Critical assessment of formulation, processing and storage conditions on the quality of alveolar baked products determined by different analytical techniques: A review

The determination of the quality and authenticity of olive oil becomes more and more required by producers, consumers, and authorities to thwarter falsification. Several analytical techniques including chemical, sensory, chromatography, and so on, are used for the determination of the quality and authenticity of olive oil. Although these methods are considered as the reference ones, they are cumbersome, time-consuming and destructive. Therefore, rapid analytical techniques such as fluorescence, ultraviolet-visible, near infrared, and mid infrared spectroscopies, electronic sensing, among others, are more and more used for the determination of the quality and authenticity of olive oils. This review will identify current gaps related to different analytical techniques in olive oil authentication and discuss the drawbacks of existing analytical methods concerning olive oil authenticity from 2010 up to now.

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.

Design of experiments and regression modelling in food flavour and sensory analysis: A review

The effects of partial replacement of fish meal by vegetable protein sources in the diet of rainbow trout ( Onchorynchus mykiss) on post mortem spoilage of fillets

The logistic technologies for effective and efficient ‘order processing operations’ in the areas of tracking, shipping, replenishment, dispatching and holding of inventory are deficient in the Nigerian construction industry, when compared to manufacturing and retailing sectors. This is confirmed to have a significant effect on the performance of the construction sector. This article assessed how order processing technology utilised by manufacturing and retail industries could improve the order processing logistics operations of the construction industry. Lagos State and the F.C.T. Abuja, Nigeria, were the selected geographical study areas, from which five manufacturing companies, five retailing companies and five construction projects were purposively selected. Mixed methods research strategy was used. The research instruments included an observation guide (quantitative) and semi-structured interviews (qualitative). The collected quantitative data was analysed, using descriptive analytical tools: frequencies and percentiles. The qualitative data was analysed, using the thematic method. The result revealed that 80% and 100% of the manufacturing and retailing industries, respectively, observed, adopted barcoding technology for order processing purposes. Only 40% of the observed construction project adopted barcoding technology for order processing in the following: 2.4% for receiving process; 0.9% for put-away process; 0.9% for shipping process (stock control); 1.2% for dispatching process; 0.6% for replenishment process, and 1.2% for tracking inventory (stock tracking). In addition, 100% and 80% of the manufacturing and retailing industries, respectively, observed, adopted Radio Frequency Identification (RFID) technology for order processing purposes. Only 40% of the observed construction projects adopted RFID technology for order processing. It was also revealed that utilisation of the order processing technology could have the following benefits: managerial control in the construction industry; shorter processing time; easy way of tracking materials on site, and increased speed of work in the construction industries. The research concludes that effective utilisation of order processing technology in the logistics system could lead to full efficiency gains in the order processing aspect of the construction industry. It is recommended that the Federal Government of Nigeria should mandate all major construction project stakeholders to attend workshops on the use of recent technologies in the management of construction operations.

Eco-innovative possibilities for improving the quality of thawed cod fillets using high-power ultrasound

Increasing concern over atmospheric environmental problems has necessitated the design and development of new analytical techniques in order to introduce alternatives to the presently employed methods. The use of solid sorbents for collection of pollutants in air has gained general acceptance, and criteria for this type of system have often been presented. In general practice, solid sorbents are subjected to a desorption process in order to prepare an analyte solution prior to an analytical detection procedure of choice. Therefore, in general, the solid sorbents employed are designed to provide physical and chemical characteristics for efficient takeup of analyte and yet allow effective desorption procedures. This results in a high overall recovery value necessary for required accuracy. Collection of atmospheric H/sub 2/S on a Cd(II)-exchanged zeolite as a solid sorbent and application of several analytical techniques as diverse as X-ray fluorescence spectrometry, combustion analysis by nondispersive infrared (IR) measurement, diffuse reflectance Fourier transform infrared (FTIR) spectrometry, visible spectrometry, and photoacoustic spectrometry on both intact solid sorbent and its leached solution after conversion to methylene blue have been studied. The present paper reports the initial data on a novel sampler-sensor that uses a filter paper pretreated system as a solid sorbent samplermore » having an air channel in the shape of a planar spiral which gives a direct visual readout of low levels of H/sub 2/S.« less

Innovative blends with probiotic potential: Processing optimization, bioactive compounds and sensory evaluation of yellow mombin (Spondias mombin) and Talinum triangulare beverages

The present study detects the volatiles of egg white antioxidant peptides (EWAPs) with molecular weight range from 1 to 3 kDa and identifies the key volatiles responsible for the aroma changes under different storage conditions using HS-SPME-GC-MS and sensory evaluation. In comparison, the original samples and samples stored at 4 °C and 50% relative humidity (RH), 4 °C and 75% RH, 25 °C and 50% RH, 25 °C and 75% RH, presented 24, 27, 27, 28 and 30 major volatiles, respectively. The cluster analysis and principal component analysis (PCA) both showed that storage environment had a significant effect on the aroma changes. The sensory evaluation demonstrated that EWAPs stored at the same temperature had similar aroma profiles and the samples stored at a higher RH 75% had much stronger aroma intensity, because high temperature and RH may be more suitable to promote some chemical reactions. In Addition, the sensory evaluation of EWAPs samples and the verification experiment about contributions of volatiles, temperature and RH to the changed aroma were conducted, the results further revealed that 3-ethyl-2,5-dimethyl-pyrazine and benzothiazole may be the key volatiles responsible for aroma changes. The results attained in this study may help to explore the methods to prevent or retard the deterioration, and it is also expected to contribute to further research on the stabilization and productization of EWAPs as nutritional and functional food.

Background: walnut production and consumption has shown a steady rise in both amount and value in recent years. According to the seasonal production of walnuts, the storage condition plays a great role in its qu al it y. Methods: In this cross-sectional Study, effects of storage temperature and removing hard peels of walnut were studied on the shelf life of walnut over 6 months. The aflatoxin levels, lipid oxidation, antioxidant activity, and sensory evaluation were measured every 16 days (d). Results: The aflatoxin reduction was statistically significant in all stored walnut samples kept in the fridge, freezer, and their hard shell at room temperature after 151 days. The highest lipid oxidation and the lowest antioxidant activity were observed at the 6th month in walnuts preserved at room temperature. Through the sensory evaluation and chemical tests, walnuts preserved at fridge had the highest acceptance among panelist and least chemical changes after 6 months. Conclusion: the best storage condition for a long time is keeping peeled walnuts in the fridge.

Camellia oil authentication: A comparative analysis and recent analytical techniques developed for its assessment. A review

Redfish (Sebastes marinus and S. mentella) were caught by an Icelandic trawler, stored at about 0°C in boxes in the hold and landed in a German fishing harbour. Boxed redfish, differing in storage time on board, were subsequently stored in melting ice in the chill store of the laboratory at a temperature of +4°C until the borderline of saleability was reached. the quality loss of the ice‐stored redfish was monitored by a number of chemical, physical and microbiological parameters including volatile base nitrogen (TVB‐N), trimethylamine (TMA), trimethylamine oxide (TMAO), creatine, ethanol, Fishtester readings and number of cfu. AH parameters were correlated with sensory analysis and time in ice.The rate of deterioration of iced redfish depended on the conditions of storage. Sensory analysis was the most accurate indicator of the limit of saleability of redfish. Iced redfish, stored mainly in a chill store (4–5°C) onshore, had a shelf‐life of 16 to 19 days from catching. Fish stored at 0.5°C in the hold of the fishing vessel had a shelf‐life of 22 days: These results reflect the different storage temperatures and the effects of handling, transport and storage damage on the quality of the fish. the Fishtester proved to be very useful for the determination of deterioration. Measuring ethanol, TVB‐N and TMA gave no information about quality changes during the first 12 days of storage.

Order processing system is the beginning and core part of distribution center operations, and efficient order processing operations can not only improve customer satisfaction but also reduce costs. Therefore, the trade-off analysis between order processing difficulty and quick response time, improving the handling capacity and efficiency while reducing order processing costs are regarded as two big challenges for e-commercial enterprise. Based on queuing model as well as some data collected from Jingdong, a Chinese E-commerce giant, this paper constructed a 3D simulation model by using Flexsim, aiming at solving the bottleneck of the whole system of E-commerce order processing. According to the simulation, the author gives two order processing optimization solution, service stations optimization and queuing optimization to solve the two challenges.

In the field of joining technologies, known and established methods are combined thus inventing novel processes in order to reduce production time and also to create new application possibilities. Besides the simple coupling of laser beam and gas-metal arc, other hybrid methods such as the HyDRA method (Hybrid Double Rapid Arc) and the LUPuS method (Laser Submerged Arc Welding) have been developed.For the HyDRA method, the laser beam is coupled with two arcs thus allowing diverse inclination positions of the GMA torch to the laser beam. This method extends and optimizes the process limits of the conventional hybrid method with regard to the gap bridging ability, the welding speed and the energy input. The first industrially applicable weld heads for this special hybrid method have, meanwhile, become available. It is, therefore, assumed that industrial applications will soon be established.The idea of the LUPuS method originates from the knowledge that, with increasing penetration depth, the laser beam process and also the laser beam GMA hybrid process have a tendency to pore formation in the lower weld regions. The main reasons are the weld geometry of the laser beam weld with high aspect ratio between weld depth and weld width and the short time until solidification occurs. The coupling with the energy-efficient submerged-arc process improves the degassing out of the lower weld region and reduces the tendency to pore formation. The high deposition rate of the SA process in combination with the laser beam process offers, providing the appropriate choice of weld preparation, the possibility of welding plates with a thickness larger than 20° mm in a single pass, and also of welding thicker plates with the double-sided single pass technique.In the field of joining technologies, known and established methods are combined thus inventing novel processes in order to reduce production time and also to create new application possibilities. Besides the simple coupling of laser beam and gas-metal arc, other hybrid methods such as the HyDRA method (Hybrid Double Rapid Arc) and the LUPuS method (Laser Submerged Arc Welding) have been developed.For the HyDRA method, the laser beam is coupled with two arcs thus allowing diverse inclination positions of the GMA torch to the laser beam. This method extends and optimizes the process limits of the conventional hybrid method with regard to the gap bridging ability, the welding speed and the energy input. The first industrially applicable weld heads for this special hybrid method have, meanwhile, become available. It is, therefore, assumed that industrial applications will soon be established.The idea of the LUPuS method originates from the knowledge that, with increasing penetration depth, the laser beam pro...

Along with flavor, texture is one of the most important attributes of fresh-cut produce, which plays a critical role in consumer acceptance, influencing perceived freshness, quality, and overall eating experience. Salads, specifically green salads, usually contain leafy greens and other fresh-cut fruit vegetables such as cucumbers and tomatoes. Each of these components has its own unique characteristics, together giving the salad a wide range of textures and consumer experiences. Texture can be measured by both instrumental analysis and sensory evaluation techniques. Instrumental analysis consists of destructive and non-destructive methods, whereas sensory evaluation consists of descriptive and consumer studies. However, a comprehensive understanding and correlation of instrumental analysis and sensory evaluation of texture in salad-related fresh-cut fruits and vegetables is lacking in the literature. This review aims to address this gap by providing an in-depth understanding of the techniques used to quantify texture-related parameters and establishing relationships between the two techniques in fresh-cut salad products. The two different modes of analysis, along with the vastly different texture-related characteristics of fresh-cut salad produce, make it challenging to correlate instrumental analysis with sensory evaluation results. Furthermore, the integration of advanced technologies, including hyperspectral imaging and artificial intelligence-driven texture analysis, is emerging as a promising approach to enhance texture characterization and quality control. In addition to providing a comprehensive approach to enhance quality assessment methods, this review highlights the importance of predictability models powered by artificial intelligence and machine learning, enabling correlating instrumental analysis and sensory evaluation.