typical sweetener range found in commercial soft drinks. The setup was then employed to estimate sweetener contents of 26 popular commercial beverages using the HFCS-55 standard curve as a training data set. Our results are remarkably consistent with the label values for these representative commercial beverages, in spite of the fact that some beverages clearly employ a sweetener other than HFCS-55 or a proprietary blend, suggesting the excellent potential of the FPL-LISP setup as a quick screening tool well-suited to quality control and real-time assessment in the beverage and fermentation industrial sectors. The proposed approach represents a significant improvement over many existing methods on the basis of measurement time (down to 1 s, which can be considered real time for many applications), lenient sample requirements (tens of microliters to 1 mL), robust and user-friendly analysis, practical considerations (e.g., economical, minimal service and maintenance concerns), and prospects for advancing both online monitoring and fully portable versions of this instrumentation.

Determination of Sugar, pH, and Anthocyanin Contents in Port Wine Grape Berries through Hyperspectral Imaging: An Extensive Comparison of Linear and Non-Linear Predictive Methods

This paper presents an extended comparison study between 16 different linear and non-linear regression methods to predict the sugar, pH, and anthocyanin contents of grapes through hyperspectral imaging (HIS). Despite the numerous studies on this subject that can be found in the literature, they often rely on the application of one or a very limited set of predictive methods. The literature on multivariate regression methods is quite extensive, so the analytical domain explored is too narrow to guarantee that the best solution has been found. Therefore, we developed an integrated linear and non-linear predictive analytics comparison framework (L&NL-PAC), fully integrated with five preprocessing techniques and five different classes of regression methods, for an effective and robust comparison of all alternatives through a robust Monte Carlo double cross-validation stratified data splitting scheme. L&NLPAC allowed for the identification of the most promising preprocessing approaches, best regression methods, and wavelengths most contributing to explaining the variability of each enological parameter for the target dataset, providing important insights for the development of precision viticulture technology, based on the HSI of grape. Overall, the results suggest that the combination of the Savitzky−Golay first derivative and ridge regression can be a good choice for the prediction of the three enological parameters.