Browsing by Author "Lahne, Jacob"

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    Analysis of volatile compounds, proximate composition, and fatty acids in Pacific bluefin tuna (Thunnus orientalis)
    James, Cierra Alisha (Virginia Tech, 2022-06-07)
    Pacific bluefin tuna (PBT; Thunnus orientalis) has grown significantly in popularity in recent years due to the globalization of Japanese cuisine. PBT is highly sought after for sushi and sashimi products due to its great quality and taste. Wild populations of this species have been affected by their increasing popularity, pushing innovators in the food industry to create meat alternative versions of PBT. The muscle composition of PBT varies, leading to different types (cuts) of meat in a way that is analogous to various cuts of beef. This study evaluated the differentiation amongst the 6 distinct cuts, including otoro, ventral akami, dorsal akami, ventral chu-toro, dorsal chu-toro, and wakaremi conducting volatile analysis, proximate analysis, and fatty acid analysis. The results from these analyses can then be used as a base standard for companies seeking to create alternatives versions of PBT. Samples analyzed in this study were cultured PBT species that were caught as juveniles and raised in captivity on a PBT farm in Mexico. Volatile analysis was conducted using a SPME GC/MS method. Overall, 41 aroma compounds were identified in PBT that met the identification criteria, including 9 aldehydes, 7 alcohols, 14 alkanes, 2 ketones, 4 alkenes, 3 aromatic compounds, and 2 miscellaneous compounds. Proximate analyses were conducted using standard methods. Significant differences (p <0.05) were found between each cut for the proximate analysis. The fatty acid analysis determined that there were twenty-two identifiable fatty acids found in the different cuts. The omega-3 fatty acids eicosapentaenoic acid (EPA, 20:5n-3) and docosahexaenoic acid (DHA, 22:6n-3) with DHA being present at a higher amount than EPA in each cut. Overall, there are similarities and differences among the different cuts of bluefin tuna that researchers would need to mimic to provide adequate nutritional and sensorial properties of PBT.
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    Analyzing larger sample sets with rapid methods: Incomplete-block designs with free-sorting and free-linking tasks
    Ac-Pangan, Marlon; Tejedor-Romero, Marino; Swatko, Kyra; Orden, David; Lahne, Jacob (Elsevier, 2024-04)
    As rapid, holistic methods for similarity and description—such as sorting and projective mapping—have grown in popularity, a limiting factor is the number of samples that can be presented to subjects: more than 25 food samples decreases the quality and stability of results. While incomplete-block designs could address this, their use has not been developed for these holistic methods. In this paper we present an empirical investigation into the use of incomplete-block designs with free sorting and the newer free linking. We compare these two methods because while their results are comparable, the cognitive tasks are different, and thus their suitability for incomplete-block designs may differ. We evaluated the effects of incomplete-block designs in two studies. In Study 1, 20 subjects evaluated 6/10 chocolate bars by free linking in an incomplete-block design, with each subject completing 2 blocks; results were compared to a complete-block evaluation of the 10 bars by free sorting and free linking. In Study 2, a total of 90 subjects evaluated 62 terms from a chocolate flavor-wheel in 3 conditions (between subjects): free sorting with complete blocks (N = 30, all 62 terms) and free sorting (N = 30) or free linking (N = 30) with 3 incomplete blocks of 16/62 terms. We introduce a novel method to evaluate stability for the incomplete-block designs that we call “pairwise simulation.” From Study 1, we find that pairwise simulation provides adequate stability estimates and that, with sufficient pairwise cooccurrences, free linking with incomplete blocks produces results that are comparable to free sorting or linking with complete blocks. From Study 2, we demonstrate that free linking with incomplete blocks can produce high quality results from a large sample set, maintaining the increased discrimination capacity that marks free linking in general, and that with incomplete blocks, free linking is likely to be more stable than free sorting. This research demonstrates that incomplete-block designs can be used with free linking, and also provides a new, effective method through pairwise simulation for evaluating stability with incomplete-block designs, which cannot be resampled using standard bootstrapping approaches.
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    Appeal of the Apple: Exploring consumer perceptions of hard cider in the Northeast and Mid-Atlantic United States
    Calvert, Martha D.; Neill, Clinton L.; Stewart, Amanda C.; Chang, Elizabeth A. B.; Whitehead, Susan R.; Lahne, Jacob (Taylor & Francis, 2023-10-23)
    Alcoholic or “hard” cider is experiencing a resurgence in popularity, particularly throughout the Northeast and Mid-Atlantic regions of the United States. Yet, many stakeholders struggle to understand how consumers define and distinguish hard cider from the sea of options in the saturated alcoholic beverage market. This study aimed to explore consumer preferences for hard cider using a phenomenological, qualitative approach. The research comprised 14 focus groups with regular cider consumers (99 participants) throughout three leading cider-producing states in the Northeast and Mid-Atlantic United States: Virginia, Vermont, and New York. All focus group sessions were subject to reflexive thematic analysis for themes broadly related to cider product preference and the cider-drinking experience. Results of the study suggest that cider preference is motivated largely by sensory quality in addition to various other factors including perceived health effects, regionality and proximity, the drinking occasion, and product information. Results also emphasize the importance of nostalgia in cider sensory experiences, as well as the role of social norms in consumer valuation of cider products. Overall, this research highlights diverse consumer preferences for cider and serves as a framework for using qualitative research methods to explore consumer preferences in the food and beverage industries.
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    Appeal of the Apple: Investigating Preference, Perception, and Communication Around Hard Cider in the Northeast and Mid-Atlantic United States
    Calvert, Martha D. (Virginia Tech, 2023-07-03)
    Alcoholic or "hard" cider, as it is known in the United States, is experiencing a resurgence in popularity worldwide, but most relevantly throughout the Northeast and Mid-Atlantic regions of the United States. Cider has a rich history of being America's drink of choice, beginning with the native apple trees of indigenous communities and the proliferation of apple growing in the original American colonies. Today, cider is becoming popular particularly in the Northeast and Mid-Atlantic where New York, Virginia, and Vermont are the 1st, 8th, 12th ranked states with the most cideries in America. In light of the American cider industry experiencing such a renaissance, leading industry stakeholders and various other scholars have drawn attention to the need for increased clarity regarding consumer and producer perceptions of cider quality, as well as a more comprehensive understanding of cider sensory quality. This dissertation utilizes qualitative research methods, including focus groups and interviews conducted in New York, Virginia, and Vermont, to explore consumer and producer preferences of cider and the cider-drinking experience. In addition, this research employed traditional sensory descriptive analysis (DA) to quantify sensory differences across cider products. Lastly, this research presents findings on the use of biterm topic modeling (BTM), an emergent method of text mining for small datasets, to explore topics of discussion in cider marketing materials for products in the American cider marketplace. This dissertation presents evidence of preferences, sensory perception, and discourse within a snapshot of the current American cider industry. Cider consumers and producers prioritize flavor when discussing cider quality, but also value how cider is made and where it comes from. Consumers, in particular, are nostalgic about the cider-drinking community and culture that is omnipresent in the Northeast. Secondly, the sensory quality of ciders can be discriminated across multiple variables, including region of origin, packaging, and style; suggesting that the sensory space of American cider products is diverse and nuanced. Lastly, when marketing cider products through website platforms, cider producers tend to emphasize topics related to sensory attributes, production elements, food-pairing, flavorings, and apple varieties. With a greater understanding of consumer and producer preferences of cider, cider sensory quality, and cider communication, industry actors and stakeholders may have a more actionable understanding of where the cider industry may be headed with continued growth. As well, this dissertation provides a framework for the use of qualitative and text mining tools to better understand facets of consumption and production, as well as marketing language in the food and beverage space.
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    Application of Automated Facial Expression Analysis and Facial Action Coding System to Assess Affective Response to Consumer Products
    Clark, Elizabeth A. (Virginia Tech, 2020-03-17)
    Sensory and consumer sciences seek to comprehend the influences of sensory perception on consumer behaviors such as product liking and purchase. The food industry assesses product liking through hedonic testing but often does not capture affectual response as it pertains to product-generated (PG) and product-associated (PA) emotions. This research sought to assess the application of PA and PG emotion methodology to better understand consumer experiences. A systematic review of the existing literature was performed that focused on the Facial Action Coding System (FACS) and its use to investigate consumer affect and characterize human emotional response to product-based stimuli, which revealed inconsistencies in how FACS is carried out as well as how emotional response is inferred from Action Unit (AU) activation. Automatic Facial Expression Analysis (AFEA), which automates FACS and translates the facial muscular positioning into the basic universal emotions, was then used in a two-part study. In the first study (n=50 participants), AFEA, a Check-All-That-Apply (CATA) emotions questionnaire, and a Single-Target Implicit Association Test (ST-IAT) were used to characterize the relationship between PA as well as PG emotions and consumer behavior (acceptability, purchase intent) towards milk in various types of packaging (k=6). The ST-IAT did not yield significant PA emotions for packaged milk (p>0.05), but correspondence analysis of CATA data produced PA emotion insights including term selection based on arousal and underlying approach/withdrawal motivation related to packaging pigmentation. Time series statistical analysis of AFEA data provided increased insights on significant emotion expression, but the lack of difference (p>0.05) between certain expressed emotions that maintain no related AUs, such as happy and disgust, indicates that AFEA software may not be identifying AUs and determining emotion-based inferences in agreement with FACS. In the second study, AFEA data from the sensory evaluation (n=48 participants) of light-exposed milk stimuli (k=4) stored in packaging with various light-blocking properties) underwent time series statistical analysis to determine if the sensory-engaging nature of control stimuli could impact time series statistical analysis of AFEA data. When compared against the limited sensory engaging (blank screen) control, contempt, happy, and angry were expressed more intensely (p<0.025) and with greater incidence for the light-exposed milk stimuli; neutral was expressed exclusively in the same manner for the blank screen. Comparatively, intense neutral expression (p<0.025) was brief, fragmented, and often accompanied by intense (albeit fleeting) expressions of happy, sad, or contempt for the sensory engaging control (water); emotions such as surprised, scared, and sad were expressed similarly for the light-exposed milk stimuli. As such, it was determined that care should be taken while comparing the control and experimental stimuli in time series analysis as facial activation of muscles/AUs related to sensory perception (e.g., chewing, smelling) can impact the resulting interpretation. Collectively, the use of PA and PG emotion methodology provided additional insights on consumer-product related behaviors. However, it is hard to conclude whether AFEA is yielding emotional interpretations based on true facial expression of emotion or facial actions related to sensory perception for consumer products such as foods and beverages.
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    Binge-Restrict-Repeat: The Governmentality of Eating Regimes
    Cutter, Linea Lee (Virginia Tech, 2023-05-15)
    This study employs Michel Foucault's conceptualization of governmentality, or dispersed rationalities that seek to calculate and maximize the health of the population, to study how eating regimes of truth influence how individuals relate to their bodies and each other. Importantly, the study of eating regimes elucidates how food rules are portrayed in the discourses, institutions, philosophical and moral propositions, administrative measures, and technologies (what Foucault refers to as societal apparatuses of power, or dispositifs) that address what and how to eat. In this dissertation, I specifically analyze dispositifs that promote certain foodstuffs as devotional objects that can be utilized as forms of pleasure and/or self-control. I conceptualize artificial sweeteners as ingestible stores of self-control and biopower, arguing that they provide a lens through which to view how mealtime rituals, temporalities of eating, and the intersubjective perceptions of the relationship between food consumption and the ideal healthy body have transformed in the face of discourses that emphasize the need to strip food of carbohydrate- and calorie-loaded consequences. The dissertation analyzes how contemporary dietary discourses in the United States encourage individuals to view freedom of food choice as a binary selection between binge and restrict eating practices. I argue that this notion of dietary balance is part of what I refer to as the neoliberal binge-restrict eating regime. I analyze the binge-restrict eating regime on three different yet supplementary registers: 1) that of neoliberal discourses of dietary balance, which are premised on logics and technologies of rigid, machine-like correction and anticipatory compensation through carefully planned periods of restriction and healthy eating followed by food binges, or periods where an individual indulges in seemingly unhealthy foodstuffs; 2) that of discourses that encourage the individual to consume endlessly but not allow signs of "excessive" consumption to develop in the body; 3) and that of edible instantiations of the binge-restrict eating regime, with a particular emphasis on artificial sweeteners. The dissertation concludes that the contemporary notion of dietary balance as "binge-restrict" is informed by a popular interpretation of food rules as rigid, algorithmic truths and contributes to a loss of embodied knowledge regarding how to eat well.
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    Can Cider Chemistry Predict Sensory Dryness? Benchmarking the Merlyn Dryness Scale
    Calvert, Martha D.; Cole, Elizabeth; Stewart, Amanda C.; Neill, Clinton L.; Lahne, Jacob (Taylor & Francis, 2022-09-23)
    The growing popularity of hard cider in the United States has been accompanied by an inconsistent understanding of the nature and importance of consumers’ perception of dryness and sweetness in the product. In 2018, the New York Cider Association proposed the Merlyn Dryness Scale as a tool to predict cider dryness using basic cider chemistry, but this approach has yet to be validated in sensory experiments. In the current study, panelists (N = 48) evaluated three different commercial ciders served at two different temperatures (2 °C and 22 °C) in three parts: by rating the dryness of the sample on a line scale equivalent to the range of the Merlyn Dryness Scale, by using a simple check-all-that-apply (CATA) tool that included dryness, and by rating their overall liking on a 9-point hedonic scale. The results indicated that the Merlyn Dryness Scale may not achieve its goal of predicting perceived dryness in cider, as consumers perceived cider samples to be more dry than was suggested using Merlyn Scale chemical procedures. Contrary to expectations, the serving temperature of the cider samples did not significantly impact perceived dryness rating but did influence overall liking. This study suggests that predicting sensory dryness from cider-chemistry parameters requires further study.
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    Comparing Extraction Methods in Sample Preparation for the Quantification of Cannabinoids in Industrial Hemp
    Sandbrook, Ann Marie (Virginia Tech, 2021-05-28)
    Industrial hemp is legally defined in the United States by the Agriculture Improvement Act of 2018 (2018 Farm Bill) as Cannabis containing <0.3% total tetrahydrocannabinol (THC). The 2018 Farm Bill does not, however, specify standard methods for sample preparation or quantification of cannabinoids (including THC) in Cannabis. Extraction efficiency of phytochemicals is well-known to depend on the solvent and extraction method used. In this project, we evaluated the effect of sample preparation extraction methods on the quantitative analysis of five cannabinoids found in industrial hemp with regulatory or commercial significance: cannabidiol (CBD), cannabidiolic acid (CBDA), delta-9-tetrahydrocannabinol (THC), tetrahydrocannabinolic acid (THCA), and cannabinol (CBN). Extraction methods evaluated include: QuEChERS, diethyl ether, ethanol, and methanol. Extracts obtained via these methods were subject to quantitative cannabinoid analysis by UPLC/PDA. Standard curves for quantification of each cannabinoid were constructed using authentic standards for quantification. The concentrations of each cannabinoid in the plant material determined via each of the extraction methods were compared using one-way ANOVA followed by Tukey's HSD (significant difference defined as p <0.05). All extraction methods evaluated returned different concentrations of total THC in the plant material. The QuEChERS extraction resulted in the highest calculated concentrations of THC, THCA and CBDA, reporting three to four times greater than obtained via other extractions evaluated. Classification of the starting plant material as hemp or marijuana depended on the extraction method used. These findings clearly and quantitatively demonstrate the need for standardization of extraction methods for hemp analysis and regulation.
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    Consumer Acceptance of Beer: An Automated Sentiment Analysis Approach
    Canty, Ellise Adia (Virginia Tech, 2022-07-13)
    Selecting the correct methodology to better understand how consumers perceive food products is a challenging task for the food industry and sensory researchers alike. Free comment tasks (FC) utilize the advantages of open-ended questions to generate intuitive comments from untrained consumers to help identify and describe sensory attributes of products. However, FC data is typically analyzed using text analysis done by hand and is very cumbersome to organize and interpret. There is a growing need and interest to add to the library of data analysis tools used to understand FC data and consumer acceptance studies. Sentiment analysis is an opinion mining tool commonly used in marketing and computer science that extracts the emotional valence of the author from an unstructured text in the form of a sentiment score. A few studies in sensory evaluation use lexicon-based sentiment analysis which has many drawbacks: it is time-consuming, requires a large amount of data and dictionaries need to be tailored for food. We used a deep learning sentiment analysis approach to analyze and predict consumer sentiment/acceptance. The research objectives of this study are 1) to explore quicker and automated methods of sentiment analysis to better understand and predict consumer acceptance, and 2) to examine the advantages and disadvantages of sentiment analysis as a data analysis tool in sensory evaluation. We avoided the pitfalls of creating a sentiment lexicon by using online beer reviews to train a word embedding model where all of the relevant words in the review are converted into vectors. We used the distance and similarity (clustering) of the vectors to determine taste/flavor attributes that correspond to negative and positive sentiment. Next, to validate and test our model we gathered FC data in a consumer acceptance study. Panelists (N=68) were presented with six beers, one at a time and were instructed to taste and smell before leaving comments. We performed sentiment analysis on the FC data, and we compared our deep learning sentiment analysis model with three other pre-existing sentiment analysis models: SentimentR, VADER, and Liu and Hu opinion lexicon. Our deep learning sentiment analysis model had the highest accuracy (69%) and precision rate (73%). Overall, our findings provide an early look into the advantages and disadvantages of sentiment analysis applied to FC data in sensory evaluation.
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    The Development of a Lexicon for Virginia Ciders through Descriptive Analysis
    Cole, Elizabeth Jane (Virginia Tech, 2022-06-08)
    Hard cider or "cider" is a fermented, alcoholic beverage made from the juice of apples. The cider industry has experienced recent growth within the United States and Virginia. Virginia is one of the largest producers of apples in the United States, and apples are considered a top commodity in the state. Currently, there is inconsistent terminology to describe Virginia cider, and cider producers are using descriptors that are usually associated with beer and wine. Thus, this study aims to identify the distinct sensory profiles of Virginia ciders and to identify drivers of consumer liking. Understanding sensory profiles and drivers of consumer liking for Virginia ciders will aid consumers in understanding what kind of cider styles they prefer and could help producers identify acceptable cider products. A descriptive analysis (DA) was completed to determine a well-defined sensory profile for Virginia hard ciders. The DA consisted of 24 ciders that producers considered to be representative of Virginia and their brands from 16 of the 32 known cider producers in Virginia. In the DA, 6 panelists defined reference standards for 48 descriptors consisting of 20 aromas, 3 tastes, 13 flavors, and 12 mouthfeel attributes. Through M/ANOVA, 22 descriptors were identified as significant, and 6 groups of ciders were identified using Hierarchical Cluster Analysis (HCA). Then, an exploratory consumer study using 8 representative ciders from the DA was conducted with 67 subjects. Subjects were first asked a series of demographic questions, then presented with samples in randomized, sequential, monadic fashion and reported overall liking, purchasing intent, and willingness to pay. Internal and external preference mapping was accomplished with Partial Least Squares Regression (PLS) and Clustering Around Latent Variables (CLV). Three distinct clusters were identified with distinct product and sensory preferences. Finally, basic chemical analyses of all samples were performed. The DA demonstrated that Virginia ciders have distinct sensory characteristics and fall into distinct sensory groups. The 3 consumer clusters found through CLV may represent cider drinkers' preferences in both Virginia and the United States. While no unusual cider chemistry was found, we were able to observe expected connections between chemistry and sensory profiles.
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    Development of standardized dry roasting procedures for Virginia type peanuts
    Khan, Jasim (Virginia Tech, 2021-10-08)
    Peanuts are grown around the world and in United States where most peanuts are consumed after roasting. Peanuts are roasted to a specified color on L*a*b* scale as it is correlated with quality and acceptability. Two batches of Virginia type peanuts were acquired, one normal and other a high oleic variety. A surface response model using the Box-Behnken design was developed for Behmor 2000AB and GeneCafe coffee roasters, for normal and high oleic peanuts respectively with sample size, roast time and power/temperature as dependent variables and L* as a response variable. The model for Behmor was not significant (p>0.05 and R2 =0.87) but with effect contribution of roast time while the GeneCafe model was significant (p<0.05 and R2=0.98) with multiple first and second order effect contributions from temperature and roast time. Each model was validated and Behmor was found to be more consistent and predictable compared to GeneCafe. Both varieties of peanuts were roasted on each roaster and tested for volatile analysis using SPME GC/MS with high variation observed within samples which may be caused by uneven roasting. The volatile results showed similar trends for seventeen compounds between normal and high oleic samples. The Behmor roaster was more effective at predictable roasting for 50 to 100 g sample and more validation is needed on GeneCafe to improve its model. The results can help with quality testing of new varieties of Virginia type peanuts quickly without relying on large sample size typically used in other lab scale studies.
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    The Effect of Health Information on the Acceptability of a Functional Beverage with Fresh Turmeric
    Grasso, Stephanie Marie (Virginia Tech, 2018-06-29)
    BACKGROUND: Turmeric is a root with curcumin and non-curcumin derivatives that serve as antioxidants, which reduce the risk of oxidative stress-induced chronic disease. The provision of health information has shown to increase the acceptability of functional foods that impart unfamiliar flavors. PURPOSE: The purpose of this study was to evaluate the acceptability and sensory qualities of a functional beverage with fresh turmeric, and the impact of information related to the beverage's health benefits on acceptability. This study also investigated personal and psychological factors associated with food acceptance. METHODS: Antioxidant capacity (ferrous equivalents) and polyphenolic content were evaluated in a fruit-based beverage containing 0g, 7g, 14g, and 22g of fresh turmeric. Sixty-one individuals were recruited to participate in a sensory evaluation of two fruit-based beverages with and without fresh turmeric. Thirty-one participants were given health information related to the beverage and 30 participants received no health information. The degree of liking was measured on a hedonic scale and sensory attributes were measured using a Just About Right (JAR) scale. Food choice motives and demographic characteristics were measured using a Food Choice Questionnaire and demographics questionnaire. RESULTS: The development of a functional beverage with 14 grams of turmeric was considered significantly more acceptable with the provision of health information and resulted in a significant increase in antioxidant capacity and polyphenolic content. There was a significant difference in acceptability scores of the functional beverage across antioxidant interest groups and health motivation groups.
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    Effects of Hydroxycinnamates and Exogenous Yeast Assimilable Nitrogen on Cider Aroma and Fermentation Performance
    Cairns, Paulette Anne (Virginia Tech, 2019-07-08)
    Heritage apple cultivars for cider-making are often distinguished by a high concentration of tannins (phenolic compounds), and/or acid. The phenolic content of some cider apples far exceeds that of white wine, however most cider fermentation practices are directly taken from white winemaking, not accounting for effects of high concentrations of phenolic compounds on yeast fermentation. The objective of this study was to determine the impact of ferulic acid, p-coumaric acid, and chlorogenic acid—at concentrations reported in apples—and their interactions with yeast assimilable nitrogen (YAN) on fermentation kinetics and cider aroma. Our hypothesis was that the phenolic compounds present in high-tannin cider apples would negatively impact fermentation kinetics, but not alter the aroma, and that added YAN would reduce these effects. Ferulic acid negatively affected fermentation performance (p < 0.05), but p-coumaric acid and chlorogenic acid did not. p-Coumaric acid led to the greatest changes in cider aroma. Differences were also detected for different concentrations of ferulic acid. Chlorogenic acid did not affect aroma. Yeast strain influenced fermentation performance and cider aroma. Finally, addition of exogenous YAN improved fermentation performance for the low concentration ferulic acid condition, but not for the high concentration. Adding YAN also changed cider aroma in the presence of p-coumaric acid.
  • Enhanced Apple Cider Fermentation by Selective Light Exposure
    Wright, Melissa; Williams, Robert; Hurley, E. Kenneth; Eifert, Joseph D.; Lahne, Jacob (2019-04-26)
    Fermentation represents a large segment of post-harvest agricultural processing nationwide. Virginia is a leading state in the production of apples and has shown significant growth in the area of hard cider production. Consumer preference drives the hard cider market and new hard ciders are being introduced frequently. In an effort to enhance the quality of hard cider, this project sought to understand the effect of selected light (color and intensity) exposure during fermentation of apple cider on color and sensory characteristics of the resulting hard cider. Apple juice was inoculated with Saccharomyces cerevisiae and placed into a vertical glass fermentation vessel. Light of selected colors (red, yellow, green, blue, and ultraviolet) and intensities (low, medium and high) was applied to the apple juice during fermentation. Juices were allowed to ferment for 187 ± 3 h, followed by sensory and color analysis. Hard cider exposed to ultraviolet light during fermentation was most different from the dark control (fermented with no light exposure) and most preferred by sensory panelists on the basis of taste. Ultraviolet light-treated ciders were less yellow in color as compared to the dark control. Modifying the color and intensity of light may yield hard ciders with improved sensory characteristics and provide cider makers with processes to enhance quality of traditionally fermented products. This project was funded by a grant from the Virginia Agricultural Council.
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    An evaluation and shortening of the Cooking and Food Provisioning Action Scale (CAFPAS) using item response theory
    Karlsson, Simon; Harris, Kathryn L.; Melin, Jeanette; Lahne, Jacob; Wolfson, Julia A.; Collier, Elizabeth S. (Elsevier, 2023-05)
    The Cooking and Food Provisioning Action Scale (CAFPAS) is a 28-item validated tool for measuring food agency, a latent construct representing an individual's ability to make and achieve food-preparation and -pro-visioning goals. Here, key measurement parameters (targeting, threshold ordering, item fit, unidimensionality, differential item functioning, local dependency, and person reliability) of the CAFPAS are evaluated using a specific case of item response theory, Rasch analysis, on data from a development sample (N = 1853; 910 from Sweden; 943 from the US). Winsteps (v.5.1.7) is used for this analysis. The similarity of the Swedish version of the CAFPAS to the original is also assessed. Based on an iterative assessment of the measurement properties with different combinations of items in the development sample, ways to shorten the CAFPAS without jeopardizing construct validity or person reliability are examined. After removing items that do not fit the Rasch model, or that appear redundant in relation to other items, an 11-item version (CAFPAS-short) is suggested and tested using further Rasch analysis on both the development sample and an additional US-based validation sample (N = 1457). Scores of cooking confidence and attitudes are then modelled with measures from the CAFPAS and CAFPAS-short using frequentist and Bayesian analysis. Results suggest that the CAFPAS-short performs similarly to the full-length version, and potential future improvements to the CAFPAS are discussed. This study represents a successful application of item response theory to investigate and shorten a psychometric scale, reducing cognitive load on participants in studies using the CAFPAS whilst minimizing loss of data reliability.
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    Exploring cider website descriptions using a novel text mining approach
    Calvert, Martha D.; Cole, Elizabeth; Neill, Clinton L.; Stewart, Amanda C.; Whitehead, Susan R.; Lahne, Jacob (Wiley, 2023-05)
    Rapid methods of text analysis are increasingly important tools for efficiently extracting and understanding communication within the food and beverage space. This study aimed to use frequency-based text mining and biterm topic modeling (BTM) as tools for analyzing how cider products are communicated and marketed on cider-producer websites for products made in Virginia, Vermont, and New York. BTM has been previously used to explore topics in small corpora of text data, and frequency-based text mining is efficient for exploring patterns of text across different documents or filters. The present dataset comprised 1115 cider products and their website descriptions extracted from 124 total cider-producer websites during 2020 and 2021. Results of the text mining analyses suggest that cider website descriptions emphasize food-pairing, production, and sensory quality information. Altogether, this research presents the text mining approaches for exploring food and beverage communication. Practical applicationsThis research will be valuable to stakeholders in the United States' cider industry by providing relevant insight as to how cider marketing and sensory communication varies based on extrinsic product factors, such as geography and packaging. This research also demonstrates the efficiency and potential of text mining tools for exploring language and communication related to foods, beverages, and sensory quality. Further, this research provides a framework for extracting sensory-specific language from a large corpus of data, which may be adopted by other researchers wishing to apply rapid descriptive methods in the sensory, quality, and consumer research fields.
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    Exploring Perceptions and Categorization of Virginia Hard Ciders Through the Application of Sorting Tasks
    Kessinger, J.'Nai Britny (Virginia Tech, 2020-02-19)
    Hard cider is an alcoholic beverage made from fermented apple juice. Its popularity has grown rapidly since the early 2000s and is expected to grow to a billion-dollar industry by 2022. However, unlike beer and wine, there are few popular resources and little scholarly research on the sensory attributes of ciders and how consumers perceive them. Thus, the purpose of this study was to categorize and describe the sensory and visual product attributes of ciders made in Virginia, USA using a rapid sensory evaluation method with untrained panelists known as a free sorting task. Specifically, panelists (N=65) first evaluated, sorted into groups, and described ciders (K=18). Then panelists (N=63) sorted photo sheets of cider labels and packaging according to how they expected the products would taste and at what occasion they would be most inclined to drink each cider. The data were analyzed with DISTATIS to produce compromise similarity maps, with bootstrapped confidence intervals to identify significant differences between products. Classical text analysis was used to evaluate the sensory descriptions used by assessors during the sorting task and project terms onto the similarity map. Panelists identified and described distinct sensory styles and attributes among the ciders evaluated. Consistent patterns in what occasion panelists might consume a cider emerged, providing a first-look into how cider might be valued based on packaging and label.
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    Exploring the sensory characteristics of Virginia ciders through descriptive analysis and external preference mapping
    Cole, Elizabeth; Stewart, Amanda C.; Chang, Elizabeth A. B.; Lahne, Jacob (Taylor & Francis, 2022-09-23)
    The cider industry has experienced recent growth within the USA and Virginia in particular. However, the sensory characteristics and drivers of consumer acceptance of ciders are largely uncharacterized. Therefore, this work describes the sensory profiles of commercial Virginia ciders and links these to consumer acceptance. In study 1, a descriptive analysis (DA) of 24 representative ciders from 16 producers in Virginia was conducted: 6 panelists defined 48 descriptive terms for ciders. In study 2, a consumer acceptance study was conducted on 8 ciders from the DA with 67 subjects. For the DA study, 22 descriptors were found to be significant, and multivariate analyses identified 6 groups. In the consumer study, external preference mapping was conducted to identify 3 clusters of consumers with distinctive patterns of sensor preference. The largest cluster favored sweet ciders without off-flavors; a second, smaller cluster favored sweetness even in the presence of off-flavors; and the smallest cluster disliked sweetness in ciders and was intolerant of off-flavors. We describe these groups’ demographic and consumption profiles. All ciders’ basic chemistry was within previously reported ranges, and expected relationships between flavor and chemistry were observed. We were able to establish sensory profiles for Virginia ciders, and tentatively link sensory profiles and consumer acceptance. Overall, this work adds to a small-but-growing body of knowledge about ciders’ sensory properties. Producers can use the sensory profiles in comparison to other regions’ ciders to establish regional sensory profiles, and the consumer preference map to understand how to capitalize on their ciders’ distinct profiles.
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    The Facial Action Coding System for Characterization of Human Affective Response to Consumer Product-Based Stimuli: A Systematic Review
    Clark, Elizabeth A.; Kessinger, J'Nai; Duncan, Susan E.; Bell, Martha Ann; Lahne, Jacob; Gallagher, Daniel L.; O'Keefe, Sean F. (Frontiers, 2020-05-26)
    To characterize human emotions, researchers have increasingly utilized Automatic Facial Expression Analysis (AFEA), which automates the Facial Action Coding System (FACS) and translates the facial muscular positioning into the basic universal emotions. There is broad interest in the application of FACS for assessing consumer expressions as an indication of emotions to consumer product-stimuli. However, the translation of FACS to characterization of emotions is elusive in the literature. The aim of this systematic review is to give an overview of how FACS has been used to investigate human emotional behavior to consumer product-based stimuli. The search was limited to studies published in English after 1978, conducted on humans, using FACS or its action units to investigate affect, where emotional response is elicited by consumer product-based stimuli evoking at least one of the five senses. The search resulted in an initial total of 1,935 records, of which 55 studies were extracted and categorized based on the outcomes of interest including (i) method of FACS implementation; (ii) purpose of study; (iii) consumer product-based stimuli used; and (iv) measures of affect validation. Most studies implemented FACS manually (73%) to develop products and/or software (20%) and used consumer product-based stimuli that had known and/or defined capacity to evoke a particular affective response, such as films and/or movie clips (20%); minimal attention was paid to consumer products with low levels of emotional competence or with unknown affective impact. The vast majority of studies (53%) did not validate FACS-determined affect and, of the validation measures that were used, most tended to be discontinuous in nature and only captured affect as it holistically related to an experience. This review illuminated some inconsistencies in how FACS is carried out as well as how emotional response is inferred from facial muscle activation. This may prompt researchers to considermeasuring the total consumer experience by employing a variety of methodologies in addition to FACS and its emotion-based interpretation guide. Such strategies may better conceptualize consumers’ experience with products of low, unknown, and/or undefined capacity to evoke an affective response such as product prototypes, line extensions, etc.
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    Flavor language in expert reviews versus consumer preferences: An application to expensive American whiskeys
    Hamilton, Leah M.; Neill, Clinton L.; Lahne, Jacob (Elsevier, 2023-07)
    Treating natural language flavor descriptions as data that can explain or “predict” consumer or market responses to a product, a process called Natural Language Processing or Text Mining, is increasingly common in food research. Text data has high variation in vocabulary usage and which features writers attend to, necessitating large datasets which tend to be from unblinded tastings with limited types of supplemental data. In this study, a random forest model trained on 4300 full-text whiskey reviews identified terms commonly describing higher- or lower-priced whiskeys. Ten terms were selected for a survey of American whiskey consumers. Professional whiskey reviewers commonly describe expensive whiskeys as tasting of “sultanas”, “oak”, “leather”, and “chocolate”. “Corn” and “grassy” are used commonly for inexpensive whiskeys. In contrast, US consumers are more likely to purchase whiskeys with “chocolate” and “caramel” flavor, ranking “corn” near the middle of the 10 terms tested and “tobacco”, “leather”, and “grass” the lowest. This study shows that the flavor terms reviewers use for expensive whiskeys aren’t necessarily most important to consumers, possibly due to bias from unblinded tastings or differences between reviewers and consumers. Predictions based on reviews can also overestimate the negative impact of common or expected flavors (like “corn” or “caramel” in whiskeys). Large correlational studies using convenient text corpora can effectively generate hypotheses or identify vocabulary and follow up surveys or controlled sensory experiments using the population of interest can provide additional insights about the product category and the groups of people interacting with it.