Comparison of NIR and MIR spectroscopic methods for determination of individual sugars, organic acids and carotenoids in passion fruit

Comparative analysis of spectroscopic methods for rapid authentication of hazelnut cultivar and origin

Hazelnut market prices fluctuate significantly based on cultivar and provenance, making them susceptible to counterfeiting. To develop an accurate authentication method, we compared the performances of three spectroscopic methods: near infrared (NIR), handheld near infrared (hNIR), and medium infrared (MIR), on over 300 samples from various origins, cultivars, and harvest years. Spectroscopic fingerprints were used to develop and externally validate PLS-DA classification models. Both cultivar and origin models showed high accuracy in external validation. The hNIR model effectively distinguished cultivars but struggled with geographic distinctions due to lower sensitivity. NIR and MIR models showed over 93 % accuracy, with NIR slightly outperforming MIR for geographic origin. NIR proved to be a fast and suitable tool for hazelnut authentication. This study is the first to systematically compare spectroscopic tools for authenticating hazelnut cultivar and origin using the same dataset, offering valuable insights for future food authentication applications.

Nondestructive Determination of Tocopherol and Tocotrienol in Vitamin E Powder Using Near- and Mid-Infrared Spectroscopy

Vitamin E is an essential nutrient, but its poor water solubility limits food and pharmaceutical applications. The usability of vitamin E can be enhanced via modification methods such as encapsulation, which transforms the physical state of vitamin E from a liquid to a powder. This study examined the efficacy of near-infrared (NIR) and mid-infrared (MIR) spectroscopy in identifying and predicting various vitamin E derivatives in vitamin E-encapsulated powder (VEP). An MIR analysis revealed the fundamental C-H vibrations of vitamin E in the range of 2700-3250 cm-1, whereas an NIR analysis provided information about the corresponding combination, first, and second overtones in the range of 4000-9000 cm-1. The MIR and NIR data were analyzed using a principal component analysis to characterize the VEP. Partial least squares (PLS) regression was applied to predict the content of individual vitamin E derivatives. PLS cross-validation revealed that NIR analysis provides more reliable predictive accuracy and precision for the contents of vitamin E derivatives, achieving a higher coefficient of determination for prediction (Q2) (0.92-0.99) than MIR analysis (0.20-0.85). For test set validation, the NIR predictions exhibited a significant level of accuracy, as indicated by a high ratio of prediction to deviation (RPD) and Q2. Furthermore, the PLS models developed using the NIR data had statistically significant predictive performance, with a high RPD (1.54-3.92) and Q2 (0.66-0.94). Thus, NIR spectroscopy is a valuable nondestructive technique for analyzing vitamin E samples, while MIR spectroscopy serves as a useful method for confirming its presence.

Genome-wide analysis of the passion fruit invertase gene family reveals involvement of PeCWINV5 in hexose accumulation

BACKGROUND

Invertases (INVs) are key enzymes in sugar metabolism, cleaving sucrose into glucose and fructose and playing an important role in plant development and the stress response, however, the INV gene family in passion fruit has not been systematically reported.

RESULTS

In this study, a total of 16 PeINV genes were identified from the passion fruit genome and named according to their subcellular location and chromosome position. These include six cell wall invertase (CWINV) genes, two vacuolar invertase (VINV) genes, and eight neutral/alkaline invertase (N/AINV) genes. The gene structures, phylogenetic tree, and cis-acting elements of PeINV gene family were predicted using bioinformatics methods. Results showed that the upstream promoter region of the PeINV genes contained various response elements; particularly, PeVINV2, PeN/AINV3, PeN/AINV5, PeN/AINV6, PeN/AINV7, and PeN/AINV8 had more response elements. Additionally, the expression profiles of PeINV genes under different abiotic stresses (drought, salt, cold temperature, and high temperature) indicated that PeCWINV5, PeCWINV6, PeVINV1, PeVINV2, PeN/AINV2, PeN/AINV3, PeN/AINV6, and PeN/AINV7 responded significantly to these abiotic stresses, which was consistent with cis-acting element prediction results. Sucrose, glucose, and fructose are main soluble components in passion fruit pulp. The contents of total soluble sugar, hexoses, and sweetness index increased significantly at early stages during fruit ripening. Transcriptome data showed that with an increase in fruit development and maturity, the expression levels of PeCWINV2, PeCWINV5, and PeN/AINV3 exhibited an up-regulated trend, especially for PeCWINV5 which showed highest abundance, this correlated with the accumulation of soluble sugar and sweetness index. Transient overexpression results demonstrated that the contents of fructose, glucose and sucrose increased in the pulp of PeCWINV5 overexpressing fruit. It is speculated that this cell wall invertase gene, PeCWINV5, may play an important role in sucrose unloading and hexose accumulation.

CONCLUSION

In this study, we systematically identified INV genes in passion fruit for the first time and further investigated their physicochemical properties, evolution, and expression patterns. Furthermore, we screened out a key candidate gene involved in hexose accumulation. This study lays a foundation for further study on INV genes and will be beneficial on the genetic improvement of passion fruit breeding.

Metabolic Profile of Leaves and Pulp of Passiflora caerulea L. (Bulgaria) and Their Biological Activities

At present, there are no data in the scientific literature on studies aimed at characterizing Passiflora caerulea L. growing in Bulgaria. The present study aimed to investigate the metabolic profile and elemental composition of the leaves and pulp of this Passiflora, as well as to evaluate the antioxidant, antimicrobial and anti-inflammatory activities of its leaf and pulp extracts. The results showed that the pulp predominantly contained the essential amino acid histidine (7.81 mg g-1), while it was absent in the leaves, with the highest concentration being tryptophan (8.30 mg g-1). Of the fatty acids, palmitoleic acid predominated both in the pulp and in the leaves. A major sterol component was β-sitosterol. Fructose (7.50%) was the predominant sugar in the pulp, while for the leaves, it was glucose-1.51%. Seven elements were identified: sodium, potassium, iron, magnesium, manganese, copper and zinc. The highest concentrations of K and Mg were in the pulp (23,946 mg kg-1 and 1890 mg kg-1) and leaves (36,179 mg kg-1 and 5064 mg kg-1). According to the DPPH, FRAP and CUPRAC methods, the highest values for antioxidant activity were found in 70% ethanolic extracts of the leaves, while for the ABTS method, the highest value was found in 50% ethanolic extracts. In the pulp, for all four methods, the highest values were determined at 50% ethanolic extracts. Regarding the antibacterial activity, the 50% ethanolic leaf extracts were more effective against the Gram-positive bacteria. At the same time, the 70% ethanolic leaf extract was more effective against Gram-negative bacteria such as Salmonella enteritidis ATCC 13076. The leaf extracts exhibited higher anti-inflammatory activity than the extracts prepared from the pulp. The obtained results revealed that P. caerulea is a plant that can be successfully applied as an active ingredient in various nutritional supplements or cosmetic products.

A Scoping Review on Carotenoid Profiling in Passiflora spp.: A Vast Avenue for Expanding the Knowledge on the Species

The Passiflora genus is recognised for its ethnopharmacological, sensorial, and nutritional significance. Yet, the screening of its dietary and bioactive molecules has mainly targeted hydrophilic metabolites. Following the PRISMA-P protocol, this review assessed the current knowledge on carotenoid composition and analysis within Passiflora, examining 968 records from seven databases and including 17 studies focusing on carotenoid separation and identification in plant parts. Those publications originated in America and Asia. P. edulis was the most frequently examined species of a total of ten, while pulp was the most studied plant part (16 studies). Carotenoid analysis involved primarily high-performance liquid chromatography separation on C18 columns and detection using diode array detectors (64.71%). Most studies identified the provitamin A β-carotene and xanthophylls lutein and zeaxanthin, with their geometric configuration often neglected. Only one study described carotenoid esters. Besides the methodology's insufficient description, the lack of use of more accurate techniques and practices led to a high risk of bias in the carotenoid assignment in 17.65% of the articles. This review highlights the opportunity to broaden carotenoid studies to other species and parts within the diverse Passiflora genus, especially to wild, locally available fruits, which may have a strategic role in enhancing food diversity and security amidst climatic changes. Additionally, it urges the use of more accurate and efficient analytical methods based on green chemistry to better identify Passiflora carotenoids.

Multi-integrated genomic data for Passiflora foetida provides insights into genome size evolution and floral development in Passiflora

Passiflora is a plant genus known for its extremely distinctive and colorful flowers and a wide range of genome size variation. However, how genome characteristics are related to flower traits among Passiflora species remains poorly understood. Here, we assembled a chromosome-scale genome of P. foetida, which belongs to the same subgenus as the commercial passionfruit P. edulis. The genome of P. foetida is smaller (424.16 Mb) and contains fewer copies of long terminal repeat retrotransposons (LTR-RTs). The disparity in LTR-RTs is one of the main contributors to the differences in genome sizes between these two species and possibly in floral traits. Additionally, we observed variation in insertion times and copy numbers of LTR-RTs across different transposable element (TE) lineages. Then, by integrating transcriptomic data from 33 samples (eight floral organs and flower buds at three developmental stages) with phylogenomic and metabolomic data, we conducted an in-depth analysis of the expression, phylogeny, and copy number of MIKC-type MADS-box genes and identified essential biosynthetic genes responsible for flower color and scent from glandular bracts and other floral organs. Our study pinpoints LRT-RTs as an important player in genome size variation in Passiflora species and provides insights into future genetic improvement.

Comparative Analysis of LC-ESI-IM-qToF-MS and FT-NIR Spectroscopy Approaches for the Authentication of Organic and Conventional Eggs

The importance of animal welfare and the organic production of chicken eggs has increased in the European Union in recent years. Legal regulation for organic husbandry makes the production of organic chicken eggs more expensive compared to conventional husbandry and thus increases the risk of food fraud. Therefore, the aim of this study was to develop a non-targeted lipidomic LC-ESI-IM-qToF-MS method based on 270 egg samples, which achieved a classification accuracy of 96.3%. Subsequently, surrogate minimal depth (SMD) was applied to select important variables identified as carotenoids and lipids based on their MS/MS spectra. The LC-MS results were compared with FT-NIR spectroscopy analysis as a low-resolution screening method and achieved 80.0% accuracy. Here, SMD selected parts of the spectrum which are associated with lipids and proteins. Furthermore, we used SMD for low-level data fusion to analyze relations between the variables of the LC-MS and the FT-NIR spectroscopy datasets. Thereby, lipid-associated bands of the FT-NIR spectrum were related to the identified lipids from the LC-MS analysis, demonstrating that FT-NIR spectroscopy partially provides similar information about the lipidome. In future applications, eggs can therefore be analyzed with FT-NIR spectroscopy to identify conspicuous samples that can subsequently be counter-tested by mass spectrometry.

Applications of Delayed Luminescence for tomato fruit quality assessment across varied Sicilian cultivation zones

The food industry places significant emphasis on ensuring quality and traceability as key components of a healthy diet. To cater to consumer demands, researchers have prioritized the development of analytical techniques that can rapidly and non-invasively provide data on quality parameters. In this study, we propose to use the Delayed Luminescence (DL), an ultra-weak and photo-induced emission of optical photons, as a tool for a rapid evaluation of quality profile associated with fruit ripening, in support of traditional analysis methods. Delayed Luminescence measurements have been performed on cherry tomatoes, with and without the PGI "Pomodoro di Pachino" certification, harvested from two different growing areas of south-eastern Sicily (Italy). Then, DL emissions were correlated with soluble solid content and titratable acidity values, which are known to affect the flavor, the commerciality and the maturity degree of tomato fruits. In addition, we evaluated the changes in the DL parameters with respect to the geographical origin of the cherry tomatoes, with the aim of testing the possibility of applying the technique for identification purposes. The signals of Delayed Luminescence appeared to be good indicators of the macromolecular structure of the biological system, revealing structural changes related to the content of total soluble solids present in the juice of tomatoes analyzed, and they appeared unsuitable for authenticating vegetable crops, since the differences in the photon yields emitted by tomato Lots were not related to territory of origin. Thus, our results suggest that DL can be used as a nondestructive indicator of important parameters linked to tomato fruit quality.

Vibrational Spectroscopy as a Tool for Bioanalytical and Biomonitoring Studies

The review briefly describes various types of infrared (IR) and Raman spectroscopy methods. At the beginning of the review, the basic concepts of biological methods of environmental monitoring, namely bioanalytical and biomonitoring methods, are briefly considered. The main part of the review describes the basic principles and concepts of vibration spectroscopy and microspectrophotometry, in particular IR spectroscopy, mid- and near-IR spectroscopy, IR microspectroscopy, Raman spectroscopy, resonance Raman spectroscopy, Surface-enhanced Raman spectroscopy, and Raman microscopy. Examples of the use of various methods of vibration spectroscopy for the study of biological samples, especially in the context of environmental monitoring, are given. Based on the described results, the authors conclude that the near-IR spectroscopy-based methods are the most convenient for environmental studies, and the relevance of the use of IR and Raman spectroscopy in environmental monitoring will increase with time.

Using Molecular Spectroscopic Techniques (NIR and ATR-FT/MIR) Coupling with Various Chemometrics to Test Possibility to Reveal Chemical and Molecular Response of Cool-Season Adapted Wheat Grain to Ergot Alkaloids

The objectives of this study were to explore the possibility of using near infrared (NIR) and Fourier transform mid-infrared spectroscopy-attenuated total reflectance (ATR-FT/MIR) molecular spectroscopic techniques as non-invasive and rapid methods for the quantification of six major ergot alkaloids (EAs) in cool-season wheat. In total, 107 wheat grain samples were collected, and the concentration of six major EAs was analyzed using the liquid chromatography-tandem mass spectrometry technique. The mean content of the total EAs-ergotamine, ergosine, ergometrine, ergocryptine, ergocristine, and ergocornine-was 1099.3, 337.5, 56.9, 150.6, 142.1, 743.3, and 97.45 μg/kg, respectively. The NIR spectra were taken from 680 to 2500 nm, and the MIR spectra were recorded from 4000-700 cm-1. The spectral data were transformed by various preprocessing techniques (which included: FD: first derivative; SNV: standard normal variate; FD-SNV: first derivative + SNV; MSC: multiplicative scattering correction; SNV-Detrending: SNV + detrending; SD-SNV: second derivative + SNV; SNV-SD: SNV + first derivative); and sensitive wavelengths were selected. The partial least squares (PLS) regression models were developed for EA validation statistics. Results showed that the constructed models obtained weak calibration and cross-validation parameters, and none of the models was able to accurately predict external samples. The relatively low levels of EAs in the contaminated wheat samples might be lower than the detection limits of the NIR and ATR-FT/MIR spectroscopies. More research is needed to determine the limitations of the ATR-FT/MIR and NIR techniques for quantifying EAs in various sample matrices and to develop acceptable models.

Spray drying encapsulation of essential oils; process efficiency, formulation strategies, and applications

Essential oils (EOs) have many beneficial qualities, including antimicrobial, antioxidant, antiviral, and antifungal activities, along with good aroma, which have played a significant role in pharmaceutical, textile, and food industries. However, their high volatility and sensibility to external factors, as well as susceptibility to deterioration caused by environmental and storage conditions, or even common processing, and consequently limited water solubility, makes it difficult to incorporate them into aqueous food matrices and limits their industrial application. Spray-drying encapsulation has been proposed as a solution and a challenging research field to retard oil oxidation, extend EO's shelf life, improve their physicochemical stability, achieve controlled release, suggest novel uses, and therefore boost their added value. The objective of this review is to discuss various used wall materials, infeed emulsion properties, the main formulation and process variables affecting the physicochemical properties and release characteristics of the EOs-loaded particles obtained by spray-drying, the stability of EOs during storage, and the applications of encapsulated EOs powders in foods and nutrition, pharmaceuticals, and textile industries. The current review also summarizes recent advances in spray drying approaches for improving encapsulation efficiency, flavor retention, controlled release, and applicability of encapsulated EOs, thereby expanding their use and functionalities.

Fine Mapping and Functional Analysis of Major Regulatory Genes of Soluble Solids Content in Wax Gourd (Benincasa hispida)

Soluble solids content (SSC) is an important quality trait of wax gourd, but reports about its regulatory genes are scarce. In this study, the SSC regulatory gene BhSSC2.1 in wax gourd was mined via quantitative trait locus (QTL) mapping based on high-density genetic mapping containing 12 linkage groups (LG) and bulked segregant analysis (BSA)-seq. QTL mapping and BSA-seq revealed for the first time that the SSC QTL (107.658–108.176 cM) of wax gourd was on Chr2 (LG2). The interpretable phenotypic variation rate and maximum LOD were 16.033% and 6.454, respectively. The QTL interval contained 13 genes. Real-time fluorescence quantitative expression analysis, functional annotation, and sequence analysis suggested that Bch02G016960, named BhSSC2.1, was a candidate regulatory gene of the SSC in wax gourd. Functional annotation of this gene showed that it codes for a NADP-dependent malic enzyme. According to BhSSC2.1 sequence variation, an InDel marker was developed for molecular marker-assisted breeding of wax gourd. This study will lay the foundation for future studies regarding breeding and understanding genetic mechanisms of wax gourd.

High performance liquid chromatographic method with post-column detection for quantification of reducing sugars in foods

A novel liquid chromatographic analysis method with post-column detection for sugars was developed to improve existing methods in regard to operation time, selectivity, and sensitivity. This method involves separation of reducing sugars on HPLC column at 30 °C and 0.8 mL min^-1 flow rate, post-column reaction of sugars with Cu(II)-neocuproine (Nc) reagent at 80 °C and 0.3 mL min^-1 flow rate, and measurement of Cu(I)-Nc product at 450 nm. The proposed assay was applied to glucose, fructose, maltose, and lactose as reducing sugars. Non-reducing sucrose was determined indirectly, after conversion to its constitutive monomers glucose and fructose by hydrolysis, and analysis with a relative error from -2.41 to 2.09%. Honey, apple juice, and milk samples were evaluated as commercial products. The results obtained with the proposed assay compared to those of the alkaline Cu(II)-Nc reference method were found close to each other, and compatible with the label values of commercial products. The accuracy of the developed method was performed by spiking glucose to honey and lactose to milk samples using two different concentrations. The obtained recoveries with respect to the post-column HPLC method were between 97 and 105% for honey and 96-107% for milk. The method gave linear responses against sugar concentration with correlation coefficients greater than 0.996 for the four analytes (glucose, fructose, maltose and lactose) in a range of 9.0 - 342.3 mg L^-1 with LOD values ≤ 7.4 mg L^-1. With the developed method, it was possible to sensitively determine reducing sugars in various food samples at a lower temperature of post-column reaction (compared to literature values) with easy application of low cost reagents requiring minimal preliminary operation.

Detection of adulterated sugar with plastic packaging based on spatially offset Raman imaging

BACKGROUND

The application of optical sensing technology in food adulteration detection has been extensively studied. However, due to the impact of packaging materials on the penetration depth of photons in foods and the interference from the optical properties of the packaging materials themselves, the use of optical sensing technology to detect packaged foods adulteration is still a well-known problem.

RESULTS

The line-scan Raman imaging system was used to collect Raman hyperspectral images of adulterated sugars, made by mixing soft sugar and cheap glucose in seven different ratios. With the 0 and 3 mm (optimal offset distance) between line-laser source and scanning line, the Raman hyperspectral images of adulterated sugars covered by packaging plastic were acquired respectively. Using adulterated samples un-covered by packaging plastic as training samples, the Random Forest prediction model was developed, and excellent prediction performance was achieved for adulterated samples un-covered by packaging plastics. Compared with Raman data acquired with 0 mm offset distance, the performance of the prediction model was significantly improved, with 0.957 for coefficient of determination (R² ), 0.413 for root mean square error of prediction (RMSEP), and 4.846 for residual predictive deviation (RPD), for adulterated samples with plastic packaging acquired with the 3 mm offset distance.

CONCLUSIONS

The novel non-destructive method based on spatially offset Raman imaging technology, which can reduce the interference of packaging materials and enhance the signal of internal interesting materials, was proposed for detection of adulterated sugar with plastic packaging. The experiment results show that spatially offset imaging technology provides a candidate method for detecting adulteration of packaged foods. © 2021 Society of Chemical Industry.

Nondestructive Detection of Weight Loss Rate, Surface Color, Vitamin C Content, and Firmness in Mini-Chinese Cabbage with Nanopackaging by Fourier Transform-Near Infrared Spectroscopy

A nondestructive optical method is described for the quality assessment of mini-Chinese cabbage with nanopackaging during its storage, using Fourier transform-near infrared (FT-NIR) spectroscopy. The sample quality attributes measured included weight loss rate, surface color index, vitamin C content, and firmness. The level of freshness of the mini-Chinese cabbage during storage was divided into three categories. Partial least squares regression (PLSR) and the least squares support vector machine were applied to spectral datasets in order to develop prediction models for each quality attribute. For a comparative analysis of performance, the five preprocessing methods applied were standard normal variable (SNV), first derivative (lst), second derivative (2nd), multiplicative scattering correction (MSC), and auto scale. The SNV-PLSR model exhibited the best prediction performance for weight loss rate (Rp2 = 0.96, RMSEP = 1.432%). The 1st-PLSR model showed the best prediction performance for L* value (Rp2 = 0.89, RMSEP = 3.25 mg/100 g), but also the lowest accuracy for firmness (Rp2 = 0.60, RMSEP = 2.453). The best classification model was able to predict freshness levels with 88.8% accuracy in mini-Chinese cabbage by supported vector classification (SVC). This study illustrates that the spectral profile obtained by FT-NIR spectroscopy could potentially be implemented for integral assessments of the internal and external quality attributes of mini-Chinese cabbage with nanopacking during storage.

Brazilian native passion fruit (Passiflora tenuifila Killip) is a rich source of proanthocyanidins, carotenoids, and dietary fiber

Passiflora tenuifila is a Brazilian native passion fruit consumed by the local population and is a dietary source of bioactive compounds with potential biological activity. The aim of this study is to evaluate the nutritional value of P. tenuifila fruit and its bioactive compounds at two ripening stages. Three batches of fruit were collected at mature-green and ripe stages, and phenolic compounds, carotenoids, and polyamines were analyzed by HPLC-DAD and LC-MS/MS. The fruit is a good source of dietary fiber. Proanthocyanidin dimers are the major phenolic compounds (up to 84%) at both stages, followed by the C-glycosylated luteolin. Lutein and β-carotene are the major carotenoids, contributing up to 50% of total carotenoids. The OPLS-DA segregates the mature-green and ripe fruits, as carotenoids are responsible for this separation. In conclusion, passion fruit can be consumed at both stages of maturation without losses of bioactive compound contents or nutritional value.

Systemic antioxidant and anti-inflammatory effects of yellow passion fruit bagasse extract during prostate cancer progression

We evaluated the impact of yellow passion fruit (Passiflora edulis sp.) bagasse extract (PFBE) administration in systemic oxidative and inflammatory parameters in vivo, considering prostate cancer progression in transgenic mice (TRAMP). Piceatannol, scirpusin-B, dicaffeoylquinic acid, citric acid, and (+)-catechin were identified in PFBE, and the extract showed high in vitro antioxidant capacity. Some alterations in systemic parameters were verified during prostate cancer progression, as the increase in ALT and MDA levels, and SOD and GPx activities in the plasma. In the liver, higher MDA, TNF-α, and NF-κB levels, and GR and GPx activities were verified. Compared to their respective controls, the short- and long-term PFBE administration reduced MDA levels in the liver and plasma. The long-term treatment increased the catalase activity in the plasma, while the short-term treatment increased the hepatic SOD and catalase activities. Still, a reduction in hepatic TNF-α and NF-κB levels was verified after long-term treatment. PRACTICAL APPLICATIONS: Prostate cancer progression is associated with changes in systemic redox status and inflammation markers. Moreover, the intake of polyphenols with antioxidant properties, besides delaying prostate carcinogenesis, may improve the systemic antioxidant defenses and inflammatory response. In vitro studies pointed to a promising antioxidant and anti-inflammatory potential of yellow passion fruit bagasse. However, in vivo studies are scarce. Our results provided information about in vivo impacts of PFBE oral consumption on antioxidant defense and inflammation, indicating its potential as an adjuvant during the initial steps of prostate cancer.

Current strategies to guarantee the authenticity of coffee

As they become more health conscious, consumers are paying increasing attention to food quality and safety. In coffee production, fraudulent strategies to reduce costs and maximize profits include mixing beans from two species of different economic value, the addition of other substances and/or foods, and mislabeling. Therefore, testing for coffee authenticity and detecting adulterants is required for value assessment and consumer protection. Here we provide an overview of the chromatography, spectroscopy, and single-nucleotide polymorphism-based methods used to distinguish between the major coffee species Arabica and Robusta. This review also describes the techniques applied to trace the geographical origin of coffee, based mainly on the chemical composition of the beans, an approach that can discriminate between coffee-growing regions on a continental or more local level. Finally, the analytical techniques used to detect coffee adulteration with other foods and/or coffee by-products are discussed, with a look at the practice of adding pharmacologically active compounds to coffee, and their harmful effects on health.

Changes in the Content of Organic Acids and Expression Analysis of Citric Acid Accumulation-Related Genes during Fruit Development of Yellow (Passiflora edulis f. flavicarpa) and Purple (Passiflora edulis f. edulis) Passion Fruits

Organic acids are key components that determine the taste and flavor of fruits and play a vital role in maintaining fruit quality and nutritive value. In this study, the fruits of two cultivars of passion fruit Yellow (Passiflora edulis f. flavicarpa) and purple (Passiflora edulis f. edulis) were harvested at five different developmental stages (i.e., fruitlet, green, veraison, near-mature and mature stage) from an orchard located in subtropical region of Fujian Province, China. The contents of six organic acids were quantified using ultra-performance liquid chromatography (UPLC), activities of citric acid related enzymes were determined, and expression levels of genes involved in citric acid metabolism were measured by quantitative real-time PCR (qRT-PCR). The results revealed that citric acid was the predominant organic acid in both cultivars during fruit development. The highest citric acid contents were observed in both cultivars at green stage, which were reduced with fruit maturity. Correlation analysis showed that citrate synthase (CS), cytosolic aconitase (Cyt-ACO) and cytosolic isocitrate dehydrogenase (Cyt-IDH) may be involved in regulating citric acid biosynthesis. Meanwhile, the PeCS2, PeACO4, PeACO5 and PeIDH1 genes may play an important role in regulating the accumulation of citric acid. This study provides new insights for future elucidation of key mechanisms regulating organic acid biosynthesis in passion fruit.

Progress in pretreatment and analysis of organic Acids: An update since 2010

Organic acids, as an important component of food, have great influence on the flavor, texture, freshness of food. By lowering the pH of food to bacteriostatic acidity, organic acids are also used as additives and preservatives. Because organic acids are crucial to predict and evaluate food maturity, production and quality control, the rapid and sensitive determination methods of organic acids are necessary. This review aims to summarize and update the progress of the determination of organic acids in food samples. Pretreatment methods include simple steps (e.g., "dilute and shoot," protein precipitation, filtration, and centrifugation) and advanced microextraction methods (e.g., hollow fiber liquid phase microextraction, stir bar sorptive extraction and dispersive micro-solid phase extraction). Advances in novel materials (nanomaterial), solvents (ionic liquids and supercritical fluids) and hybrid methods are clearly displayed in detail. Continuous progress which has been made in electrochemical method, two-dimensional chromatography, high resolution mass is thoroughly illustrated.

Non-invasive quantification of vitamin C, citric acid, and sugar in 'Valência' oranges using infrared spectroscopies

Near (NIR) and mid (MIR) infrared spectroscopies have been studied as potential methods for non-destructive analyses of the fresh fruits quality. In this study, vitamin C, citric acid, total and reducing sugar content in 'Valência' oranges were evaluated using NIR and MIR spectroscopy with multivariate analysis. The spectral data were used to build up prediction models based on PLS (Partial Least Squares) regression. For vitamin C and citric acid, both NIR (r = 0.72 and 0.77, respectively) and MIR (0.81 and 0.91, respectively) resulted in feasible models. For sugars determination the two techniques presented a strong correlation between the reference values and analytical signals, with low RMSEP and r > 0.70 (NIR: sucrose RMSEP = 12.2 and r = 0.75; glucose RMSEP = 6.77 and r = 0.82; fructose RMSEP = 5.07 and r = 0.81; total sugar RMSEP = 12.1 and r = 0.80; reducing sugar RMSEP = 20.32 and r = 0.82; MIR: sucrose RMSEP = 9.47 and r = 0.80; glucose RMSEP = 6.70 and r = 0.82; fructose RMSEP = 5.20 and r = 0.81; total sugar RMSEP = 11.72 and r = 0.81; reducing sugar RMSEP = 20.42 and r = 0.81). The models developed with MIR presented lower prediction error rates than those made with NIR. Therefore, infrared techniques show applicability to determine of orange quality parameters in a non-destructive way.

In Situ Monitoring of Sugar Content in Breakfast Cereals Using a Novel FT-NIR Spectrometer

This research demonstrates simultaneous predictions of individual and total sugars in breakfast cereals using a novel, handheld near-infrared (NIR) spectroscopic sensor. This miniaturized, battery-operated unit based on Fourier Transform (FT)-NIR was used to collect spectra from both ground and intact breakfast cereal samples, followed by real-time wireless data transfer to a commercial tablet for chemometric processing. A total of 164 breakfast cereal samples (60 store-bought and 104 provided by a snack food company) were tested. Reference analysis for the individual (sucrose, glucose, and fructose) and total sugar contents used high-performance liquid chromatography (HPLC). Chemometric prediction models were generated using partial least square regression (PLSR) by combining the HPLC reference analysis data and FT-NIR spectra, and associated calibration models were externally validated through an independent data set. These multivariate models showed excellent correlation (Rpre ≥ 0.93) and low standard error of prediction (SEP ≤ 2.4 g/100 g) between the predicted and the measured sugar values. Analysis results from the FT-NIR data, confirmed by the reference techniques, showed that eight store-bought cereal samples out of 60 (13%) were not compliant with the total sugar content declaration. The results suggest that the FT-NIR prototype can provide reliable analysis for the snack food manufacturers for on-site analysis.

Monitoring of soluble pectin content in orange juice by means of MIR and TD-NMR spectroscopy combined with machine learning

This study represents a rapid and non-destructive approach based on mid-infrared (MIR) spectroscopy, time domain nuclear magnetic resonance (TD-NMR), and machine learning classification models (ML) for monitoring soluble pectin content (SPC) changes in orange juice. Current reference methods of SPC in orange juice are laborious, requiring several extractions with successive adjustments hindering rapid process intervention. 109 fresh orange juices samples, representing different harvests, were analysed using MIR, TD-NMR and reference method. Unsupervised algorithms were applied for natural clustering of MIR and TD-NMR data in two groups. Analyses of variance of the two MIR and TD-NMR datasets show that only the MIR groups were different at 95% confidence for SPC average values. This approach allows build classification models based on MIR data achieving 85% and 89% of accuracy. Results demonstrate that MIR/ML can be a suitable strategy for the quick assessment of SPC trends in orange juices.

Feasibility of rapid piperine quantification in whole and black pepper using near infrared spectroscopy and chemometrics

Piperine is a bioactive alkaloid that possesses various health benefits and is responsible for the pungent aroma of pepper. Piperine content in whole and ground black pepper (n = 132) was analyzed by near-infrared spectroscopy (NIRS) in the 950 to 1650 nm wavelength window. Chemometric modeling using partial least square regression was performed, and outliers were checked and removed during the preparation of the calibration curve by considering sample residual variance and sample leverage. Model accuracy was evaluated with a low root-mean-square error of cross-validation (RMSECV) and a high ratio performance to deviation (RPD). The optimal model had a coefficient of determination (R² ) of 0.726, RMSECV of 0.289 g/100 g, and RPD of 1.744 for the whole black pepper. The results of R² , RMSECV, and RPD for the ground black pepper were 0.850, 0.231 g/100 g, and 2.424, respectively. Therefore, based on the perspective of onsite process, the proposed NIRS method can be employed for selecting abnormal samples during the inspection of black pepper raw material and for quantifying piperine contents of final black pepper product. PRACTICAL APPLICATION: Generally, the quality indicators of black pepper are graded solely based on their external appearance, quality, and size. This study discloses the development of a near-infrared spectroscopy-based fast and accurate nondestructive analytical method for the detection of piperine, a bioactive constituent of pepper, as a tool for the quality control of whole and ground black pepper.

Identification and Quantification of Adulterants in Coffee (Coffea arabica L.) Using FT-MIR Spectroscopy Coupled with Chemometrics

Food adulteration is an illegal practice performed to elicit economic benefits. In the context of roasted and ground coffee, legumes, cereals, nuts and other vegetables are often used to augment the production volume; however, these adulterants lack the most important coffee compound, caffeine, which has health benefits. In this study, the mid-infrared Fourier transform spectroscopy (FT-MIR) technique coupled with chemometrics was used to identify and quantify adulterants in coffee (Coffea arabica L.). Coffee samples were adulterated with corn, barley, soy, oat, rice and coffee husks, in proportions ranging from 1–30%. A discrimination model was developed using the soft independent modeling of class analogy (SIMCA) framework, and quantitative models were developed using such algorithms as the partial least squares algorithms with one variable (PLS1) and multiple variables (PLS2) and principal component regression (PCR). The SIMCA model exhibited an accuracy of 100% and could discriminate among all the classes. The quantitative model with the highest performance corresponded to the PLS1 algorithm. The model exhibited an R²c: ≥ 0.99, standard error of calibration (SEC) of 0.39–0.82, and standard error of prediction (SEP) of 0.45–0.94. The developed models could identify and quantify the coffee adulterants, and it was considered that the proposed methodology can be applied to identify and quantify the adulterants used in the coffee industry.

Near-Infrared Spectroscopy in Bio-Applications

Near-infrared (NIR) spectroscopy occupies a specific spot across the field of bioscience and related disciplines. Its characteristics and application potential differs from infrared (IR) or Raman spectroscopy. This vibrational spectroscopy technique elucidates molecular information from the examined sample by measuring absorption bands resulting from overtones and combination excitations. Recent decades brought significant progress in the instrumentation (e.g., miniaturized spectrometers) and spectral analysis methods (e.g., spectral image processing and analysis, quantum chemical calculation of NIR spectra), which made notable impact on its applicability. This review aims to present NIR spectroscopy as a matured technique, yet with great potential for further advances in several directions throughout broadly understood bio-applications. Its practical value is critically assessed and compared with competing techniques. Attention is given to link the bio-application potential of NIR spectroscopy with its fundamental characteristics and principal features of NIR spectra.

Application of MIR Spectroscopy to the Evaluation of Chemical Composition and Quality Parameters of Foal Meat: A Preliminary Study

The aim of this work was to study the potential of mid-infrared spectroscopy to evaluate the chemical composition and quality parameters of foal meat according to differences based on slaughter ages and finishing diets. In addition, the wavelength ranges which contribute to this meat quality differentiation were also determined. Important characteristics as moisture and total lipid content were well predicted using Mid-Infrared Spectroscopy (MIR)with Rv² values of 82% and 66%, respectively. Regarding fatty acids, the best models were obtained for arachidonic, vaccenic, docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) with Rv² values over 65%. Quality parameters, as instrumental colour and texture and sensory attributes did not reach high prediction coefficients (R²). With the spectra data of the region 2198–1118 cm⁻¹, samples were accurately classified according to slaughter age (78%) and finishing diet (72%). This preliminary research shows the potential of MIR spectroscopy as an alternative tool to traditional meat chemical composition methods. Finally, the wavelength range of the spectrum from 2198 to 1118 cm⁻¹ showed good results for classification purposes.

FT-MIR determination of taste-related compounds in tomato: a high throughput phenotyping analysis for selection programs

BACKGROUND

Tomato taste is defined by the accumulation of sugars and organic acids. Individual analyses of these compounds using high-performance liquid chromatography (HPLC) or capillary zone electrophoresis (CZE) are expensive, time-consuming and are not feasible for large number of samples, justifying the interest of spectroscopic methods such as Fourier-transform mid-infrared (FT-MIR). This work analyzed the performance of FT-MIR models to determine the accumulation of sugars and acids, considering the efficiency of models obtained with different ranges of variation.

RESULTS

FT-MIR spectra (five-bounce attenuated total reflectance, ATR) were used to obtain partial least squares (PLS) models to predict sugar and acid contents in specific sample sets representing different varietal types. A general model was also developed, obtaining R² values for prediction higher than 0.84 for main components (soluble solids content, fructose, glucose, and citric acid). Root mean squared error of prediction (RMSEP) for these components were lower than 15% of the mean contents and lower than 6% of the highest contents. Even more, the model sensitivity and specificity for those variables with a 10% selection pressure was 100%. That means that all samples with the 10% highest content were correctly identified. The model was applied to an external assay and it exhibited, for main components, high sensitivities (> 70%) and specificities (> 96%). RMSEP values for main compounds were lower than 21% and 13% of the mean and maximum content respectively.

CONCLUSION

The models obtained confirm the effectiveness of FT-MIR models to select samples with high contents of taste-related compounds, even when the calibration has not been performed within the same assay. © 2019 Society of Chemical Industry.

Evaluation of near-infrared (NIR) and Fourier transform mid-infrared (ATR-FT/MIR) spectroscopy techniques combined with chemometrics for the determination of crude protein and intestinal protein digestibility of wheat

The potential of using the near-infrared (NIR) and Fourier transform mid-infrared (ATR-FT/MIR) spectroscopy for the determination of intestinal crude protein (CP) digestibility (IPD) of wheat was evaluated. For CP, the best NIR model showed an excellent prediction performance (R² = 0.98); the best MIR model also gave an excellent prediction performance (R² = 0.96). Regarding to IPD, the best model obtained by NIR technique showed approximate quantitative predictive ability (R² = 0.68), and the best model generated by MIR technique obtained similar prediction performance (R² = 0.67). NIR models generally showed better predictive abilities than MIR models, which may be due to the MIR spectra record fundamental molecular vibrations and can be more easily affected by multiple interferences. The amide I and II bands played important roles in the development of PLS models for CP and IPD. Results from this study demonstrated the potential of using IR spectroscopy for the prediction of nutrient digestibility while more efforts are required to improve the performance of NIR and ATR-FT/MIR spectroscopy in predicting the IPD of wheat.

Antioxidant properties and chemical characterization of Spanish Opuntia ficus-indica Mill. cladodes and fruits

BACKGROUND

Recent studies have demonstrated that consumption of Opuntia ficus-indica Mill. has an important positive health benefit, mainly due to antioxidant properties, which justifies this research. This study examined antioxidant activity, organic acid and sugar profile, total phenolic, and physicochemical characteristics of six O. ficus-indica cultivars growing in the Spanish Mediterranean. It should be noted that, in this study, both cladodes (young and adult) and fruits (peel and pulp) were analyzed.

RESULTS

The antioxidant activity (2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) and 2,2-diphenyl-1-picrylhydrazyl methods) was higher in fruit peel than in cladodes. The young cladodes presented an important antioxidant activity by the ferric-reducing ability of plasma method as well as a higher total phenolic content (18.90 g gallic acid equivalent per kilogram). High-performance liquid chromatography (HPLC) with diode-array detector analysis revealed the absence of sucrose and the presence of glucose and fructose, which the values were higher in pulp fruits. HPLC with refractive index detector analysis showed that citric, malic, and succinic acids were the main organic acids in all cultivars, with a significant higher content in old cladodes.

CONCLUSION

These investigations valorize O. ficus-indica fruits in comparison with cladodes. In general, this plant can be considered as an ingredient for the production of health-promoting food, highlighting mainly in the antioxidant activity and total polyphenols content found in young cladodes and peel fruits. © 2017 Society of Chemical Industry.

Nutritional Composition and Antioxidant Properties of the Fruits of a Chinese Wild Passiflora foetida

The aim of this work was to evaluate the main nutrients and their antioxidant properties of a Chinese wild edible fruit, Passiflora foetida, collected from the ecoregion of Hainan province, China. The analytical results revealed that P. foetida fruits were rich in amino acids (1097 mg/100 g in total), minerals (595.75 mg/100 g in total), and unsaturated fatty acids (74.18 g/100 g in total fat). The lyophilized powder of edible portion contained the higher polyphenols content than the inedible portion powder. The UPLC-Q-TOF-MSE analysis of the extractable and non-extractable phenolics indicated the presence of 65 compounds including 39 free phenolics, 14 insoluble-glycoside-phenolics, and 22 insoluble-ester-phenolics. In addition, the non-extractable phenolics obtained by alkali hydrolysis showed significant antioxidant activities by/through DPPH and ABTS radical scavenging. These findings of P. foetida fruits, for the first time, suggest that these polyphenol-rich fruits may have potential nutraceutical efficacies.

Calibration Procedure for Attenuation Coefficient Measurements in Highly Opaque Media Using Infrared Focal Plane Array (IRFPA) Spectroscopy

The purpose of this article is to present a new calibration procedure for spectroscopic measurements using an infrared focal plane array (IRFPA) spectrometer on highly opaque middle-wave infrared (MWIR) media. The procedure is based on the properties of the IRFPA camera and especially the integration time (IT), which is the main parameter that can be adjusted to control the sensitivity of the measurements. The goal of the paper is to experimentally validate this dependence with the direct reference intensity light coming out of the IR monochromator in order to predict the spectrum shape and intensity level in a range out of the camera saturation. This method allows determining spectrum used as background for transmittance calculation. It has been applied in the case of measurement of water transmittance, which is a highly opaque medium and whose measurement requires high ITs. The main result is the ability to take an IR spectroscopic imaging measurement through 300 µm of water and the determination of its transmittance with sufficient sensitivity due to the proposed calibration procedure. This procedure allows the possibility of transitory studies in heterogeneous aqueous media.

Non-destructive and rapid evaluation of aflatoxins in brown rice by using near-infrared and mid-infrared spectroscopic techniques

The applicability of near-infrared (NIR) and mid-infrared (MIR) spectroscopy combined with chemometrics was explored in this study to develop rapid, low-cost and non-destructive spectroscopic methods for classification and quantification of aflatoxins in brown rice. A total of 132 brown rice samples within the aflatoxin concentration range of 0-2435.8 μg/kg were prepared by artificially inoculated with A. flavus and A. parasiticus strains of fungus. For the classification of samples at varying levels of aflatoxin B₁, the linear discriminant analysis model obtained correct classification rate of 96.9 and 90.6% for NIR and MIR spectroscopy, respectively. For the simultaneous determination of aflatoxins B₁, B₂, G₁, G₂ and the total aflatoxins, partial least squares regression also showed good predictive accuracy for both NIR (r_v  = 0.936-0.973, RPD = 2.5-4.0) and MIR spectroscopy (r_v  = 0.922-0.970, RPD = 2.5-4.0). The overall results indicated that the two spectroscopic techniques offered the feasibility to be used as alternative tools for rapid detection of various aflatoxin contaminations in grain.