LC-MS based metabolic fingerprinting of apricot pistils after self-compatible and self-incompatible pollinations.

KEY MESSAGE: LC-MS based metabolomics approach revealed that putative metabolites other than flavonoids may significantly contribute to the sexual compatibility reactions in Prunus armeniaca. Possible mechanisms on related microtubule-stabilizing effects are provided. Identification of metabolites playing crucial roles in sexual incompatibility reactions in apricot (Prunus armeniaca L.) was the aim of the study. Metabolic fingerprints of self-compatible and self-incompatible apricot pistils were created using liquid chromatography coupled to time-of-flight mass spectrometry followed by untargeted compound search. Multivariate statistical analysis revealed 15 significant differential compounds among the total of 4006 and 1005 aligned metabolites in positive and negative ion modes, respectively. Total explained variance of 89.55% in principal component analysis (PCA) indicated high quality of differential expression analysis. The statistical analysis showed significant differences between genotypes and pollination time as well, which demonstrated high performance of the metabolic fingerprinting and revealed the presence of metabolites with significant influence on the self-incompatibility reactions. Finally, polyketide-based macrolides similar to peloruside A and a hydroxy sphingosine derivative are suggested to be significant differential metabolites in the experiment. These results indicate a strategy of pollen tubes to protect microtubules and avoid growth arrest involved in sexual incompatibility reactions of apricot.

Rapid evaluation technique to differentiate mushroom disease-related moulds by detecting microbial volatile organic compounds using HS-SPME-GC-MS.

Headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was used to analyse microbial volatile organic compounds (MVOCs) of mushroom disease-related microorganisms. Mycogone perniciosa, Lecanicillum fungicola var. fungicola, and Trichoderma aggressivum f. europaeum species, which are typically harmful in mushroom cultivation, were examined, and Agaricus bisporus (bisporic button mushroom) was also examined as a control. For internal standard, a mixture of alkanes was used; these were introduced as the memory effect of primed septa in the vial seal. Several different marker compounds were found in each sample, which enabled us to distinguish the different moulds and the mushroom mycelium from each other. Monitoring of marker compounds enabled us to investigate the behaviour of moulds. The records of the temporal pattern changes were used to produce partial least squares regression (PLS-R) models that enabled determination of the exact time of contamination (the infection time of the media). Using these evaluation techniques, the presence of mushroom disease-related fungi can be easily detected and monitored via their emitted MVOCs.

Applying parallel factor analysis and Tucker-3 methods on sensory and instrumental data to establish preference maps: case study on sweet corn varieties.

BACKGROUND: Traditional internal and external preference mapping methods are based on principal component analysis (PCA). However, parallel factor analysis (PARAFAC) and Tucker-3 methods could be a better choice. To evaluate the methods, preference maps of sweet corn varieties will be introduced. RESULTS: A preference map of eight sweet corn varieties was established using PARAFAC and Tucker-3 methods. Instrumental data were also integrated into the maps. The triplot created by the PARAFAC model explains better how odour is separated from texture or appearance, and how some varieties are separated from others. CONCLUSION: Internal and external preference maps were created using parallel factor analysis (PARAFAC) and Tucker-3 models employing both sensory (trained panel and consumers) and instrumental parameters simultaneously. Triplots of the applied three-way models have a competitive advantage compared to the traditional biplots of the PCA-based external preference maps. The solution of PARAFAC and Tucker-3 is very similar regarding the interpretation of the first and third factors. The main difference is due to the second factor as it differentiated the attributes better. Consumers who prefer 'super sweet' varieties (they place great emphasis especially on taste) are much younger and have significantly higher incomes, and buy sweet corn products rarely (once a month). Consumers who consume sweet corn products mainly because of their texture and appearance are significantly older and include a higher ratio of men.

Assessment of a virtual sensory laboratory for consumer sensory evaluations.

As technology advances in the field of food sciences, the sensory experience of food consumption remains complex and influenced by various factors. Traditional consumer testing, often conducted in isolated booth environments, presents challenges in terms of construct validity and user engagement for perception formation. The growing accessibility and sophistication of virtual reality (VR) technology offer a promising avenue for research. This study focuses on the assessment of a virtual sensory laboratory, seamlessly integrating traditional sensory practices into the virtual realm to explore disparities in consumer responses, especially in sensory analysis. The virtual laboratory, designed for compatibility with VR gear, closely resembles a sensory booth. The virtual environment enables the researchers to change the visual clues of the products being tested as well as the surroundings (e.g., colors, furniture, or even the environment). Additionally, the level of immersion can be enhanced by playing any type of music, if needed. One crucial question is to assess the opinions of the participants, if they feel comfortable in the created environment. Specific participant numbers are omitted, and the study engages participants. The success of this initiative could signify a substantial advance in analysis and cost savings, adding a layer of significance to the study's potential impact on optimizing research practices. The study lays the groundwork for optimal VR practices and anticipates further exploration with immersive elements to deepen our understanding of how virtual reality influences consumer behaviour in food selection compared to traditional sensory methods.

Immersive sensory evaluation: Practical use of virtual reality sensory booth.

Sensory booths enhanced with VR technology have displayed promising potential for improving sensory evaluation, perception research, and educational experiences. However, there remains an insufficient of data on VR's utilization in sensory science. In our research, we designed a virtual sensory booth (SB) utilizing Virtual Reality (VR) to complement sensory analysis and foster applications in the field of sensory science. The experiment involved the utilization of diverse sensory methods and product samples for examination within the virtual SB, which was compared to the traditional SB. A total of forty-three participants took part in the study to scrutinize the implications of the virtual SB. The results of a post-VR questionnaire demonstrated the participants' positive reception of the virtual SB. The study's findings suggest that the virtual SB could serve as a valuable resource for sensory scientists and individuals keen on exploring the emerging opportunities offered by VR. Notably, the virtual SB has proven to have potential applications, particularly within the food industry, with a special focus on sensory science. •Virtualized SB incorporating VR technology is a promising sensory evaluation and perception studies approach.•Virtual SB intends to use various sensory methods in VR applications for sensory analysis.•The creation of new VR-based technological solutions for sensory analysis can serve as a supplement to traditional sensory analysis.

Personalizing Communication of Clinicians with Chronically Ill Elders in Digital Encounters-A Patient-Centered View.

BACKGROUND: Chronically ill elderly patients are concerned about losing the personal connection with clinicians in digital encounters and clinicians are concerned about missing nonverbal cues that are important for the diagnosis, thus jeopardizing quality of care. AIMS: This study validated the expectations and preferences of chronically ill elderly patients regarding specific communication messages for communication with clinicians in telemedicine. METHODS: The sample comprised 600 elderly chronically ill patients who use telehealth. We used a conjoint-based experimental design to test numerous messages. The outcome variable is elder patient expectations from communication with clinicians in telemedicine. The independent variables were known categories of patient-clinician communication. Respondents rated each of the 24 vignettes of messages. RESULTS: Mathematical clustering yielded three mindsets, with statistically significant differences among them. Members of mindset 1 were most concerned with non-verbal communication, members of mindset 2 prefer communication that enhances the internal locus of control, and members of mindset 3 have an external locus of control and strongly oppose any dialogue about their expectations from communication. CONCLUSIONS: The use of the predictive algorithm that we developed enables clinicians to identify the belonging of each chronically ill elderly patient in the clinic to a sample mindset, and to accordingly personalize the communication in the digital encounters while structuring the encounter with greater specificity, therefore enhancing patient-centered care.

Self-Assessed Experience of Emotional Involvement in Sensory Analysis Performed in Virtual Reality.

Virtual reality (VR) technology has gained significant attention in various fields, including education for health professionals, sensory science, psychology, and consumer research. The first aim of the paper is to explore the self-assessed experience of emotional involvement in sensory analysis performed in VR. The Positive and Negative Affect Schedule (PANAS) is a widely used self-report measure that assesses positive and negative affective states. VR sensory analysis involves the use of immersive, interactive, and multi-sensory environments to evaluate sensory perception and emotional responses. By synthesizing relevant literature, this paper provides insights into the impact of VR on affective states, the effectiveness of VR in eliciting emotions, and the potential applications of the PANAS in VR sensory analysis. Furthermore, the second aim of the paper is to uncover the effect of VR sensory evaluation on the participant's emotional states, as it has a significant effect on their evaluations. The results suggest an increase in the sum of positive effects and a decrease in the negative ones. Although these results are promising, the relationship between the PANAS and VR sensory analysis is still underexplored, with limited research investigating the specific effects of VR on affective states measured using the PANAS. Further research is needed to better understand the potential of the PANAS in assessing emotional responses in VR environments and its implications for sensory analysis.

Enhancing consumer sensory science approach through augmented virtuality.

Augmented Virtuality (AV) is a concept that merges components of Augmented Reality (AR) and Virtual Reality (VR), incorporating real elements into a virtual environment. This review analyses the influence of AV technology on sensory science and consumer behaviour, with the potential to improve product evaluation through sensory analysis. The objective is to develop immersive sensory environments that closely resemble real-world scenarios, offering accurate insights into consumer perceptions and preferences. Participants will be able to observe genuine food products within the virtual environment. Through the utilization of a multidisciplinary approach, the analysis explores the point at which technology and human senses intersect, revealing new and unique understandings of decision-making processes. This enhances comprehension of consumer choices and behaviour in virtual environments, providing practical uses for industries navigating the ever-changing nature of augmented virtuality. This review demonstrates that the integration of AV elements in sensory science can have a substantial influence.

Unveiling aromas: Virtual reality and scent identification for sensory analysis.

Sensory analysis is crucial for optimizing experiences in various fields, including food, cosmetics, and product design. Traditional methods can be inefficient and imprecise. This study introduces a novel approach by blending Virtual Reality (VR) technology with scent identification techniques. The aim is to investigate whether the visual representation of food products affects scent perception. Limited research has explored the use of VR in scent identification, which is especially relevant when altering the food environment setting. A virtual sensory laboratory was developed to mimic MATE's sensory booth. Sixty participants, all MATE students, were involved in this study. This method offers a potential means to streamline scent identification and reduce human bias in sensory analysis. In summary, the combination of VR technology and scent identification presents a fresh methodological approach to sensory analysis, where both scent and exposure are influenced by the environment or imagery. This concept delves into cross-modal correspondences and the role of sensory cues in shaping our perception of food odours within the VR setting.

Exploring pectin from ripe and unripe Banana Peel: A novel functional fat replacers in muffins.

The study addresses global fruit waste concerns in the food industry by extracting pectin from both ripe and unripe banana peels at varying pH levels and time intervals using hydrochloric acid. The best results were observed for unripe banana peel pectin at pH 1.5 and 250 min exhibiting a yield of 16.46% and favorable characteristics. In muffin development, seven treatments (M0, M1, M2, M3, M4, M5 and M6) are prepared and analyzed for morphology, nutritional content, and sensory parameters. The M4 treatment, utilizing pectin from unripe banana peel at pH 1.5 and 250 min, displays superior qualities with reduced peroxide value, free fatty acids, percent moisture loss, and hardness. Sensory evaluations indicate high acceptability due to lower fat content. In conclusion, the extraction of pectin from unripe banana peels proves promising as a fat replacer in bakery items, maintaining muffin quality while addressing fruit waste challenges in the food industry.

Recommendations for validating hierarchical clustering in consumer sensory projects.

Choosing the proper hierarchical clustering algorithm and number of clusters is always a key question in consumer sensory projects. In many cases, researchers do not publish any reason why it was chosen a given distance measure and linkage rule along with cluster numbers. The reason behind this could be that different cluster validation and comparison techniques give contradictory results in most cases. A complex evaluation to define the proper clustering might be time-consuming and tedious. The paper introduces the clustering of three sensory data sets using different distance metrics and linkage rules for different numbers of clusters. The results of the validation methods deviate, suggesting that clustering depends heavily on the data set in question. Although Euclidean distance, Ward's method seems a safe choice, testing, and validation of different clustering combinations is strongly suggested.

How do ethnically congruent music and meal drive food choices?

Playing ethnic music in restaurants increases consumer experience. Studies show, furthermore, that ethnic congruence of music and food affects food selection but not the liking of customers. An eye-tracking study was completed with 104 participants to uncover if there is an effect of ethnic music on selecting ethnic foods. German, Hungarian, Italian, and Spanish ethnic music was played while participants choose congruent starters, main dishes, and desserts. Results show that visual attention decreased when any background music was played. However, when played, the highest visual attention was recorded during Spanish music. Similarly, the most visual attention was recorded on Spanish dishes. Food choice frequencies showed no differences among the four nations. However, after aggregating German-Hungarian and Italian-Spanish music and dishes, it turned out that participants chose congruent music and food. Choice predictions were also completed on data with and without ethnic music. The performance of prediction models significantly increased when music was played. These findings highlight a clear link between music and food choices, and that music helped participants complete their choices and decide faster.

Microencapsulation and Application of Probiotic Bacteria Lactiplantibacillus plantarum 299v Strain.

Microencapsulation is an up-and-coming technology for maintaining the viability of probiotics. However, the effect of core-to-wall ratios and ratios of polysaccharides on the protection of the Lactiplantibacillus plantarum 299v strain has not been deeply discussed. Lyophilization of the Lp. plantarum 299v strain was conducted, and different core-to-wall ratios and ratios of maltodextrin (MD) and resistant starch (RS) were applied. Results demonstrated that the content of MD and RS had an influence on the yield and bulk density in both core-to-wall ratios (1:1 and 1:1.5). In addition, samples coated with a core-to-wall ratio of 1:1.5 had significantly higher viability than those coated with a core-to-wall ratio of 1:1. Moreover, samples coated with core-to-wall ratios of 1:1 and MD:RS 1:1, as well as core-to-wall ratios of 1:1.5 and MD:RS 3:1, had the highest cell number after simulated gastric fluid and simulated intestinal fluid testing, respectively. Furthermore, the optimal formulation for the application of microencapsulated Lp. plantarum 299v in apple juice (serving as a functional beverage) is listed as follows: core-to-wall ratios of 1:1 and MD:RS 1:1, with the fortification method, and stored at 4 °C. After 11 weeks of storage, the cell count was 8.28 log (CFU/mL). This study provided a strategy for Lp. plantarum 299v to achieve high viability in long-term storage and provides an application in functional apple beverages.

Analysis of wheat flour-insect powder mixtures based on their near infrared spectra.

Insects are gaining more and more space in food and feed sectors, creating an intense scientific interest towards insects as food ingredients. Several papers deal with cereal-based products complemented by insect powder in the past few years. However, adulteration and quality control of such products present some hot topics for researchers, e.g., how can we justify the amounts and/or species of the insects used in the given products? Our paper aims to answer such questions by analysing seven edible insect powders of different species independently. The mixtures with wheat flour were analysed using near infrared spectroscopy and chemometric methods. Not only powders of different species were clearly differentiated, but also mixtures created by different amounts of wheat flour. Prediction of insect content showed 0.65% cross-validated error. The proposed methodology gives an excellent tool for quality control of insect-based cereal food products.

Personalized Communication with Patients at the Emergency Department-An Experimental Design Study.

Communication of clinicians at the emergency department is a barrier to patient satisfaction due to lack of human connection, lack of control over the situation, low health literacy, deficient information, poor support at a time of uncertainty all affecting perceived quality of care. This explorative study tests drivers of patient satisfaction with communication of clinicians at the emergency department. The sample comprises 112 Americans from the New York greater area, who visited an emergency department in the past year. A conjoint-based experimental design was performed testing six messages in six categories. The categories encompass acknowledged aspects of communication with health providers enabling to compare among them when exploring communication at the ED by patient preferences. Respondents rated messages by the extent to which it drives their satisfaction with communication of clinicians at the emergency department. Based on the similarity of patients' response patterns to each message, three significantly distinct mindsets of patient preferences regarding communication exchanges with clinicians at the emergency department emerged. Different conduct and communication messages drive the satisfaction of members of each mindset with the communication of clinicians at the emergency department. The strong performing messages for one mindset are irrelevant for members of other mindsets. Clinicians may identify the patient-belonging to a mindset and communicate using mindset-tailored messages. This novel strategy may enable clinicians to implement patient-centered communication, by mindset, promoting patient satisfaction and enabling clinicians to better cope with patients in the chaotic emergency department environment.

The Crick-Eatery: A Novel Approach to Evaluate Cricket (Acheta domesticus) Powder Replacement in Food Products through Product Eating Experience and Emotional Response.

This study was conducted to evaluate three different food products containing cricket powder for consumer acceptability, emotional response, satiety, and plate waste. US untrained consumers (n = 108), from the San Luis Obispo, CA area, were recruited to evaluate three food products (sausage, pasta, and brownies) as components in a three-course meal that either contain cricket powder (CP) or not (Control). The CP sausage was found to have lower liking scores than the Control for the attributes tested (p < 0.05). The CP pasta was found to be higher in overall liking than the Control (p < 0.05). The CP Brownies were rated highly across the attributes, except for texture and aftertaste (p < 0.05). Though the CP products were found to be as acceptable as the Controls, the use of cricket powder may have affected the texture and flavor profile of both the CP sausage and brownies. The participants selected more positive emotions terms for both the CP and Control products than negative emotions. Negative terms selected, such as worried, decreased once the products were consumed (p < 0.05). Plate waste and subjective satiety may also be indicators of consumer acceptability. Significant correlations were found between appearance liking and satiety as well as taste liking and plate waste for both the Control and CP products/dishes (p < 0.05). Based on this work, future acceptance of insect-based products may be encouraged by evaluating the products throughout an eating experience.

Multicriteria decision making for evergreen problems in food science by sum of ranking differences.

Finding optimal solutions usually requires multicriteria optimization. The sum of ranking differences (SRD) algorithm can efficiently solve such problems. Its principles and earlier applications will be discussed here, along with meta-analyses of papers published in various subfields of food science, such as analytics in food chemistry, food engineering, food technology, food microbiology, quality control, and sensory analysis. Carefully selected real case studies give an overview of the wide range of applications for multicriteria optimizations, using a free, easy-to-use and validated method. Results are presented and discussed in a way that helps scientists and practitioners, who are less familiar with multicriteria optimization, to integrate the method into their research projects. The utility of SRD, optionally coupled with other statistical methods such as ANOVA, is demonstrated on altogether twelve case studies, covering diverse method comparison and data evaluation scenarios from various subfields of food science.

Discrimination Ability of Assessors in Check-All-That-Apply Tests: Method and Product Development.

Binary similarity measures have been used in several research fields, but their application in sensory data analysis is limited as of yet. Since check-all-that-apply (CATA) data consist of binary answers from the participants, binary similarity measures seem to be a natural choice for their evaluation. This work aims to define the discrimination ability of CATA participants by calculating the consensus values of 44 binary similarity measures. The proposed methodology consists of three steps: (i) calculating the binary similarity values of the assessors, sample pair-wise; (ii) clustering participants into good and poor discriminators based on their binary similarity values; (iii) performing correspondence analysis on the CATA data of the two clusters. Results of three case studies are presented, highlighting that a simple clustering based on the computed binary similarity measures results in higher quality correspondence analysis with more significant attributes, as well as better sample discrimination (even according to overall liking).

How to predict choice using eye-movements data?

In recent decades, eye-movement detection technology has improved significantly, and eye-trackers are available not only as standalone research tools but also as computer peripherals. This rapid spread gives further opportunities to measure the eye-movements of participants. The current paper provides classification models for the prediction of food choice and selects the best one. Four choice sets were presented to 112 volunteered participants, each choice set consisting of four different choice tasks, resulting in altogether sixteen choice tasks. The choice sets followed the 2-, 4-, 6- and 8-alternative forced-choice paradigm. Tobii X2-60 eye-tracker and Tobii Studio software were used to capture and export gazing data, respectively. After variable filtering, thirteen classification models were elaborated and tested; moreover, eight performance parameters were computed. The models were compared based on the performance parameters using the sum of ranking differences algorithm. The algorithm ranks and groups the models by comparing the ranks of their performance metrics to a predefined gold standard. Techniques based on decision trees were superior in all cases, regardless of the choice tasks and food product categories. Among the classifiers, Quinlan's C4.5 and cost-sensitive decision trees proved to be the best-performing ones. Future studies should focus on the fine-tuning of these models as well as their applications with mobile eye-trackers.