Spectroscopic Methods of Edible Flower Authentication and Quality Control for Food Applications

The incorporation of edible flowers in the human diet and culinary preparations dates back to ancient times. Nowadays, edible flowers have gained great attention due to their health-promoting and nutritive effects and their widespread acceptance by consumers. Therefore, edible flowers are ideal candidates for use in the design and development of functional foods and dietary supplements, representing a new and promising trend in the food industry. Thus, the present study attempts to assess the potential of various edible flowers against oxidative stress by applying a combination of in vitro, in silico and spectroscopic techniques. Specifically, the spectroscopic profiles of edible flower extracts were evaluated using ATR-FTIR spectroscopy, while their total phenolic contents and antioxidant/antiradical activities were determined spectrophotometrically. The most abundant phytochemicals in the studied flowers were examined as enzyme inhibitors through molecular docking studies over targets that mediate antioxidant mechanisms in vivo. Based on the results, the red China rose followed by the orange Mexican marigold exhibited the highest TPCs and antioxidant activities. All samples showed the characteristic FTIR band of the skeletal vibration of phenolic aromatic rings. Phenolic compounds seem to exhibit antioxidant activity with respect to NADPH oxidase, myeloperoxidase (MP), cytochrome P450 and, to a lesser extent, xanthine oxidase (XO) enzymes.

This comprehensive examination delves into the multifaceted characteristics of edible flowers, underlining their significance as sources of natural ingredients and their medicinal properties. The review commences with an introductory section emphasizing edible flowers' cultural and health importance. It proceeds to explore the botanical diversity of edible flowers, encompassing their geographical distribution. Emphasis is placed on the bioactive constituents of these flowers, with a focus on their potential health benefits and various molecular targets for the treatment of several chronic disorders. Culinary and medicinal uses are examined, illustrating their adaptability across diverse cultural contexts. Their nutritional richness is highlighted through comparative analysis. Safety considerations and regulatory frameworks ensure consumer protection. Future prospects underscore innovation, discussing potential applications in the food industry and avenues for further research. The analysis concludes by summarizing key findings and discussing future implications, highlighting the intriguing potential of edible flowers as natural components for various applications in food, health, and beyond.Graphical abstract

Phytochemicals screening, antioxidant capacity and chemometric characterization of four edible flowers from Brazil.

Edible flowers as sources of bioactive compounds: Determination of phenolic extraction conditions

Flowers have been commonly used in cooking to add color and flavor to dishes. In addition to enhancing the visual appeal of food, many edible flowers also contain bioactive compounds that promote good health. These compounds include antimicrobial, antihypertensive, nephroprotective, antiulcer, and anticancer agents. In the last 5 years, there have been 95 published reviews about edible flowers. Among these, 43% have concentrated on Food Science and Technology, while 32% have analyzed their effects on human health. Most of these edible flowers are commonly consumed, but some are less known due to limited distribution or seasonality. These lesser-explored flowers often contain compounds that offer significant health advantages. Therefore, this review focuses on exploring the characteristics, phytochemical composition, and bioactive compounds found in less commonly examined edible flowers. The flowers included in this review are peonies, forget-me-nots, frangipani, alpine roses, wild roses, hibiscus species, common lilacs, woodland geraniums, camellias, Aztec marigolds, kiri flowers, sunflowers, yucca flower, hollyhocks, and cornflowers. Due to their diverse biological activities, these flowers provide various health benefits and can be used to be incorporated into food and supplements or develop mainly cancer-fighting medications.

Two commonly consumed, yet under-researched, edible flowers—Malvaviscus arboreus (Topi Turki) and Acmella paniculata (Jotang)—were comprehensively analyzed to assess their potential as functional food sources. This study investigated their nutritional content, phytochemical profiles, antioxidant activity, and organoleptic properties. Our methodology, conducted between July and December, 2024, involved a multi-faceted approach—proximate analysis quantified ash, moisture, protein, fat, fiber, carbohydrates, and total energy. Freeze-dried samples underwent LC-MS for phytochemical identification, and antioxidant activity was determined using the DPPH assay. Organoleptic preferences were evaluated through a hedonic test where 30 panelists rated color, aroma, taste, and overall acceptance. Key findings revealed distinct differences. A. paniculata presented higher protein (18.75%), fat (21.71%), and fiber (24.10%), leading to a greater total energy (213.84 kcal/50g). In contrast, M. arboreus showed higher moisture (21.22%) and carbohydrates (48.12%). Phytochemical profiling by LC-MS indicated that M. arboreus contained 51 phytochemicals, primarily phenolics (13.52%), while A. paniculata had a remarkable 170 phytochemicals, dominated by alkaloids (2.94%). Importantly, M. arboreus demonstrated superior antioxidant activity (IC50 92.74 µg/mL, strong) compared to A. paniculata (IC50 156.95 µg/mL, weak) in the DPPH assay. Organoleptically, M. arboreus was preferred for its color, taste, and overall acceptability, with no significant difference in aroma. Overall, both M. arboreus and A. paniculata exhibit promising nutritional value and bioactive potential for functional food applications. This research highlights the significant potential of these edible flowers to diversify plant-based diets and contribute to the development of novel health-promoting products. Future research should focus on optimizing processing techniques and exploring diverse food applications to maximize their utilization.

Chronic stress and elevated cortisol levels can compromise intestinal barrier function, potentially leading to leaky gut syndrome and associated health conditions. The probiotic potential of novel strains isolated from honey and edible flowers was evaluated in the present study. Five strains identified as Lactiplantibacillus plantarum (MP), Enterococcus lactis (PERI), Lactiplantibacillus plantarum (PARI), Lactocasiebacillus rhamnosus (M1A), and Enterococcus nangengnisis (KK) exhibited strong bile salt hydrolase (BSH) activity. Furthermore, these strains produced short-chain fatty acids, including acetic acid (8.0 to 10.0mM), butyric acid (0.3 to 0.5mM) and propionic acid (1.8 to 2.5mM), known to support gut health and immune modulation. Under chronic cortisol exposure, L. rhamnosus (M1A), L. plantarum (BAN), and L. plantarum (PARI) significantly alleviated tight junction disruption, experimentally proven by FITC dextran leakage and gene expression of zona occludin-1 (≤3-fold increase) and cadherin (≤4.36-fold increase) compared to the cortisol-treated CaCo2 cell model. These findings indicate that the novel probiotic strains can enhance intestinal barrier integrity under chronic stress conditions in a model system; however, they warrant further investigation for their potential application in functional foods targeting gut health. PRACTICAL APPLICATIONS: Probiotic consumption improves gut microbiota balance and thereby enhances immune responses. Natural sources, including honey and edible flowers, are gaining attention for having a rich diversity of Lactic acid bacteria, which are known to have probiotic properties. Lactic acid bacterial strains isolated from these sources in the present study showed probiotic activity and produced short-chain fatty acids, supporting gastrointestinal health and immune responses. These strains can be used to develop functional food products for better gut health and overall well-being.

Background: Torch ginger (Etlingera elatior) is an edible flower whose inflorescence is utlized for culinary purposes to enchance the taste of traditional dishes containing polyphenols and antioxidant compounds. However, investigation on the phytochemical profile and antioxidant activity of torch ginger inflorescence extract following simulated gastrointesinal digestion is still limited. Objective: This study aims to determine the phytochemical profile and evaluate the antioxidant activity of the inflorescence extract after in vitro simulated digestion. Methods: Torch ginger inflorescence (TGI) was extracted by ultrasound-assisted extraction with different solvents (water,50%, and 80% aqueous ethanol). Total phenolics content (TPC), total flavonoid content (TFC), and antioxidant activity were determined by ORAC, DPPH, FRAP, and metal ion (Fe2+) chelating activity. The solvent extraction that gave the highest value of TPC, TFC, and antioxidant activities was used for an in vitro digestion and identification of phytochemicals profile by LC-ESI-QTOF-MS/MS. Furthermore, the TPC, TFC, and antioxidant capacities of digested TGI extract were compared to those of undigested extract. Results: TGI contained 90.24% moisture. The 80% aqueous ethanol extract exhibited the highest antioxidant capacity, with an ORAC value of 1,156.61 ± 11.55 mM TE/g extract, DPPH radical scavenging capacity of 1,087.68 ± 14.37 mM TE/g extract, FRAP value of 799.30 ± 1.45 mM TE/g extract, and Fe2+ chelating capacity of 42.32 ± 3.48% /mg extract. The 39 phytochemicals were identified for 9 flavonoids and 5 phenolic acids. The putative bioactive compounds for antioxidant, anticancer, anti-inflammatory, and anticholesterol were detected in TGIE, such as catechin, 2-hydroxycinnamic acid, astragalin, chlorogenic acid, coumarin, and procyanidin B2. After passing through an in vitro simulated mouth, gastric, and intestinal digestion, the TGI extract exhibited higher values of TPC, TFC, and antioxidative capacities than the undigested extract. Conclusion: This study reviewed the phytochemical components presented in the 80% aqueous ethanol TGIE. The expressed antioxidant capacity was increased when the TGIE passed through the in vitro simulated digestion, which could potentially represent a promising source of endogenous antioxidants in food and nutraceutical applications. Keywords: Antioxidant, edible flower, gastrointestinal digestion, phytochemicals, Torch ginger inflorescence

Applications of Raman spectroscopy in art and archaeology

This report with recommendations is the result of an expert panel meeting on PAT applications in food industry that was organized by the M3C Section of the European Society of Biochemical Engineering Science (ESBES) at the 10th ESBES Symposium. The aim of the panel was to provide an update on the present status of the subject and to identify critical needs and issues for wider applications of PAT in food industry. A brief description of the current state-of-the-art and industrial uptake of the methodology is provided in this report. It concludes with a number of recommendations to facilitate further developments and a wider application of PAT in food industry. Process Analytical Technologies (PAT) [1] (European Medicines Agency EMA-FDA pilot program for parallel assessment of Quality by Design applications; Document EMA/172347/2011) have been extensively discussed in literature, particularly with respect to (bio)pharmaceutical process modelling, monitoring and control [2]. Table 1 provides an historic overview of the PAT development in the context of food applications. Although successful applications within food industry are increasingly being reported [3, 4], the session on PAT in food industries at the ESBES-IFIBiop 2014 in Lille highlighted significant challenges and opportunities for further development in this area. This position paper briefly reviews the current state-of-the-art, industrial needs and opportunities as well as scientific challenges to be addressed in order to extend the use of PAT methodology in the food industries. Currently, quality and safety control are still based mainly on discontinuous analysis with traditional analytical methods in the lab or, at best, at-line measurements. This is no longer sufficient to fulfill the needs of the food industry. Due to higher safety and quality standards and demands and high throughput of production facilities, the number of samples to be analyzed is increasing. Rapid analysis methods and PAT are required to address these needs along the complete production chain leading to a better understanding and control of raw materials, intermediate products in the production process as well as the final products to be packaged and delivered. The goal is to achieve real time analysis in order: • to avoid usage of any out-of-specification raw material and to detect adulteration, substitution, tampering and counterfeiting leading to non-authentic products; • to be able to intervene and stop/change processes in order to secure the target quality; • to assess the final quality to avoid out-of-specification products being packaged and shipped, thus leading to undesirable customer dissatisfaction and costs associated with the resolution of complaints. Over a hundred years ago (on May 22nd, 1913) the first patent on a PAT device ("Pfeiffenanalysator" for measuring the ratio of H2 and N2 gas for ammonia synthesis) was granted to Paul Gmelin from Badische Anilin- und Soda-Fabrik, BASF (Patentschrift Nr. 281157, Klasse 42/. Gruppe 4). Since then, PAT found broad application in chemical industry, which is dominated by highly automated, continuous processes. Today in chemical processes, such as the synthesis of isocyanates, e.g. hexamethylendiisocyanate (HDI), typically 60-130 PAT measurements are collected. In contrast, in sectors like (bio)pharmaceutical or food industry, the application of PAT is significantly less frequent today, especially, in terms of on-line analytics, where the measurement takes place in or close to the production step (or unit operation). One reason for this is the reduced degree of automation of the processes in these industries, which are dominated by unit operations, single production steps consecutively executed after each other, resulting in production batches. Analytics of a production batch takes place mostly off-line in analytical laboratories during hold-up times of the process intermediate between the different unit operations. Regulatory requirements represent an equally important driver for extensive online analytics. With the 2004 FDA's Quality by Design initiative, regulatory agencies demand systematic risk based process development and understanding of the processing space. This also allows for flexible process adjustments within the explored space for producing the desired product quality. In order to achieve the required understanding, more extensive analytical data is required, ideally obtained in-time on raw materials, process intermediates and ideally also on product quality attributes. In food industry, where typically high product titers are obtained, product analytics is sometimes possible by in-line measurements, such as spectroscopy (section 4). In biopharmaceutical processes, product titers are usually very low, the products are proteins with high molecular weight, and quality attributes are challenging to analyse. In these situations, online sampling with automated sample preparation and analytics may open up a solution [5]. But, identifying and implementing analytical methods, which are fast enough for delivering results on product quality attributes (e.g. protein glycosylation) in time, during the unit operation for allowing process modulation, remains a challenge. The overall typical goals in industry are high safety, high and stable product quality, high yield, low consumption of resources (materials, energy, room, time, and people), reduced influence of variability in raw materials as well as an increased shelf life of products which holds also in food processes. However, compared to the chemical and biopharmaceutical industries, food industry has to deal with certain characteristics, which renders PAT a formidable challenge in this context. The characteristic features in food industry are: • Raw materials are not pure substances: they are complex combinations of pure substances with varying compositions • Raw materials are soft, variable size, fragile and slippery • Physical properties of raw materials depend heavily on temperature, pressure, moisture and harvesting, and storage conditions • Raw materials undergo usually a phase transformation during processing and hence change their physical properties during processing • Micro processes (physical, (bio)-chemical, microbiological) are frequently not known • Highly perishable products. Here the challenge is to produce good quality, which maintains for a long time (shelf life) • High demand for hygiene These characteristics lead to a challenge for the application of sensors in the food industry. For important quality and process variables, such as sensory assessment, micro flora or spoilage, reliable and robust sensors are not yet available. Moreover, the sensors which are available are typically used only in isolated applications and frequently provide insufficient reliability. They are often not integrated in a common data management infrastructure. The materials of construction do not always consider suitability of contact with food and the solutions developed within advanced research projects frequently demand high care and maintenance. One reason why PAT is not as common as in other areas is that in food industry knowledge from various subject areas is necessary (such as physics, chemistry, biology, mathematics, informatics, engineering, nutritional science). For unit operations mathematical models are available in principle, but frequently they are too complicated to adapt. One of the biggest challenges in food industries is the dynamic nature of the processes. Changes in geometry, porosity, microstructure, solubility as well as mass and energy transfer coefficients must be addressed. Mostly gradients of temperature and moisture have to be considered as well as changes in kinetic parameters during process run. End product qualities like color, smell and 'brokens' also strongly influence the process. Therefore, food processes can be considered to be significantly more complex then chemical and bio-pharmaceutical processes. To achieve more stable processes PAT applications are necessary to check the quality of the raw and processed materials and their relationship to each other. If the quality is changing, then control actions resulting in online parameter changes are required in order to maintain constant product quality. Measurement systems are required, which guarantee that the process is in accordance with recipe and formulation. Furthermore, disturbances must be compensated for using control actions to reduce process variability and to conform to food regulations. As Glassey [6] argues, PAT methodology can aid in product design and testing as well as in ensuring full compliance with the HACCP and ISO 22000:2005 requirements during processing. As demonstrated below, PAT methodologies have the potential to aid the identification of critical control points and their critical limits, their effective monitoring and control, but also effective communication with suppliers and customers. Documentation which requires measurements of important variables is especially important so that traceability can be guaranteed. Here PAT has to deliver the corresponding measurement systems. Clearly a high demand for PAT in food industry is evident as is the need for further developments in the science and technology that help address the specific challenges posed by the characteristics of the food industry highlighted above. The complexity of raw materials that are typically soft and easily damageable is arguably one of the major scientific and technological challenges in food industry. During storage and processing the quality of such raw materials can decline due to oxidation processes, pressure and temperature effects. In addition, the visual impression of the final product (i.e. its appearance) is much more important than in other industries due to the fact that this will influence the purchase decision of the consumer. During the whole processing from raw material to the storage of the final product, hygiene is of utmost importance. Therefore non-invasive sensor systems are required in these applications. Measurement systems based on optical principles are particularly suitable from this perspective. Such measurement systems, including near infrared (NIR), Raman and fluorescence spectroscopy as well as computer-assisted image-based systems, potentially have a number of advantages in food process supervision and automation. Spectroscopic methods and imaging devices are well suited for PAT purposes because they are fast, non-destructive, provide multiple chemical information, allowing remote in-process analysis via fiber optics or instruments mounted directly on-line. Fluorescence spectroscopy is the most sensitive spectroscopic technique. Recently, many applications have been developed using fluorescence techniques [3, 7, 8]. Raw materials, the supervision of processing as well as product quality and the contamination of the equipment can be monitored by fluorescence. For example, Everard et al. [3] presented a method for detection of fecal contamination on spinach leaves. They coupled three hyperspectral imaging (HSI) configurations with two multivariate image analysis techniques and compared fluorescence imaging in the visible region with ultra violet and violet excitation sources, and reflectance imaging in the visible to near-infrared regions. They showed, that both fluorescence configurations had 100% detection rates for fecal contamination up to 1:10 dilution level and violet HSI had 99% and 87% detection rates for 1:20 and 1:30 levels, respectively. Everard et al. emphasized that on-line detection of fecal contamination on leaves has the potential to reduce the cases of food borne illnesses and their associated costs. A similar approach is presented by Lee et al. [7] where bovine faeces on Romaine lettuce and baby spinach leaves were investigated. They pointed out that two-band ratios using bands at 665.6 nm and 680.0 nm for lettuce and at 660.8 nm and 680.0 nm for spinach effectively differentiated all contamination spots applied. Grote et al. [8] described a fluorescence measurement technique to monitor a sourdough fermentation process. For the prediction of pH value and acidity during rye sourdough fermentations they applied partial least squares regression and principal component regression models for prediction and compared them with an evaluation where principal component analysis was combined with artificial neural networks. Depending on process operation and evaluation technique the average percentage root mean square errors of prediction for pH values were between 2.5 and 5.1%. For the prediction of the acidity level, the best results were between 6.0 and 8.1%. Liu et al. [9] used the Hoffman reaction to convert acrylamide to a compound which shows strong fluorescence emission at 480 nm. They showed good correlation of acrylamide in the range of 0.015 μg/mL to 20 μg/mL. Using this technique the food security will be increased. A fluorescence imaging device to detect deli residues on deli slicers were used by Beck et al. [10] processing four cheeses and four processed meats. The authors suggested that a fluorescence imaging device can be applied for routine use even in delicatessens. Fig. 1 clearly shows that the application of fluorescence for the monitoring of food processes increased from less than 10 before 2003 to more than 60 a year since 2013. This figure includes all papers from a search containing the key words "Food" and "Fluorescence". Although most of these papers describe laboratory applications rather than industrial PAT applications, they indicate potential future applications in this technology in food industry. Number of published papers obtained from the Scopus database searching for the words "Food" and "Image analysis" or "Raman" or "Near infrared spectroscopy" or "Fluorescence spectroscopy". Raman spectroscopy can only be applied if no fluorescence occurs in the corresponding excitation range. He et al. [11] applied the surface enhanced Raman scattering spectroscopy to detect banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. They concluded, that Raman spectroscopy and chemometric evaluation techniques can be used to identify banned food additives to ensure food safety. Ilaslan et al. [12] presented a method based on Raman spectroscopy to provide a rapid method for evaluating the quantitative analysis of glucose, fructose, and sucrose in soft drinks. Wang et al. [13] applied a Raman spectrometer as a process analyzer to monitor the wine fermentation. They demonstrated that sugar, ethanol and glycerol can be measured on-line with high correlation (higher than 0.98) to the HPLC reference measurements. Nache et al. [14] investigated Raman spectra from pork meat to monitor the early postmortem lactate accumulation and pH decline. They suggested that the locally weighted regression applied to the standard normal variate (SNV) normalized Raman spectra provide one of the most accurate and robust models with a cross-validated coefficient of determination (r2cv) of 0.97 for pH and lactate, a cross-validated root mean square error (RMSECV) of 4.5 mmol/kg for the lactate prediction and 0.06 pH-units for the pH prediction. These results demonstrate significant potential of combining chemometrics and Raman spectroscopy for on-line meat quality control applications. Fig. 1 shows the number of papers recorded in Scopus (search words "Food" and "Raman"). Compared to fluorescence, the number of papers describing Raman spectroscopy is twice as high in recent years with a significant rate of increase, demonstrating the increasing interest in this method for food process monitoring. Computer vision systems enable one of the main aspects of consumer preference – the appearance of a product – to be inherently considered. Therefore, computer vision systems for the supervision of food processing also gained importance over the years. An overview of several examples is given by Sun [15]. Especially the supervision of food drying processes is discussed by Aghbashlo at al. [16]. They pointed out that there is a large unexploited potential in the image data captured during various food processing operations. More informative feature extraction algorithms or novel pattern recognition procedures have to be developed. Paquet-Durand et al. [4] described a system for the supervision of the baking process. They demonstrated, by using the Viola–Jones-algorithm as well as neural networks, that the pastry can be identified and the volume increase as well as color development can be monitored. To detect defective apples Zhang et al. [17] used a computer vision system, which was combined with an automatic lightness correction system. For 160 samples they showed a 95% overall detection accuracy. For the evaluation they used a weighted relevance vector machine classifier. Fig. 1 shows the number of papers over time from Scopus searching for "Food" and "Image analysis". Here the applications start earlier compared to the spectroscopic methods, the number of applications per year is higher than in the case of spectroscopic applications; except in the year 2014, where more reports of Raman applications were published. Moreover imaging systems using visible and NIR region are available to perform quality checks based on the spectroscopic information derived from each point in the image. One example is the on-line analysis of the widely varying fat distribution in salmon for sorting purposes [18]. Near infrared (NIR) is a well-established method for rapid analysis of food raw materials and products [18], either on-/in-line, at-line or off-line. In the lab or at-line multiple components such as fat, protein, moisture and many more, can be analyzed without any sample preparation in all kinds of liquid, solid and semi-solid samples. Raw materials can be verified for identity and further characterized regarding composition already in the goods reception. The composition, freshness and adulteration of edible oils [19], e.g. olive oil [20], can be analyzed rapidly before a truck is unloaded. Many other sample types like meat, grains, flour, dairy products [21] and others can be analyzed. Even mixtures like vitamin premixes can be analyzed to make sure that the correct material was delivered and can be used in production. There are several approaches and technologies for PAT available, ranging from simple filter based devices over dispersive diode array spectrometers to Fourier-Transform (FT)-NIR instruments. Samples can be analyzed in-line by fiber optic probes or by contactless systems (Fig. 2). Smaller instruments can be directly attached to pipes, chutes or in other installations. A) NIR reflection probe in a fluid bed dryer. (B) Probe head for contactless measurement of grain and other solids. Applications cover a broad range from a simple monitoring of moisture content of a product on a conveyor belt to more complex control situations. In dairy industry there are demands to control milk powder production by monitoring the feed of the spray tower and the powder after fluid bed drying. Other important production steps to control are the standardization of milk, cream, whey and concentrates [22]. In frying processes with big volumes of oil an in-line monitoring of the oil quality with regards to acid value, anisidine value and the content of polar and polymerized components [23] are of particular interest. Another example of high volume processes where monitoring of protein, moisture and ash is important is the milling of grain to flour and the production of cereals of any kind. Finally there are more and more fermentation processes controlled by in-line NIR to optimize the conditions and follow the feeding and consumption cycles during biomass buildup [24]. In 2013 roughly 120 papers were published, however the recent increase is not as steep as in the case of Raman spectroscopy (Fig. 1). The economic benefits due to PAT can be attributed to higher product quality and yield as well as decreased product variation. This will reduce the overall production costs significantly and increase competitiveness. Furthermore, the knowledge and understanding of the process will increase. However, the level of automation in industrial food processes is significantly lower compared to the chemical and pharmaceutical processes. This is partly due to the complexity of food processes. On the other hand, the lack of reliable sensor systems to determine important process parameters and variables contributed to this in the past. Sensors represent a fundamentalpart of all automation systems, although they only represent a part of the requirements for wider application of PAT in food industry. The areas of further development and recommendations enabling more extensive use of the PAT within this industry also include: • Further industrial case studies and wider dissemination of the positive impact of reliable sensor technology in raw material and product quality as well as process monitoring. • Operational and maintenance requirements of sensor technologies will remain a significant aspect of future sensor technology uptake in this industry. • Data management and analysis software will play a significant role in extending the PAT application within the food industry. Platform solutions, preferably supporting wireless data transfer, at competitive pricing levels are required. • Cost benefit analysis studies are particularly important given the business drivers of this industry. • The impact of PAT is likely to be more pronounced in the new processes, although it is important to continue to encourage the application of PAT approaches within established food processes to enhance the process economics and compliance with the standards ensuring safe food supply chains. • PAT can significantly contribute to the stringent traceability and documentation requirements, although issues of compatibility and data standardization will impact upon data management systems employed by the companies within the supply chain. The authors declare no financial or commercial conflict of interest.

Beside several studies about the occurrence of microplastic (MP) there is still a huge gap of knowledge regarding the dynamic processes of MP distribution and fate. Consequently, there is a need for reliable, fast, and robust analytical methods for MP monitoring. However, due to the physicochemical attributes of plastic, new analytical approaches fundamentally different from those for most other environmental contaminants are required. Promising strategies include spectroscopic and thermo-analytical methods. The two vibrational spectroscopic methods, Fourier-transform infrared spectroscopy (FT-IR) and Raman spectroscopy, have been implemented for MP detection. Especially in combination with particle finding software or a focal plane array (FPA) detector, they enable reliable determination of MP particle numbers in environmental samples. In recent years, different thermo-analytical techniques, such as pyrolysis (Py), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC) have been adapted for MP detection. All thermo-analytical methods are based upon measurement of physical or chemical changes of the polymer under thermal treatment. While DSC measures differences in heat flux caused by phase transitions of the polymer, TGA-MS is based upon detection of specific thermal degradation products. By means of a gas chromatographic separation step, an enhanced detection of the marker compounds is possible, enabling a more sensitive MP detection even in complex matrices. The extent of analytical information obtained as well as the complexity and effort of the methods increase by TGA-DSC < TGA-MS < Py-GC-MS/TED-GC-MS. The results are comparable to those of spectroscopic methods (FT-IR, Raman), but both techniques have different benefits and limitations. While thermo-analytical methods require minor sample pretreatment and reveal mass concentrations, spectroscopic methods are non-destructive and yield particle numbers and size distribution by imaging techniques. Whichever is the most suitable method depends on the scientific question and what kind of information is required.

In recent years, edible flowers have gained increasing attention as unconventional foods, primarily due to their richness in bioactive compounds. Within this context, Clitoria ternatea L. (Fabaceae), commonly known as butterfly pea, stands out not only for its remarkable biological properties but also for its intense blue pigmentation. This review aims to provide a comprehensive overview of the plant’s potential in the food industry, highlighting its bioactive compounds, technological applications, and associated health benefits. Recent studies have demonstrated its antioxidant, antidiabetic, anti-obesity, hepatoprotective, and anticancer activities, as well as its use as a natural colorant, functional ingredient, active packaging component, and in nutraceutical and cosmetic formulations. Despite these promising findings, most available evidence comes from preclinical studies, with limited clinical validation to date. Therefore, further human studies are needed to confirm the efficacy and safety of the reported beneficial effects. Altogether, C. ternatea represents a promising natural resource for developing functional foods that meet the growing clean-label demand, fostering the incorporation of sustainable and natural ingredients.

EDITORIAL article Front. Nutr., 16 February 2023Sec. Food Chemistry Volume 10 - 2023 | https://doi.org/10.3389/fnut.2023.1148051

Raman and NIR spectroscopy: A discussion of calibration robustness for food quality measurements through two case studies.

The need for accurate and reliable methods for food analysis on molecular level has been steadily increased during past decades. This trend is connected with the recent food scandals caused by food adulteration. Raman spectroscopy has very important role in identification of food fraud and food adulteration. Through this specific technique, the food quality control and authentication of food products can be easily performed. Adulteration, contamination and origin of food can be investigated through new field of food science-food forensics. Raman spectroscopy is one of the most valuable spectroscopic techniques used in different research fields. It has gained popularity due to it’s advantages over other analytical techniques. It is used in chemistry to study vibration, rotational, and other low-frequency modes of the system. This technique allows obtaining a chemical information from samples in nondestructive manner. It is useful for both solid and liquid samples. The main advantage of the Raman spectroscopy is that samples doesn’t require preparation. Another advantage is that water does not interfere in analysis. Raman spectra is captured within few seconds from sample, and after that analysed. In this review, relationship of food forensics with Raman spectroscopy is briefly explained. Raman spectroscopic techniques such as Fourier transform Raman spectroscopy, Surface-enhanced Raman spectroscopy and Visible—micro Raman spectroscopy are briefly introduced.