ABSTRACT GIPSON, RACHEL SIMONE. Sensory Characterization

ABSTRACT

GIPSON, RACHEL SIMONE. Sensory Characterization of Specific Wood Smoke Aromas and their Contributions to Smoked Cheddar Cheese Flavor and Consumer Perceptions of Smoked Cheddar Cheese. (Under the direction of Dr. MaryAnne Drake).

Smoked cheeses are created by the addition of smoke flavoring to cheese milk or by natural cold smoking of curds or cheese using a variety of woods. Consumer interest in smoked cheese is growing, however, there is a need to understand the aromatics that smoke contributes and how the aromatics influence the flavor of smoked cheese. Furthermore, an understanding of the sensory properties and consumer perceptions of smoked cheese will help guide product development and meet consumer expectations.

In the first study, the sensory properties of different wood smokes were characterized through projective mapping, and the aromas of Cheddar cheese smoked with four distinct wood smokes was evaluated through descriptive analysis. The purpose of this study was to characterize the sensory properties of different wood smokes and their application to smoked Cheddar cheese.

There were nine wood smokes evaluated, and these included: apple, alder, cedar, cherry, hickory, maple, mesquite, oak, and pecan. A trained panel generated sensory attributes for the nine wood smokes and then did projective mapping of the different wood smoke aromas. Twenty-five attributes were generated to describe wood smoke aromas, and the most commonly used sensory descriptors were sweet aromatic, charcoal/charred, guaiacol, meaty, vanillin, and fresh tobacco.

Following this, cold smoking of Cheddar cheese was completed with four distinct wood smokes chosen from the projective map and this included: mesquite, cherry, hickory, and cedar. The distinct aromas seen in these four wood types were also imparted to smoked Cheddar cheeses.

Mesquite smoked cheese was characterized by high smoke aroma, cherry smoked cheese was characterized by campfire/marshmallow flavors, hickory smoked cheese was characterized by

high overall smoke and campfire/marshmallow flavors, and cedar smoked cheese was characterized by resinous flavors. Determination of the sensory properties of different wood smokes provides insight into the differences in smoke flavor contributions to smoked cheese.

In the second study, consumer perceptions of smoked cheese were evaluated through focus groups, surveys, and consumer acceptance testing. Three focus groups (n=29) were conducted with smoked cheese consumers. Following this, two online surveys were conducted.

The first survey (n=1195) objective was to understand smoked food consumption habits and to identify if consumers consider smoked cheese to have more product attributes other than just

‘smoked’. Then, an Adaptive Choice-Based Conjoint (ACBC) (n=367) was conducted to evaluate ideal smoked cheese product builds and trade-offs for smoked cheese consumers. This survey also included Maximum Difference scaling and familiarity questions. Consumer acceptance testing (n=135) was conducted with three cheeses smoked with three different woods at low and high intensity (six cheeses total). Focus group results indicated that smoked cheese was perceived as an artisan product and that appearance and price were strong purchase factors.

Consumers did not have awareness of methods for producing smoked cheese, but once they were informed of the two common processes used, consumers preferred cold smoking over liquid smoke addition. Survey results confirmed that consumers can conceptually differentiate between different products and wood smokes. Attributes that were most important for purchasing smoked cheese were method of smoking, smoke intensity, type of wood and type of cheese. Additionally, results from the consumer acceptance test showed that consumers differentiated smoke aroma and flavor among cheeses and preferred cherry smoked cheeses over apple or hickory smoked cheeses. An understanding of consumer perceptions and expectations of smoked cheese provides a platform for producers of smoked cheese to meet consumer expectations.

Sensory Characterization of Specific Wood Smoke Aromas and their Contributions to Smoked Cheddar Cheese Flavor and Consumer Perceptions of Smoked Cheddar Cheese

by Rachel Simone Gipson

A thesis submitted to Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the degree of Master of Science

Food Science

Raleigh, North Carolina

2019

APPROVED BY:

______Dr. MaryAnne Drake Dr. Dana Hanson Chair of Advisory Committee

______Dr. Jason Osborne

BIOGRAPHY

Rachel Simone Del Toro-Gipson was born on November 29th, 1993 in Gilroy, California.

Following high school, Rachel attended Gavilan Community College, where she graduated in

2014 with an Associate’s degree in Health Science. Rachel transferred to California Polytechnic

University, San Luis Obispo, and graduated in 2017 with a Bachelor’s degree in Nutrition and a minor in Food Science. During her time as an undergraduate, she worked as a server at a local brewery, was a member of Alpha Omicron Pi sorority, ran a cooking blog, and participated in nutrition and food science research. Rachel’s academic goals took her to Raleigh in August 2017, where she pursued her Master’s degree in Food Science under the direction of Dr. MaryAnne

Drake. Rachel worked in the lab for just under 2 years while completing her degree, and graduated in June 2019. While not at work, Rachel spends her time going to hot yoga classes and run clubs, hiking and spending time outside, making charcuterie boards, and traveling with friends.

ACKNOWLEDGEMENTS

To my mom, thank you for supporting me even though my endeavors took me far away from you. Your strength and resilience have helped me learn the value of my own strength, and your encouragement has helped me persevere through this chapter. To my brother, thank you for making me feel ‘cool’ for wanting to be a scientist and for patiently answering all of my novice questions about computer programming. To Liz and Gianna, thank you for visiting me and for the constant friendship that has never wavered and only grew stronger during my time away. To

Lee, thank you for making sure I ate dinner on long workdays and for just being you. To my friends who became my family when I could not fly home to see my own, thank you for teaching me that home is not merely a place, but a feeling.

To everyone who believed in me, pushed me, and supported me along the way, I am so grateful for you. Thank you to the professors and teachers I had who encouraged me to pursue higher education. Thank you to my committee members, Dr. Hanson and Dr. Osborne for your time and guidance. And last but most certainly not least, thank you to Dr. MaryAnne Drake. You took a chance on me as a graduate student and the opportunity to be one of your students has changed my life.

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TABLE OF CONTENTS LIST OF TABLES ...... vi LIST OF FIGURES ...... vii

CHAPTER 1: LITERATURE REVIEW. EVALUATION METHODS FOR SMOKING CHEESE AND SENSORY METHODOLOGY USED TO EVALUATE AROMAS AND CONSUMER PERCEPTIONS OF SMOKED CHEESE...... 1 Introduction ...... 2 Different Wood Sources and Their Effect on Generated Wood Smoke ...... 2 Smoked Foods ...... 4 Smoked Foods ...... 5 Smoked Cheese ...... 8 Process of Smoking Cheese ...... 10 Liquid Smoke and Smoke Flavoring ...... 10 Cold Smoking ...... 13 Objective Sensory Analysis Methods ...... 15 Descriptive Analysis ...... 15 Projective Mapping ...... 17 Methods to Measure Consumer Acceptance...... 19 Conjoint Analysis...... 19 Maximum Differential Scaling ...... 22 Consumer Acceptance Testing ...... 24 Objectives ...... 25 References ...... 26

CHAPTER 2: SENSORY CHARACTERIZATION OF SPECIFIC WOOD SMOKE AROMAS AND THEIR CONTRIBUTIONS TO SMOKED CHEDDAR CHEESE FLAVOR ...... 35 Abstract ...... 37 Introduction ...... 38 Materials and Methods ...... 40 Experimental Overview ...... 40 Projective Mapping ...... 40 Smoked Cheese ...... 42 Descriptive Sensory Analysis ...... 42 Statistical Analysis ...... 43 Results ...... 44 Projective Mapping ...... 44 Descriptive Sensory Analysis ...... 45 Discussion ...... 46 Conclusion ...... 48 Acknowledgments...... 49 References ...... 50

CHAPTER 3: CONSUMER PERCEPTION OF SMOKED CHEDDAR CHEESE ...... 58

Abstract ...... 60 Interpretive Summary ...... 61 Introduction ...... 61 Materials and Methods ...... 64 Focus Groups ...... 64 General Survey...... 64 Smoked Cheese Survey...... 65 Descriptive Analysis ...... 66 Central Location Testing...... 67 Statistical Analysis ...... 69 Results ...... 71 Focus Groups ...... 71 General Survey...... 72 Conjoint Analysis...... 72 MaxDiff...... 74 Descriptive Analysis of Smoked Cheese ...... 75 Central Location Testing of Smoked Cheese...... 75 Discussion ...... 78 Focus Groups ...... 78 Surveys ...... 79 Descriptive Analysis and Consumer Acceptance Testing ...... 80 Conclusion ...... 83 Acknowledgements ...... 83 References ...... 84

APPENDICES ...... 109 APPENDIX A: Factor loadings for descriptor tags for smoke aroma projective mapping...... 110 APPENDIX B: Selection frequency of product and smoke combination selection (Survey 1) ...... 111 APPENDIX C: Demographic information for ACBC consumer clusters (Survey 2) ...... 114 APPENDIX D: Demographic information and consumption characteristics of smoked Cheddar cheese consumers in the consumer acceptance test (n=135) ...... 117

LIST OF TABLES Table 1.1 Aroma active constituents of smokes ...... 34

Table 2.1 Orthonasal aroma attributes for projective mapping and descriptive analysis of wood smokes ...... 52

Table 2.2 Proximate analysis means for duplicate 10 kg blocks of Cheddar cheese ...... 53

Table 2.3 Frequency of selection of attributes for projective mapping of smokes by trained panelists ...... 56

Table 2.4 Mean sensory attributes of smoked Cheddar cheeses ...... 57

Table 3.1 Product options in the general survey (Survey 1) ...... 87

Table 3.2 Attributes and levels used in the ACBC conjoint survey (Survey 2) ...... 90

Table 3.3 Smoked foods general and specific product and specific-wood smoke selection frequency (n=1195 consumers) (Survey 1) ...... 91

Table 3.4 Attribute importance scores for consumer clusters (Survey 2) ...... 95

Table 3.5 Scaled importance scores for smoked cheese attributes (n=367), (Survey 2) ...... 97

Table 3.6 Maximum Difference (MaxDiff) scaling of smoked cheese attributes by cluster (n=367), (Survey 2) ...... 98

Table 3.7 Trained panel mean sensory attributes of smoked Cheddar cheeses and unsmoked control Cheddar cheeses ...... 99

Table 3.8 Consumer acceptance scores for smoked cheese (n=135) ...... 101

Table 3.9 Two-way ANOVA (smoke type x intensity) for consumer liking means for smoked Cheddar cheese evaluation (n=135 through each sample) ...... 106

LIST OF FIGURES Figure 1.1 Flowchart of method of producing a block of smoked cheese ...... 33

Figure 2.1a Projective map of wood smoke aromas (Dimensions 1 and 2) ...... 54

Figure 2.1b Projective map of supplemental variables used to describe smoke aromas (Dimensions 1 and 2) ...... 54

Figure 2.2a Projective map of wood smoke aromas (Dimensions 1 and 3) ...... 55

Figure 2.2b Projective map of supplemental variables used to describe smoke aromas (Dimensions 1 and 3) ...... 55

Figure 3.1 Moderator guide for smoked cheese focus groups ...... 88

Figure 3.2 Overall mean utility scores for attribute levels for the total population (n=367) from the smoked cheese conjoint survey ...... 93

Figure 3.3 Attribute importance scores from smoked cheese conjoint survey for segmented consumer clusters. (Survey 2) ...... 94

Figure 3.4 Mean utility scores from smoked cheese conjoint survey for segmented consumer clusters. (Survey 2) ...... 96

Figure 3.5 Principal component biplot of smoked Cheddar cheeses ...... 100

Figure 3.6 Consumer acceptance test liking scores for consumer cluster (n=135)...... 107

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CHAPTER 1: LITERATURE REVIEW. EVALUATION METHODS FOR SMOKING CHEESE AND SENSORY METHODOLOGY USED TO EVALUATE AROMAS AND CONSUMER PERCEPTIONS OF SMOKED CHEESE

INTRODUCTION Smoked cheese is a growing specialty category of flavored cheese. Smoked cheeses are created by the addition of smoke flavoring to cheese milk or by natural cold smoking of curds or cheese, using a variety of woods. With increased consumer interest and category growth, there is a need to understand the specific flavors imparted by different wood smokes. The determination of sensory properties of different wood smokes can give insight into the characterization of differences in smoke flavorings. Furthermore, the determination of the sensory properties specific to smoked cheese will provide cheese manufacturers with an understanding of the consumer perceptions of their products. This literature review will explain how a variety of sensory methodologies can be used to characterize the aromatic properties of different wood smokes and smoked cheeses, as well as how the raw materials and processing involved in the smoking process contribute to the final smoked cheese product.

DIFFERENT WOOD SOURCES AND THEIR EFFECT ON GENERATED WOOD

SMOKE

The wood sources utilized in the smoking process have a significant effect on the final smoked product. The composition of the wood smoke depends on the type of wood used for smoldering, the dryness of the wood, the composition of hemicelluloses, celluloses, lignin, and resins, as well as the temperature and access of air to the zone of oxidation of the volatile products (Sikorski and Kołakowski, 2010). When wood smoke is exposed to food, there is also the potential that food components can serve as intermediates in the formation of smoke flavor compounds (Maga, 1992). Wood smoke is developed through the partial burning of wood with a limited oxygen supply. The wood smoke generated contains gaseous products of thermal

2 degradation, and partial oxidation of the wooden material, as well as dispersed soot and compounds present in fluid or particle form (Sikorski and Kołakowski, 2010).

Sources of wood can be classified into two main groups, hardwood and softwood. These type of woods differ in their composition. Softwoods have more lignin and more resin extractives and are comprised of woods such as cedar and pine. Hardwoods are higher in syringol derivatives and softwood has more guaiacol derivatives, which causes them to produce distinct smokes that vary in amount of phenolics. Hardwoods are comprised of woods such as oak and cherry (Pallu, 1971; Maga, 1988; Maga, 1992). The three major components of woods include hemicellulose, cellulose, and lignin. Hemicellulose is usually composed of a combination of five-carbon sugars including glucose, mannose, and galactose. Cellulose is a long chain glucose polymer. The third component is lignin, a phenolic based compound with many combinations of hydroxyl- and methoxy-substituted phenylpropane units (Maga, 1992). The degradation of these components through smoking is what creates the different sensory properties of smoked foods. The temperature at which the thermal degradation occurs for the varying wood constituents can range from 180-300°C for hemicelluloses, 260-350 °C for cellulose, and 300-500 °C for lignin (Sikorski and Kołakowski, 2010). At temperatures lower than 170°C, free and bound water loss occurs, and only non-combustible gasses, primarily water vapor with traces of carbon dioxide, formic acid, acetic acid, and glyoxal are produced. At temperatures above 500°C, secondary reactions occur; all volatile material is gone and the remaining residue is activated char that can be oxidized to carbon dioxide, carbon monoxide, and water vapor (Beall and Eickner, 1970; LeVan, 1989; Maga, 1992). The thermal degradation of these three wood constituents is responsible for the generation of a variety of compounds within the wood smoke. Through thermal degradation, cellulose generates glucose, acetic acid and

3 homologs, water, furans and phenolic compounds. Thermal degradation of hemicellulose produces furans and carboxylic acid. The products of decomposition of cellulose and hemicellulose occur as a result of caramelization from Maillard reactions, and it has been hypothesized that this process produces fruity and floral scents due to combustion at lower temperatures, however, this has not been confirmed through sensory analysis (Sikorski and

Kołakowski, 2010). Pyrolysis of lignin generates phenolic compounds and ethers, in addition to carbonyl, acidic and alcoholic compounds (Sainclivier, 1985; Miler and Sikorski, 1990).

Smoke can be generated at a relatively low temperature, representing primarily hemicellulose degradation. Under these conditions, lignin might not be completely degraded and the resulting smoke would have a different composition than if a higher temperature were utilized (Maga, 1992). Wood smoke is comprised of air, water vapor, carbon dioxide, carbon monoxide, and several hundred organic compounds in different concentrations; many of the compounds have been identified through chromatographic and spectral analytical methods.

Despite being able to know the factors that affect the generation of compounds in wood smoke, there has not yet been an advance made in predicting the exact content of various compounds in the smoke (Sikorski and Kołakowski, 2010).

SMOKED FOODS

Smoke has been used in food since ancient times as a preservation technique. However, smoke has evolved beyond this in the food industry today. Food smoking increases the shelf life of foods, prevents food poisoning through antimicrobial components of wood smoke, and adds a desirable smoky flavor (Sikorski and Sinkiewicz, 2014). Today, consumer demand for smoked foods is mainly due to their unique flavor characteristics, rather than prolonged shelf life

(Chambers et al., 1998). Smoking food is a popular artisan technique that adds flavor and depth to food products.

Smoked Foods

The aromatic character of smoke is influenced by the following factors: type of wood, method of smoke generation, method of smoke collection, and the process and conditions of combustion (Fujimaki et al., 1974). Early studies speculated about potential origins of smoke flavor in order to characterize the types of aromas produced. These studies hypothesized that characteristic smoky flavor did not appear to be limited to one class of compounds, but instead was a blend of compounds belonging to many different classes (Fiddler et al., 1970).

Initial attempts to characterize smoke began with identification of phenols. A study done by Fujimaki et al. (1974) reported that the quantity and composition of flavor components in the carbonyl, non-carbonyl, neutral/basic, acidic and phenolic fractions of smoke contributed to differences in aroma; the phenolic fraction being the most important. Smoke was collected from

6 different types of wood and was distilled to create smoke condensate. Flavor constituents were then extracted from the condensate and separated by gas chromatography. Sensory evaluation of the distilled smoke condensate, along with gas chromatography-mass spectrometry (GC-MS), indicated that differences in aroma were due to differences in relative amounts of carbonyl, non- carbonyl, neutral, basic, acidic, and phenolic compounds, rather than the presence of distinctly different compounds (Fujimaki et al., 1974). Other studies have confirmed that phenolic compounds play an important role in smoke flavor (Maga, 1992).

Phenols remained the analytical focus to understand smoke flavor. Phenols are also associated with many other effects of smoking: color, preservation and flavor formation. In wood smoke production, phenols are developed through pyrolysis of lignin monomers

(Wittkowski et al., 1992). Lignin is an amorphous, polyphenolic material that is formed through enzymatic dehydrogenative polymerization of three phenylpropanoid monomers, coniferyl alcohol, sinapyl alcohol, and p-coumaryl alcohol. Lignin is a main component of vascular plants, and as such, it contributes 24-33% to normal softwoods and 19-28% of temperate-zone hardwoods. Lignified wood cells contain lignin; in most wood cells, lignin binds and stiffens wood fibers through its distribution within the cell walls. Within wood, lignin is essential to the internal transport of water, nutrients, and metabolites. Lignin is responsible for the rigidity within cell walls and binds wood cells to make them resistant to compression, impact, bending and biological degradation (Gargulak et al., 2002). In the context of smoke production, lignin must go through lignin pyrolysis, a decomposition step, in order to produce flavor compounds such as phenols, which are associated with smoke aroma.

In lignin pyrolysis, the guiacol derivatives that are produced at 250-300 °C form pyrocatechols. Subsequently, methylated products are developed and methyl radicals are generated with the alkyl cleavage of the methoxy group occurs, creating alkyl and dialkylphenols. Phenols are strongly concentrated when condensing smoke in an aqueous solution (Wittkowski et al., 1992). However, several studies have also established the contributions of other compounds to smoke aromas (Porter et al., 1965; Fidler et al., 1970; Kim et al., 1974; Hruza et al., 1974). Maga and Fapojuwo (1986) reported that the carbonyl fraction of smoke was the primary contributor to flavor for most woods. The carbonyl fraction of wood smoke originates through thermal decomposition and rearrangement of cellulose and hemicellulose through carbohydrate degradation; this fraction contains many compounds that have been identified from wood smoke (Maga, 1987). Their objective was to establish that the carbonyl fraction of smoke contributed much of the smoke aroma in order to reduce the need for

6 the phenolic fraction in many smoke sources. The sawdust of eight wood types was used to generate smoke, which was condensed and fractionated into a total ether extract, and then into carbonyl, neutral, basic, and phenolic fractions. The intensities of each fraction were evaluated by sensory analysis and recorded for each respective wood source. This study indicated that classes of compounds other than phenolics contributed significantly to smoke aroma. For most wood smokes (excluding mesquite), the phenolic fraction contributed to smoke intensity but statistically was not the major contributor to smoke intensity (Maga and Fapojuwo, 1986).

Further studies were able to identify over 400 volatile compounds in wood smoke; most of which were carbonyls and phenols (Maga, 1992). Additionally, Cadwallader (1996) compared aroma extracts prepared from hickory and mesquite liquid smokes by gas chromatography- olfactometry (GCO) and aroma extraction dilution analysis (AEDA). Results indicated that while phenolic compounds were key components of smoke flavor, other constituents such as carbonyls and acids were important contributors to smoke aroma (Cadwallader, 1996). Additionally, a simpler explanation for the varying components within wood smoke was presented by Sikorski and Kołakowski (2010) related to the composition of wood smoke generated from a smokehouse.

They suggested that due to the action of the gravitation and centrifugal forces within a smokehouse and the temperature gradient, some components are deposited on smoked goods, while others are deposited in smoke ducts and on the walls of the smokehouse, causing a change in the concentration of the smoke (Sikorski and Kołakowski, 2010).

Wood smoke has also been analyzed by sensory techniques. In the aforementioned study conducted by Maga and Fapujowo (1986), the total ether extract and the other four fractions from wood sources were presented to a trained panel (n=24) and the overall aroma intensity was evaluated on a 10-point intensity scale (Maga and Fapojuwo, 1986). This sensory evaluation

7 focused on smoke condensate fractions, which provided information about how each fraction contributed to the overall smoke intensity of each smoke. Another study by Mcilveen and

Vallely (1996) involved a mixture of discrimination and descriptive tests where panelists evaluated smoked processed cheese products using scaling techniques. The objective of the study was to generate an ideal recipe for processed smoked cheese. Consumers of processed, smoked cheese (n=50) participated in an acceptance test in which they tasted a processed cheese that had been cold smoked for five hours, and a cheese that had added 4% (w/w) smoke flavoring. The cheese with smoke flavoring was preferred. Researchers concluded that by smoking food, value can be added to an otherwise bland product and a selling point created. However, the use of added flavorings and the image often attached to processed cheese may need further consideration (Mcilveen and Vallely, 1996).

Smoked Cheese

The smoky flavor of smoked cheese occurs when the compounds within the smoke particulates are deposited on the product surface. Mcilveen and Vallely (1996) found that the higher the intensity of smoke, the greater its absorption into the food. It was hypothesized that smoke particle condensation on food surfaces was reduced as temperature decreased. However, if relative humidity is high, steam will condense on the surface of the product and increase the absorption of the water-soluble parts of the smoke (Mcilveen and Vallely, 1996). The compounds that contributed to the formation of the smoky flavor through smoke production were mainly the following phenolic compounds; syringol, 4-methylsyringol, 4-allylsyringol, guaiacol,

4-methylguaiacol, and trans-isoeugenol. Carbonyl compounds, furans, and other smoke constituents played a role as well, although the exact concentrations of different smoke

8 components as they contributed to flavor have not been disclosed (Sikorski and Sinkiewicz,

2014).

Though several studies have used various sensory methodologies to evaluate smoked foods, studies determining sensory characteristics of smoked cheese have not been widely documented. Rehman et al. (2003) conducted a study in which they observed the effects of the application of natural wood smoke on ripening of Cheddar cheese and determined the effects of smoking before or after ripening on cheese quality. This study involved trained panel sensory analysis of 6 and 9-month old cheeses. Flavor attributes scaled included previously identified

Cheddar flavor sensory descriptors, as well as two additional terms, smoky and skunky, to describe the smoked character of the cheeses. Based on trained panel data, cheeses smoked after ripening for 3 or 6 months had the most desirable smoked flavor in Cheddar cheese as a result of having high smoke flavor and low skunky flavor (Rehman et al., 2003). Jaffe et al. (2017) published a lexicon that established 14 attributes to describe smoked foods, which included sauces, meats, fish, cheeses, vegetables, flavorings, as well as in-house smoked products. A wide range of smoked products was evaluated for the study and the lexicon contained attributes that related specifically to the smoke aromas of the foods. The fourteen identified attributes were: smoky (overall), ashy, woody, musty/dusty, musty/earthy, burnt, acrid, pungent, petroleum-like, creosote/tar, cedar, bitter, metallic, and sour (Jaffe et al., 2017). The lexicon introduced the idea that the term ‘smoke’ was no longer sufficient to cover all aromas that encompassed by smoke.

However, this study did not make any mention of smoked cheese nor an attempt to characterize the aroma characteristics of different wood smokes.

PROCESS OF SMOKING CHEESE

The process of smoking cheese occurs commercially through two main methods, the addition of liquid smoke to cheese milk or cold smoking of cheese blocks or fresh cheese curds.

Liquid smoke is a condensed smoke flavoring that is produced by condensing and purifying the smoke emitted from burning wood (Mcilveen and Vallely, 1996). When wood is burned, the thermal decomposition of the wood followed by oxidation generates many solid, liquid, and gaseous compounds. The compounds differ in boiling point, solubility, chemical properties, and their involvement in food smoking (Sikorski and Sinkiewicz, 2014). In contrast, the process of cold smoking involves applying smoke to a food product at room temperature for a designated amount of time. Smoking methods are normally characterized by the temperature used. Cold smoking is characterized by the range of 12-25 °C, warm smoking occurs at 23-45 °C, and hot smoking occurs in a range of 50-90 °C to accommodate for thermal denaturation of meat proteins (Sikorski and Kołakowski, 2010). The cold smoking method is most commonly utilized with cheese in order to prevent the product from melting so that it can maintain a more stable structure (Mcilveen and Vallely, 1996).

Liquid Smoke and Smoke Flavoring

Liquid smoke condensates are produced through physical condensation of smoke or the volatile products of dry distillation of wood. Smoldering smoke enters a condenser at a constant temperature. This prevents the condensation of water vapor and allows for higher boiling point constituents of smoke to be condensed. Liquid smoke can also be produced through distillation, which occurs at normal pressure or under a vacuum at elevated temperature (Sikorski, 1990).

The solid, liquid and gaseous compounds are comprised of water, carbon monoxide, carbon dioxide, alcohols, carbonyl compounds, carboxylic acids, esters, hydrocarbons, nitrogen oxides,

10 and phenols. These components vary and the chemical composition of liquid smoke depends primarily on the wood type and moisture content of the wood. The moisture content has a significant influence on the pyrolysis temperature and the duration of the smoke generation

(Guillen and Ibargoitia, 1999; Cadwallader, 2007).

Prior to a study by Fiddler et al. (1970), it was hypothesized that the characteristic smoke aroma did not originate from just one compound, but from multiple compounds. The study involved fractionation of an ether extract concentrate of a commercial liquid smoke solution through gas-liquid chromatography. A sensory test (n=30) was conducted in which panelists were asked to select the smokier sample of the two samples of frankfurters treated with different fractions of smoke. The frankfurters were dipped into solutions of the various fractions for approximately 15 seconds and then were cooked in a commercial smokehouse. Panelists were asked to score the intensity of the sample they perceived to be smokier for degree of smokiness on a 7-point scale where 0=not smokier and 5-6=considerably more smoky than the other member of the pair. After analyzing gas-liquid chromatography results and conducting the sensory evaluation, it was determined that the characteristic smoky flavor of the liquid smoke concentrates contained primarily phenols and carbonyls (Fiddler et al., 1970). Further examination into liquid smoke was conducted by Bates et al. (1981) who reported that commercial, full-strength liquid smoke was composed of water (11-92%), tar (1-17%), acids

(2.8-9.5%), carbonyl containing compounds (2.6-4.6%) and phenol derivatives (0.2-2.9%). In separate studies, it was reported that phenolic compounds contributed to smoke flavor and color of liquid smokes and had antibiotic and antioxidant properties (Clifford et al., 1980; Maga, 1987;

Varlet et al., 2010). The carbonyl-containing compounds had sweet or burnt-sweet aromas and balanced the harsher, phenolic compounds. The carbonyl compounds also impacted the texture

11 and color of smoked food through protein interactions and Maillard reaction products (Varlet et al., 2007).

There is some debate over the consumer acceptability of liquid smoke, because of its seemingly ‘unnatural’ method as a source of smoke. Liquid smokes are either full-strength or refined to have better control over polycyclic aromatic hydrocarbon (PAH) content, a wider diversity of applications to food systems, superior product homogeneity, ease of storage, and less environmental pollution (Montazeri et al., 2013). PAHs are compounds containing two or more condensed aromatic rings, and comprise the largest class of carcinogenic compounds

(Cadwallader, 2007). Several determinants of PAH in smoked foods include temperature during smoking, as well as wood composition and more specifically lignin content. Products that experience direct smoke exposure tend to have higher PAH concentration than products with liquid smoke flavorings, which can have complete elimination of PAH through condensation and processing (Cadwallader, 2007). Due to differences in various smoked foods regarding mutagenic and carcinogenic activities of PAH, it is difficult to predict the degree of health hazard caused by these compounds in smoked foods and can potentially be seen as a deterrent to consumers when purchasing smoked products (Sikorski and Sinkiewicz, 2014). There has not been much definition of the appropriate usage of liquid smoke in food systems, likely due to the relative ‘newness’ of smoked food products. The chemical composition of commercial liquid smokes can provide information about interactions with the chemical components of food systems. This information, when combined with an understanding of sensory characteristics, can in turn help give key points to define functions and appropriate uses of liquid smokes in food systems (Montazeri et al., 2013).

Cold Smoking

Smoking methods are normally characterized by the temperature used. Smoking methods include cold smoking, where the temperature does not exceed 30°C, warm smoking at around

40°C, and hot smoking, a combination of intense heat (80°C) and smoke (Mcilveen and Vallely,

1996). Cold smoking is used during smoked cheese production because it prevents the product from melting and allows it to maintain its structure (Mcilveen and Vallely, 1996). During cold smoking, the product must be arranged in the smoking unit to allow for uniform smoke absorption, temperature exposure, and drying (“Summary of Cold Smoking Process”, 2001).

Further considerations in contemporary industrial smoking include: the temperature of smoke generation, proper circulation of the smoke, and drying air in order to reach the required degree of uniformity of smoke deposition, water evaporation, and heating, as well as to control all process parameters affecting the quality of the products (Sikorski and Kołakowski, 2010).

Industrial cold smoking typically occurs in a smokehouse, which consists of the smoking room, and a smoke generator designed to control process parameters such as temperature or air flow. Sawdust or wood chips are automatically fed onto a plate or grate in the smoke generator, and are burned at a controlled temperature of about 350 ̊C. The air needed for smoldering is blown from below the plate, through an inlet. The temperature of the sawdust depends on the temperature of the heated grate and the volume of air. If the sawdust used is small in size, the flow of air may be blocked and thus the temperature will be below that of the grate; as a result, the smoke will be rich in carbon dioxide. The addition of wood chips causes an increase in the temperature of the grate and the phenolic compounds in the smoke. Automatic smokehouses have drafts forced by mechanical equipment that can be adjusted depending on the product. Cold smoking in an automatic smokehouse generally occurs at about 12-25 ̊C; the temperature of the

13 smoke affects the sensory properties of the final smoked product and controls the rate of the process (Sikorski and Kołakowski, 2010). In recent years, there have been several developments to traditional smoking methods. Sikorski and Kołakowski (2010) noted that these developments included control of composition of smoke by use of established procedures of smoke generation, use of engineering principles regarding heat and mass transfer to optimize the processing, modernization of smokehouses to improve the smoke generation and the process, as well as treatment of spent smoke to decrease pollution effects. Specifically for smoking methods related to cheese products, McLeod (2017) submitted a patent for natural wood smoking of cheese curds. Using this method, a smoked block of cheese is prepared by exposing the cheese curds, rather than the pressed block of cheese, to natural wood smoke. By this process, the block of cheese is evenly smoked in a short period of time. This process is a stark contrast to the traditional method of cold smoking cheese, which is a batch process (rather than a continuous process) and requires several days in a smokehouse for even smoking. Naturally smoked cheeses by the traditional cold smoking method typically have a gradation of smoked flavor from the exterior to the interior. The newer process of adding liquid smoke to cheese milk produces a cheese with an even intensity of smoke flavor but the product is ‘smoke-flavored’ and not smoked (McLeod, 2017). A visual representation of this process can be found in Figure 1.

The cold smoking process causes color changes in smoked foods. Several components cause the color change that occurs in cold smoking: the deposited, colored smoke components on a smoked food product, their changes during heating and storage, and their interactions with the surface material of the product. A chemical change that occurs with smoking and increased heat is polymerization of phenols and Maillard reactions, which promotes darker coloring of the smoked food products (Sikorski and Sinkiewicz, 2014). High temperature favors the

14 development of dark color because it increases the concentration of the components of the dispersing phase of smoke. Higher temperatures also increase the rate of the carbonyl-amino reactions and polymerization of various components (Sikorski and Kołakowski, 2010). Studies have also found that a significant contribution of the color of smoked food products comes from the reaction of the carbonyl compounds: glycoaldehyde and methylglyoxal mainly found in the vapor phase of smoke, with the amino groups of proteins and nonprotein nitrogen compounds.

The smoke phenols react with proteins at weak alkaline conditions and form colors as a result of the reaction (Ziemba, 1969; Ruiter, 1979).

OBJECTIVE SENSORY ANALYSIS METHODS

Objective sensory analysis methods are used to generate data that is analytical in nature using trained panelists. Some examples of objective sensory methods include difference tests, threshold tests, and descriptive analysis. The goal of an objective sensory analysis method is for the panel to act as an instrument and produce data that is analogous to instrumental data (Lawless and Heymann, 2010).

Descriptive Analysis

Descriptive analysis is a widely used sensory technique in which a trained panel generates a complete product profile (Lawless and Heymann, 2010). The qualitative attributes that are analyzed in descriptive analysis include aroma, appearance, flavor, texture, aftertaste and sound properties of a product. A major strength of descriptive analysis is its ability to allow relationships between descriptive sensory and instrumental or consumer preference measurements to be determined (Murray et al., 2001). Descriptive analysis methodologies vary based on philosophy and approach; commonly used methods include Flavor Profile method,

Texture Profile Method, Quantitative Descriptive Analysis™, Spectrum Method™, Quantitative

Flavor Profiling, Free-choice Profiling, and generic descriptive analysis. Despite different methodologies, several elements of a descriptive analysis panel are essential to all processes.

Descriptive analysis methods require panelists with some degree of training in evaluating the product. Following the formation of a panel, there is a need to develop a common language to describe product attributes. Then, the panel is trained to use a common frame of reference to define attributes of a product and their intensities on a scale, relative to reference points.

Procedures during descriptive analysis training are related to the method chosen, as well as the time requirement for training and the products available (Murray et al., 2001).

Following data collection from descriptive analysis, there are several statistical procedures used in data analysis. Data analysis within descriptive analysis aims to understand how samples differ in their sensory aspects, which differences can be reported as repeatable as opposed to chance variation, and how are panelists performing as a whole, as well as individuals.

In order to determine differences between samples, the samples are initially compared based on mean scores to understand variation. The analysis used for this task is an analysis of variance, also called an ANOVA. The purpose of an ANOVA is to determine if variation in sample means is greater than that expected from panel variation alone. Once there are confirmed variations among samples, a principal component analysis (PCA) can be conducted, provided there are a sufficient number of samples to conduct a PCA. This multivariate technique gives a low dimensional representation of sample differences in a multidimensional sensory space, by finding new components or directions in the overall sensory space, in order to understand sample variation. Within a principal component biplot, the principal components pass through the

16 centroid of attribute means, and determine the multivariate sample space that explains sample variation (Kemp et al., 2018).

Projective Mapping

Projective mapping is a multidimensional data collection method in which panelists place products directly into a two-dimensional space based on their perceived similarity (Nestrud and

Lawless, 2010). Early foundations of projective mapping were sorting techniques. Sorting is a form of nominal measurement; pairs of products are placed either in the same category or not for each subject. Nestrud and Lawless (2010) conducted a study comparing sorting and projective mapping by employing both methodologies to generate product maps and cluster analyses separately for cheese and apples. The binary nature of sorting may have limitations based on the dimensions related to certain areas of the plot, while projective mapping allowed less strongly related dimensions to emerge. Several studies have also investigated the ability of projective maps to clearly represent a product space (Giménez et al., 2014; Vidal et al., 2016). Other studies have found that comparison of descriptive analysis data and projective mapping data shows distinct relationships between data (Nestrud and Lawless, 2008; Kennedy and Heymann, 2009;

Albert et al., 2011) and another study suggested that projective mapping is a potential alternative to descriptive analysis if descriptive analysis is not available (Bárcenas et al., 2005).

The first instance of projective mapping within the scope of food science was done by

Risvik (1994) in which panelists were given chocolate samples and a sheet of paper with two crossed axes; panelists were asked to place the samples on the two-dimensional space according to how they perceived them to be related to each other. Panelists were told to place samples close together on the map to represent similar samples, and to place samples further apart to show how different they are (Risvik et al., 1994). Typical statistical analyses conducted on projective

17 mapping data include Generalized Procrustes Analysis (GPA), Principal Component Analysis

(PCA) and Multiple Factor Analysis (MFA). Generalized Procrustes Analysis (GPA) involves product coordinates grouped within assessors (King et al., 1998; Nestrud and Lawless, 2008;

Risvik et al., 1994). Principal Component Analysis (PCA) involves product coordinates as separate attributes for which the assessors significantly differentiate the products (Pagès and

Husson 2001; Nestrud and Lawless, 2008; Risvik et al., 1997). Multiple Factor Analysis (MFA) is a newer method which involves a scaled PCA analysis that provides information about the perceptual differences between subjects (Pagès and Husson, 2001; Pagès, 2004).

These three methodologies have been compared and the results showed that they generated similar profiles for samples based on RV coefficients, which is a type of multivariate correlation coefficient (Nestrud and Lawless, 2008). A study conducted by Perrin et al. (2009) found that projective mapping and descriptive analysis separately gave similar product representations, however, the projective mapping data had higher variability. Projective mapping alone cannot characterize the product, and benefits from the addition of descriptive analysis or instrumental data. When the two data analyses were combined, more interpretations of product attributes were found (Perrin and Pagès, 2009). In the aforementioned study where projective mapping and sorting data was analyzed for apples and cheese, Nestrud and Lawless (2010) concluded that projective mapping and descriptive analysis combined allowed for competitive analysis of products where some or all products in a similar category can be compared (Nestrud and Lawless, 2010).

METHODS TO MEASURE CONSUMER ACCEPTANCE

Conjoint Analysis

Conjoint analysis is a technique that measures consumer trade-offs through survey responses to preferences and intentions to buy (Green, 2004a). Within a conjoint analysis, there are profiles and choice sets. A product may have three attributes, A, B, and C, and within each attribute there are four levels: a1, a2, a3, a4, b1, b2, b3, b4, c1, c2, c3, and c4. A product profile could consist of a1, b3 and c2, while a choice set could consist of {(a1, b2, c3); (a2, b1, c4); (a4, b3, c2); (No Choice)}. When preferences are made for a product profile, the resulting data is a rating or a rank. Preferences about choices by consumers are made amongst items in a choice set

(Rao, 2010).

Early development of conjoint analysis was conducted by Green and Rao (1971). Green and Rao suggested that conjoint analysis would be useful for finding component utilities for different factors of a product when they are jointly considered, such as how the varying levels of

3 specific attributes influence consumer perceived purchase intent for a product. Another proposed usage for conjoint analysis was promotional congruence testing, which involves measuring the joint effects of congruent characteristics such as package design, copy theme, price, and brand image on the overall evaluation of a brand. These uses for conjoint analysis are useful in the research and development aspect of understanding consumer perceptions of a food product, without the high cost of investment and production required to make the product.

Conjoint analysis is a measurement technique to quantify buyer trade-offs and values, and it serves as an optimization technique for understanding product service profiles that maximize return (Green et al., 2004b).

The types of conjoint analysis that are commonly used today are traditional full-profile conjoint analysis, adaptive conjoint analysis, choice-based conjoint, and adaptive choice-based conjoint. Traditional full-profile conjoint analysis was the original conjoint method. This method is limited by the amount of attributes and levels that can be shown to respondents, as it is fatiguing. Adaptive conjoint analysis (ACA) was developed to handle large numbers of attributes. ACA incorporates the presentation of pairs of partial profiles, generally consisting of levels of two or three attributes from a full set of attributes (Green, 2001). ACA requires respondents to rank or rate attribute levels and to then assign importance values to each attribute.

Choice based conjoint (CBC) analysis uses stated choices. This method measures consumer responses to questions that reflect consumer decision-making and measures interactions between attributes to determine if they have an effect on a choice or if two attributes are correlated.

Adaptive choice-based conjoint (ACBC) analysis employs an adaptive experience that generates an individually designed survey based on respondent previous responses. ACBC begins with a consider-then-choose model where respondents are presented with a variety of product concepts, and then they choose products based on the responses they gave. Finally, respondents participate in a section where they choose products from a series of product concepts (Jervis et al., 2012).

A conjoint methodology is based on a decompositional approach in which respondents react to a set of ‘total’ profile descriptions, and then part-worths of importance are consistent with the respondents preferences (Green and Srinivasan, 1978). A conjoint analysis first begins with selecting a model of preference, such as a mixed model. Options for preference models include the vector model which is linear, the ideal point model which is linear and quadratic, a part-worth function model which is piecewise linear, and a mixed model in which some attributes follow a part-worth function model while other attributes follow vector or ideal point

20 models (Green and Srinivasan, 1990). Following this, data collection is needed. Data collection may entail questioning consumers about the attributes that matter most to them, or the attributes that are most relevant (Braun and Srinivasan, 1975). Then, the stimulus profiles are constructed for the full-profile method. This involves investigating how many stimuli are needed, the range of attribute variation and inter-attribute correlation in constructing the stimuli, and how stimuli themselves should be constructed. Following this, a decision must be made about how the stimulus should be presented. Several approaches used include verbal descriptions, paragraph descriptions, and pictorial representations. The dependent variable in the experiment must also have a defined measurement scale to measure the calculate response, such as preference or likelihood to purchase the product. The final step is to generate an estimation method. These range from methods that assume the dependent variable is ordinally scaled, intervally scaled, or methods that relate paired comparison data to a choice probability model (Green and Srinivasan,

1978).

Conjoint analysis is typically analyzed using multiple regression and analysis of variance for parameter estimation (Green and Srinivasan, 1978). Past analyses of conjoint data only estimated main effects, however Green and Srinivasan (1978) commented that interaction effects and specifically two-way interaction effects may be important for sensory phenomena. Utility scores and importance scores are generated from conjoint analyses. Utility scores are scaled to an arbitrary additive constant within each attribute and are interval data. The utilities are scaled to sum to zero within each attribute; negative utility values are not necessarily strong dislike, but they generally represent being less liked than other levels. Attribute importance scores represent calculated percentages from relative ranges that add up to 100% and depend on the particular attribute levels chosen for a study. Importance measures are ratio-scaled, but are also related to

21 specifics within the study. As a result, the importance scores can only be compared within a study but not across studies with different attributes (Orme, 2010).

Conjoint analysis is a useful tool in sensory analysis as it allows consumers to evaluate product and concept builds. A study conducted by Jervis et al. (2012) compared ACBC and CBC to determine key choice attributes of sour cream with a limited sample size. The study found that both methods provided similar outcomes for consumer preferences for different sour cream products. Additionally, with ACBC conjoint, the researchers were able to estimate perception of brand as well as work with smaller sample sizes and still generate actionable data (Jervis et al.,

2012). Other studies have successfully characterized experiences with products by using conjoint analysis as a way to guide product development (Mahanna et al., 2009; Lawless et al., 2013) , or as a way to understand packaging (Gadioli et al., 2013; Mesías et al., 2013).

Maximum Differential Scaling

Maximum differential scaling (MaxDiff) or ‘Best Worst Scaling’ is a technique used to understand how respondents place importance on a variety of issues or attributes of a product.

Best worst scaling requires that a respondent choose one item that the respondent thinks is best or most ‘attribute’ and one that is the worst or least ‘attribute’ from a series of sets that contain different combinations of a larger master set of items (Lee et al., 2007). The founding principle of best worst scaling is that values are guiding principles that determine what is important to people, and they are relatively stable in adults and can motivate behavior (Kahle, 1983, William and Rokeach, 1974). There are many methodologies to measure values, and they all conclude that an individual’s values have a large impact on his or her beliefs, attitudes, behavior and preferences in many ways (Corfman, et al., 1991; Schwartz and Bardi, 2001). Kahle’s List of

Values is a scale that is commonly used to measure values. The values on the list include: a sense

22 of belonging, excitement, warm relationships with others, self-fulfillment, being well respected, fun and enjoyment of life, security, self-respect, and a sense of accomplishment (Kahle et al.,

1988). The scale is derived from Rokeach’s values, and has 9 items that can be measured easily and is well suited to group comparisons (Lee et al., 2007). An understanding of the values that drive the individual allows for a complete understanding of the motivations and behaviors that influence consumer purchases and liking.

A sensory-driven theory behind best-worst scaling is that it is an extension of a paired comparison test (David, 1988; Thurstone, 1927; Buck et al., 2001; Duineveld et al., 2000; Léon et al., 1999; Liem et al., 2004). Instead of choices amongst pairs, the choices are made amongst larger sets of items and best worst scaling identifies the best and worst items. When participants have to select a best and worst or most and least liked item out of a large set, best worst scaling gives more information than a paired comparison, with less input overall. There is also evidence to the theory that best worst scaling allows for increased discrimination of items in a set, because there is a lack of discrimination when items are rated with a monadic rating, as is done in preference and importance scores (Jaeger et al., 2008).

MaxDiff has been used in evaluation of a variety of food products to understand consumer values and beliefs. This technique allows for a comprehensive understanding of consumer preferences. MaxDiff has been used to evaluate consumer preferences within a variety of food products including ground beef (Lusk and Parker, 2009; Chrysochou, 2014), olive oil

(Dekhili et al., 2011), bacon (McLean et al., 2017), and dark chocolate (Thomson et al., 2010).

A recent study by Harwood and Drake (2018) conducted a variety of surveys to assess the qualities of protein products that consumers found attractive. The survey included an Adaptive

Choice-Based Conjoint (ACBC) exercise, a Constant Sum (CS) exercise, and a MaxDiff

23 exercise. Conclusions from the MaxDiff survey were generally in agreement with attribute ratings from the ACBC and CS exercises, and additionally the MaxDiff provided further insight as to the relative importance of specific protein attribute levels for consumers.

Consumer Acceptance Testing

Traditional consumer acceptance testing involves testing with consumers to understand their degree of liking of products. A consumer acceptance test is different from objective sensory methods in that the focus is on the consumer and the consumer interaction with the product and trained panelists are not used, as the untrained consumer gives insight that reflects their ever- changing opinions that can be determined by lifestyle, marketing, and products in the market

(Drake, 2007). Within a consumer test, panelists are asked questions about products with the goal of scaling the degree of acceptability of foods (Lawless and Heymann, 2010). The most commonly used scale in consumer acceptance testing is a 9-pt hedonic scale, which is also called a degree of liking scale. The scale assumes consumer preference is on a continuum from dislike extremely to like extremely. Another commonly used scale is a ‘Just-About-Right’ (JAR) Scale, which is a bipolar scale with anchors of too little, just about right, and too much of a specified attribute. Studies (Resurreccion, 1998; Hough et al., 2006; Meilgaard et al., 2007) have confirmed that a minimum of 50 consumers is required to make any sound conclusion about product liking, although 100 or more are recommended.

OBJECTIVES The objectives of this thesis are to characterize the sensory properties of smoke from different woods alone, and then continue the application to Cheddar cheese. Following these objectives, sensory methods will be used to evaluate consumer perception of smoked cheese. The determination of sensory properties of different wood smokes will give insight into the differences in smoke flavor contributions to cheese. Furthermore, the determination of the sensory properties specific to smoked cheese will provide a platform to understand consumer perceptions of smoked cheese.

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FIGURES

Figure 1. Flowchart of method of producing a block of smoked cheese (Taken from US Patent 290,351, 2017)

TABLES

Table 1: Aroma active constituents of smokes (Terms were adapted from Cadwallader, 1996; taken from Cadwallader, 2007) Smoke Type Compound Aroma Description Liquid Smoke 2,3-Butanedione (diacetyl) Buttery Liquid Smoke l-Penten-3-0ne Plastic Liquid Smoke 2,3-Pentanedione Buttery Liquid Smoke 3- (Methy1thio)propanal Potato Liquid Smoke Butanoic acid Spoiled milk Liquid Smoke 3-Methylbutanoic acid Dried fruit Liquid Smoke 2-Methoxyphenol (guaiacol) Smoky Liquid Smoke 4-Methylguaiacol Smoky, vanilla Liquid Smoke 2-Methylphenol (0-cresol) Ink, phenol Liquid Smoke 4-Ethylguaiacol Cloves, smoky Liquid Smoke 4-Methylphenol (p-cresol) Stable, fecal Liquid Smoke Eugenol Cloves, smoky Liquid Smoke 4-Propylguaiacol Cloves, smoky Liquid Smoke 4-Vinylguaiacol Cloves, spicy Liquid Smoke 2,6-Dimethoxyphenol (syringol) Smoky Liquid Smoke Isoeugenol Cloves

CHAPTER 2: SENSORY CHARACTERIZATION OF SPECIFIC WOOD SMOKE AROMAS AND THEIR CONTRIBUTIONS TO SMOKED CHEDDAR CHEESE FLAVOR

Sensory Characterization of Specific Wood Smoke Aromas and their Contributions to Smoked Cheddar Cheese Flavor

R. S. Del Toro-Gipson, P. V. Rizzo, D. J. Hanson, M. A. Drake*

Dept. Food, Bioprocessing and Nutrition Sciences, Southeast Dairy Foods Research Center, North Carolina State University, Raleigh, NC 27695

*Corresponding author: MaryAnne Drake Box 7624, Department of Food Science North Carolina State University Raleigh, NC 27695-7624 Phone: 9191-513-4598 Fax: 919-513-0014 Email: [email protected]

ABSTRACT

The objective of this study was to characterize the sensory properties of different wood smokes and then their application to smoked Cheddar cheese. Sniff jars of wood smokes were created by exposing filter paper to 23° C smoke (cold smoke). The nine wood smokes evaluated included: apple, alder, cedar, cherry, hickory, maple, mesquite, oak and pecan. Sensory attributes for nine wood smokes were generated by a trained panel followed by projective mapping of the different wood smoke aromas. Four distinct wood smokes (mesquite, cherry, hickory, and cedar) were selected for cold smoking of 30 d Cheddar cheeses. Cheeses were cold smoked at 23° C followed by descriptive analysis of flavor attributes using the trained panel. Nonparametric and parametric statistical analyses were applied to the collected data. Twenty-five attributes were generated to describe wood smoke aromas. The sensory descriptors for the cold smokes cited most often included: sweet aromatic, charcoal/charred, guaiacol, meaty, vanillin, and fresh tobacco. Mesquite, cherry, hickory and cedar smokes were the most distinct smokes by projective mapping, and these smokes also imparted distinct flavors to smoked Cheddar cheeses.

The mesquite smoked cheese was characterized by high smoke aroma, the cherry smoked cheese was distinguished by a campfire/marshmallow flavors, the hickory smoked cheese had high overall smoke and campfire/marshmallow flavors, and the cedar smoked cheese was strong in resinous flavors. The determination of sensory properties of different wood smokes provides insight into the differences in smoke flavor contributions to cheese. Furthermore, the determination of the sensory properties of specific to smoked cheese will provide a platform to understand consumer perception of smoked cheeses.

Key Words: smoked cheese, projective mapping, descriptive analysis

INTRODUCTION Smoked cheese is a growing specialty category of flavored cheese (Market Research

Future®, 2019). Smoked cheeses are created by the addition of smoke flavorings to cheese milk or by natural cold smoking of curds or cheese, using a variety of woods. Food was originally smoked as a method of preservation. However, with the advent of more convenient preservation methods like refrigeration, smoked products are now desirable for their unique and characteristic smoky flavor (Chambers et al., 1998). With the increase in popularity of smoked cheese products, there is a need to understand the aromatics associated with the origins of smoke sources, and how they affect the sensory properties of the final smoked cheese product.

There are several aspects of the smoking process that contribute smoke aromas to smoked cheese. The degradation of the components of wood compounds through smoking creates different sensory properties of smokes. The three main components of wood are cellulose, hemicellulose, and lignin. Cellulose is a long chain glucose polymer. Hemicellulose is generally composed of a combination of five-carbon sugars including glucose, mannose, and galactose. Lignin is a phenolic based compound with many combinations of hydroxyl- and methoxy-substituted phenylpropane units (Maga, 1992). The thermal degradation of wood and wood components through combustion determine the composition of the wood smoke. The composition of wood smoke includes air, water vapor, carbon dioxide, carbon monoxide, and several hundred organic compounds in different concentrations; this is also a factor in determining the aromatic properties of wood smokes (Sikorski and Ko, 2010).

Previous studies have evaluated the volatile components of wood smoke (Fujimaki et al.,

1974; Maga, 1992; Porter et al., 1965; Kim et al., 1974; Hruza et al., 1974). Few studies have investigated the sensory properties of wood smokes. A sensory analysis of wood smoke intensity was initially conducted by Maga and Fapojuwo (1986), in which they scaled the smoke

38 intensities of varying fractions of Cherry, Chestnut, Hard Maple, White Oak, Red Oak, Apple,

Hickory, and Mesquite wood smoke, and were able to conclude that fractions other than phenols also contributed to the aromatic intensity of smoke. Rehman et al. (2003) characterized the effects of the application of natural Hickory wood smoke on ripening of Cheddar cheese to determine the effects of smoking before or after ripening on cheese sensory properties. Two attributes specific to cold smoking, smoky and sulfur/skunky, were documented by the trained panel in addition to flavor attributes specific to Cheddar cheese. A study was recently conducted by Swaney-Stueve (2019) in which pulled pork was prepared with two different types of smokers and four different types of woods; the woods included were hickory, apple, oak, and mesquite.

Pulled pork with hickory wood had the highest overall liking and appearance characteristics

(Swaney-Stueve et al., 2019). Jaffe et al. (2017) identified a descriptive language for smoked foods and reported smoky (overall), ashy, woody, musty/dusty, musty/earthy, burnt, acrid, pungent, petroleum-like, creosote/tar, cedar, bitter, metallic, and sour as attributes applicable to smoked foods. However, the study made no mention of smoked cheese nor specific sensory properties attributed to smoked cheese products. Furthermore, there have not been any studies that have characterized the sensory properties of different wood smokes.

Smoked cheese is a growing category of the dairy market and interpreting the specific aromas and flavors that each wood smoke imparts to cheese will facilitate strategic positioning and marketing. The objective of this study was to characterize the sensory properties of smoke from different woods and the sensory properties of Cheddar cheese smoked with different wood sources. Projective mapping of nine wood smokes and descriptive analysis of smoked Cheddar cheese was conducted. Projective mapping is a method that allows panelists to map products on a two-dimensional space based on similarities and differences (Risvik et al., 1997). Projective

39 mapping has been widely applied to determine similarities and differences of food products, both with trained and untrained panelists (Neustrud and Lawless, 2008; Torri et al.,2013). Projective mapping was chosen as a method for differentiating smokes because smoke can only be perceived orthonasally.

MATERIALS AND METHODS

Experimental Overview

Attributes for nine different wood smokes were generated using a trained panel.

Following attribute generation, projective mapping was utilized to characterize differences and similarities among nine wood smokes. Subsequently, Cheddar cheeses smoked with four representative wood smokes were evaluated by a trained sensory panel. Sensory testing was conducted in compliance with the North Carolina State University (NCSU) Institutional Review

Board for Human Subjects Approval.

Projective Mapping

Sniff jars of wood smokes were created using a handheld food smoker (PolyScience

Smoking Gun© Handheld Food Smoker, PolyScience Culinary of Breville USA Inc., California,

USA) applied to filter paper in glass jars. Alder, apple, cedar, cherry, hickory, maple, mesquite, oak and pecan wood chips (Cameron’s Superfine Wood Chips, Cameron’s, Colorado Springs,

Colorado, USA) were used. Each respective wood smoke had its own tubing to prevent cross- contamination of aromatic compounds; tubing used was 0.63 cm natural latex tubing (Abbot

Rubber Company INC., IL, USA). Wood chips were weighed to 0.5 g increments. Sniff jars were created by exposing 12.5 cm strips of fluted filter paper (VWR Scientific Products, West

Chester, PA, USA) in 250 mL amber wide mouth jars (VWR International LLC, Radnor, PA,

USA) to 23 °C smoke for one min. The tubing attached to the handheld food smoker was inserted into the jar containing filter paper, and the lid was held slightly open so that the tubing could be inside and that smoke could clear out of the jar following exposure to filter paper.

Preliminary experiments were done to determine the smoking time needed for the highest intensity of aroma. Smoking for 1 min generated the strongest smoke aroma intensity. Smoking equipment was cleaned after each usage. Following sniff jar generation, the jars were stored at room temperature for 1 h prior to sensory analysis. Jars were only used for one panel and new jars were generated for each panel session.

A trained descriptive sensory panel (n=9, 6 females, 3 males, ages 23 to 47 y) evaluated the orthonasal aroma attributes of sniff jars with each wood smoke to generate smoke aroma attributes and to conduct the projective mapping. Each panelist had more than 300 h of previous experience with descriptive analysis of foods using the Spectrum™ method (Meilgard et al.,

2007). Supplementary training (approximately fifty 30 min sessions) was devoted to smoke aroma and identification of smoke aroma attributes. The smoke aroma lexicon generated by Jaffe et al. (2017) were used as a starting point, and additional attributes were added (Table 1). During the development and refinement of terms, panelists identified definitions and references for attributes. Twelve attributes were selected to characterize wood smoke aroma: ashy/charcoal, guaiacol/meaty, vanillin/marshmallow, sweet aromatic, smoky, plastic, woody/bark, fresh tobacco, resinous/terpene, fruity/cherry, spicy/cinnamon, and earthy/dirt.

Sniff jars were labeled with three-digit codes for projective mapping. Panelists placed the wood smokes on a two-dimensional map, based on similarities and differences. Products placed close together were perceived to be similar, and products placed further from each other were perceived to be different. Once a panelist placed a wood smoke on the map, they were asked to

41 use the identified 12 attributes to describe each wood smoke. The projective mapping exercise was replicated by each panelist in quadruplicate in separate sessions. An iPad interface was used and data was collected with a projective mapping application in Compusense Cloud (Guelph,

Canada).

Smoked Cheese

Smokes for Cheddar cheese smoking were selected based on differences determined by projective mapping. These smokes included mesquite, cherry, hickory, and cedar. Cheddar cheese (ca 30 days old) was obtained from a commercial supplier (Hilmar Cheese, Hilmar CA) in duplicate 10 kg blocks from two different lots. These blocks were similar (p>0.05) in moisture, fat, salt content and pH (Table 2). The cheese was cut into 2 cm3 cubes for smoking.

The handheld food smoker (Breville) described previously was applied to cheese in a cocktail smoking box (Fortessa Tableware Solutions, LLC., Virginia, USA) to cold smoke the cheese.

Preliminary experiments were conducted to determine the smoking time needed for the highest intensity of smoke aroma and flavor. Smoking cubes for 5 min generated the strongest smoke aroma and flavor intensity. Cheese cubes were placed equidistantly in the smoker box and were smoked for five min at 23°C. All cheeses were smoked in duplicate on the same day they were to be evaluated by sensory analysis. Following smoking, cheeses were placed into lidded cups 2 h prior to sensory analysis.

Descriptive Sensory Analysis

Sensory testing was conducted in compliance with the North Carolina State University

(NCSU) Institutional Review Board for Human Subjects approval. A trained descriptive sensory panel (n=7) evaluated the cheeses. Each panelist had prior experience with descriptive analysis

42 of Cheddar cheese flavor. Supplementary training (approximately four 30 min sessions) was devoted to smoked Cheddar cheese flavor attributes.

The Cheddar cheeses were placed into lidded 60 mL soufflé cups with random 3-digit codes. Sample preparation was conducted with overhead lights off to avoid any light oxidation of the samples. The cheeses were served at this temperature with room temperature deionized water and unsalted crackers for palate cleansing. At the beginning of each session, panelists were given a warm up sample of unsmoked Cheddar cheese. Panelists expectorated samples, and between samples, panelists rinsed with water and unsalted crackers. A 2 min rest was enforced between samples. Sample presentation was randomized to account for presentation and carryover effects.

Descriptive analysis was conducted using a 0- to 15-point universal intensity scale consistent with the Spectrum™ method (Meilgaard et al., 1999; Drake and Civille, 2003) and an established cheese flavor sensory language (Drake et al. 2001, 2005) with the added smoke lexicon terms.

Panelists evaluated the four cheeses in duplicate. Data was collected on paper ballots.

Statistical Analysis

Statistical analyses were conducted using XLStat (Version 2018.7, Addinsoft; Paris,

France). Projective Mapping data was analyzed by multiple factor analysis. Descriptor terms were then analyzed as a supplementary variable, and as such, they did not contribute to the MFA projections and were only used to further explain the MFA data. Descriptive analysis data were analyzed by analysis of variance (ANOVA) with Fisher’s least significant difference (LSD) post hoc test. All statistical analyses were performed at a 95% confidence interval.

RESULTS

Projective Mapping

Multiple Factor Analysis (MFA) explained 59% of the variability amongst the wood smokes on 3 Dimensions (Figure 1a). Dimensions 1 and 2 are displayed in Figure 1a which represented 25 and 19% of the total variance, respectively (44% total). Dimensions 1 and 3 (15% variability) are displayed in figure 2a. The supplementary variables (variables not used to calculate the coordinates of active variables, but used for interpreting results) are used as overlay for the MFA data and can be found in Figures 1b and 2b. Dimension 1 (25%) differentiated among smokes described by the terms smoky, ashy/charcoal, guaiacol/meaty, woody/bark, spicy/cinnamon, resinous/terpene, and plastic (Figure 1a and 1b). Dimension 2 (19%) differentiated among smokes described by the terms earthy/dirt, fruity/cherry, sweet, vanillin/marshmallow. Dimension 3 (15%) was comprised of fresh tobacco aroma.

The projective map of Dimensions 1 and 2 demonstrated four groupings that described the majority of similarities and differences among the wood smoke aromas. Table 3 shows the frequency of selection of attributes for projective mapping of smokes by panelists. The attributes selected were supplementary variables that were used to characterize the similarities and differences observed in the wood smokes. All smokes were frequently described to have ashy/charcoal and smoky aromas (Table 3). Cedar was perceived as most different from the other wood smokes, as this smoke was placed far on the left side of Dimension 1. The corresponding supplementary variables characterized cedar wood smoke to be distinguished by plastic, spicy/cinnamon, and resinous/terpene aromas. Apple and pecan were placed close together on the projective map, which indicates that they were perceived to be similar. Mesquite was also in the quadrant that apple and pecan were in, but not as close in proximity to these wood smokes.

Apple, pecan and mesquite smokes were characterized by earthy/dirt, fresh tobacco, woody/bark, and guaiacol/meaty aromas. Maple and hickory smokes were perceived to be similar, and cherry smoke was juxtaposed near these smokes as well. The attributes used to describe these smokes included sweet, fruity/cherry, and vanillin/marshmallow. Dimension 3 was used to strengthen the interpretation of the wood smoke aromas, specifically between mesquite and maple smokes.

Fresh tobacco aroma further differentiated mesquite smoke from apple and pecan, and maple smoke was further differentiated from hickory smoke by woody/bark and ashy/charcoal aromas.

Descriptive Sensory Analysis

Smoked cheeses were distinct in smoke-specific flavor attributes (Table 4). All of the smoked cheeses were similar in their intensities of whey and milkfat/lactone aromatics, and sour, salty, sweet and umami tastes; these similarities were expected since the same cheese source was used. Mesquite smoked cheese had the highest orthonasal smoke aroma, followed by hickory and cedar smokes, and then cherry smoke. Cooked/milky flavor was highest in cherry smoked cheese, followed by cedar, hickory, and mesquite smoked cheese. The highest intensity of resinous flavor was observed with cedar smoked cheese, followed by mesquite. Cherry and hickory smoked cheeses did not exhibit any resinous flavor. Campfire/marshmallow flavors were observed at the same intensity for cherry and hickory smoked cheese and were not observed in other wood smoked cheeses. The highest intensity of meaty flavor was observed with mesquite smoked cheese, followed by hickory smoke. Cherry and cedar smoked cheeses did not exhibit meaty flavor. The highest intensity of ashy flavor was documented with mesquite smoked cheese, followed by hickory, cedar, and cherry. The highest aftertaste smoke intensity was observed with cedar smoked cheese, followed by mesquite and hickory, and then cherry.

Commonalties were observed between the projective mapping of wood smokes and descriptive analysis of smoked cheeses, leading to the conclusion that specific aromas observed in specific wood smokes are also generally able to be observed in cheese smoked with the same woods. Mesquite smoked cheese presented high smoke aromas, which was consistent with the projective map exercise (Figure 1a and 1b). Cherry smoked cheese presented campfire/marshmallow flavor that was similar to the vanillin/marshmallow aromatics observed in the projective map of cherry wood smoke (Figure 1a and 1b). Hickory smoked cheese had smoke and campfire/marshmallow aromatics that were similar to the smoky and vanillin/marshmallow aromatics observed in the projective map of hickory wood smoke (Figure

1a and 1b). Cedar smoked cheese was strong in resinous and overall smoke flavor, which was consistent with the projective mapping data that demonstrated that Cedar smoke was distinct from the other wood smokes, partly due to its resinous/terpene aromas.

DISCUSSION

The high amount of variability (59%) explained by the multiple factor analysis indicated that much of the variation of the different wood smokes could be explained through projective mapping. The variability in each respective wood smoke is likely attributed to the wood smoke composition. The composition of each wood smoke depends on a variety of factors that can affect the aromatics observed; factors include the type of wood used for smoldering, the dryness of the wood, the composition of hemicelluloses, celluloses and lignin resins, as well as the temperature and access of air to the zone of oxidation of the volatile products (Sikoski and

Kolakowski, 2010). The relevant variables in this study were the type of wood used for smoldering and as a result of the different wood sources used, the composition of hemicelluloses, celluloses and lignin was variable as well. Wood sources can be classified into two main groups,

46 hardwoods and softwoods. Softwoods tend to have more lignin and more resin extractives, and the only softwood used in this study was cedar. Contrastingly, hardwoods have less lignin and are higher in syringol derivatives; the hardwoods used in this study were alder, oak, apple, pecan, mesquite, cherry, maple and hickory (Pallu, 1971; Maga, 1988; Maga, 1992). A notable differentiation that can be seen on the projective map is that cedar wood smoke, generated from soft wood, loaded far on Dimension 2. This could plausibly be attributed to the difference in wood type. Further research is required to determine the exact aroma compounds that comprise each respective wood source.

Descriptive analysis data was useful in interpreting how respective wood smokes impacted the aromas of smoked cheese. The similarity of the intensity of whey and milkfat/lactone aromatics and sour, salty, sweet and umami tastes indicated that the cold smoking of the cheeses impacted the cheeses in the same way, with minimal effects on the existing cheese flavors. Smoke aroma (orthonasal) and smoke descriptor terms meaty and ashy were highest with mesquite smoked cheese. Mesquite generally appeared to be the most intense wood smoke when applied to cold smoking of cheese. Contrastingly, cherry smoked cheese was lowest in smoke aroma (orthonasal) and smoke intensity aftertaste. Mesquite smoked cheese was lowest in cooked/milky aroma while cherry smoked cheese was highest in cooked/milky aroma.

This is an indicator that a higher intensity of smoke aroma and smoke-related flavors of a smoked cheese might decrease perception of cooked/milky flavor. Another potential relationship between wood smokes was that cherry and hickory smoked cheeses presented campfire/marshmallow aromatics and no resinous aromatics, while mesquite and cedar smoked cheese presented resinous flavors with no campfire/marshmallow aromatics.

The combination of the projective mapping and descriptive analysis data is the basis for confirming that different wood smokes produce different flavors that can be characterized in smoked cheese. Furthermore, the aromas produced by each wood smoke were generally constant through applications with smoked cheese. The attributes that were used to describe mesquite, hickory and cedar smoke alone were consistent with the descriptive analysis scaled intensities of mesquite, hickory and cedar-smoked cheese (Table 4). Cherry wood smoke consistent of sweet, fruity/cherry and vanillin/marshmallow aromatics, however, these aromatics did not translate strongly to the final smoked cheese product as the cherry wood smoked cheese only had notably strong aromatics of vanillin/marshmallow.

CONCLUSION

Smoke from different wood sources can be characterized by distinct aromas when analyzed through projective mapping of wood smokes and descriptive analysis of smoked cheese. The projective maps generated were a foundation for confirming that aromatic differences exist among wood smokes. Descriptive analysis of the distinct woods used to smoke cheese also confirmed that the wood smokes could be characterized by distinct aromas. Furthermore, the data from descriptive analysis indicated that distinct aromas from wood smokes can be similarly distinguished when using the wood to cold smoke cheese. The term ‘smoke’ is no longer sufficient to cover smoked food products, as this study shows that smoked food products retain a variety of aromas derived from different wood sources. Following this sensory characterization of specific wood smoke aromas and their contributions to smoked Cheddar cheese flavor, further research is needed to establish consumer preferences and perceptions of various wood smokes and smoked cheese.

ACKNOWLEDGEMENTS

Funding was provided in part by the National Dairy Council (Rosemont, IL), Dairy West

(Meridian, ID), and Hilmar Cheese (Hilmar, CA).

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Table 1. Orthonasal aroma attributes for projective mapping and descriptive analysis of wood smokes Terms Definition References Smoke Aromaa The overall aroma impact of smoke, an Tones Liquid Smoke aromatic that may present characteristics of sweet, brown, pungent, acrid, slightly ashy or charred/burnt

Resinous/Terpene Aromatics associated with terpenes Pine sap, pine bark, pine needles

Campfire Smoky, sweet smoke aromatics Charred wood burnt in a associated with a campfire fireplace

Guaiacol/Meaty Aromas associated with cooked meat Guaiacol, 5 ppm on filter paper in a sniff jar Ashy/Charcoala Dry, dusty, dirty smoke aromatics Gerkins Midnight Black associated with the residual of burnt (BL80) Cocoa Powder products Vanillin/Marshmallow Aromatics associated with vanilla extract Pure vanilla extract and artificial vanilla, cotton candy, marshmallows Sweet aromatic Aromatics associated with sweet foods Sweetened condensed that are not vanilla/vanillin milk, shredded coconut Plastic Aromatics associated with plastic Styrene, 0.02 ppm on filter paper in a sniff jar Woody/Barka The sweet, brown, musty dark aromatics Diamond Shelled associated with bark of a tree Walnuts Fresh Tobacco Aromatics associated with tobacco Skoal Chewing Tobacco Fruity Aromatics associated with different fruits Ethyl hexanoate, 20 ppm on filter paper in a sniff jar, RW Knudsen Cherry Juice Spicy/Cinnamon Aromatics associated with cinnamon McCormick Cinnamon bark Earthy/Dirta Somewhat sweet, heavy aromatics Miracle-Gro Potting Mix associated with decaying vegetation and Soil damp black soil aTerms were adapted from Jaffe et al. (2017)

Table 2. Proximate analysis means for duplicate 10 kg blocks of Cheddar cheese Analysis Average Moisture (%) 36.15 +/-0.26 Fat in Dry Matter (%) 53.70 +/-0.215

Salt (%) 1.84 +/-0.015 pH 5.17 +/-0.025

5 Mesquite 1 4 0.75 Earthy/Dirt 3 Fresh Tobacco 0.5 2 Alder Apple Plastic Cedar Pecan Woody/Bark Ashy/Charcoal 1 Oak 0.25 Spicy/Cinnamon Guiacol/Meaty 0 0 Resinous/Terpene Smoky -1 -0.25

Dimension Dimension 2 (19%) Maple -2 Dimension 2 (19%) -0.5 Sweet Fruity/Cherry -3 Hickory Vanillin/Marshmallo -0.75 -4 w Cherry -5 -1 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 Dimension 1 (25 %) Dimension 1 (25 %)

Figure 1a. Projective map of wood smoke aromas (Dimensions 1 and 2) Figure 1b. Projective map of supplemental variables used to describe smoke aromas (Dimensions 1 and 2)

5 1 4 Alder Maple 0.75 3 0.5 Spicy/Cinnamon 2 Apple Guiacol/Meaty Pecan 0.25 Resinous/Terpene Smoky 1 Fruity/Cherry Plastic Woody/BarkAshy/Charcoal 0 0 Cedar Hickory Sweet Earthy/Dirt

-1 -0.25 Vanillin/Marshmallow Dimension Dimension 3 (15%) Dimension %) 3 Dimension (15 Fresh Tobacco -2 Cherry -0.5 Oak Mesquite -3 -0.75

-4 -1 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 Dimension 1 (25 %) Dimension 1 (25 %) Figure 2a. Projective map of smoke aromas (Dimensions 1 and 3) Figure 2b. Projective map of supplemental variables used to describe smoke aromas (Dimensions 1 and 3)

Table 3. Frequency of selection of attributes for projective mapping of smokes by trained panelists Alder Apple Cedar Cherry Hickory Maple Mesquite Oak Pecan Ashy/ Charcoal 60%a 88%a 52%a 56%a 84%a 92%a 92%a 68%a 84%a Guiacol/Meaty 32%abc 24%abc 8%ab 4%a 56%c 32%abc 40%abc 16%abc 52%bc Vanillin/Marshmallow 12%a 12%a 12%a 52%a 28%a 32%a 12%a 36%a 20%a Sweet 32%a 24%a 48%a 72%a 32%a 32%a 24%a 24%a 32%a Smoky 64%ab 88%ab 52%a 68%ab 84%ab 96%b 88%ab 68%ab 84%ab Plastic 32%a 32%a 84%b 8%a 20%a 8%a 16%a 36%a 24%a Woody/Bark 60%a 76%a 32%a 32%a 64%a 64%a 64%a 72%a 64%a Fresh Tobacco 16%a 12%a 16%a 16%a 16%a 16%a 44%a 24%a 24%a Resinous/Terpene 40%a 36%a 56%a 28%a 28%a 36%a 16%a 52%a 32%a Fruity/ Cherry 20%ab 20%ab 12%a 64%b 4%a 20%ab 0%a 4%a 12%a Spicy/ Cinnamon 32%a 12%a 28%a 8%a 16%a 12%a 4%a 12%a 4%a Earthy/ Dirt 24%a 40%a 28%a 20%a 28%a 20%a 40%a 24%a 28%a

Table 4. Mean sensory attributes of smoked Cheddar cheeses Mesquite Cherry Hickory Cedar Smoke Smoke Smoke Smoke Smoke Aroma (Orthonasal) 4.0a 2.5c 3.3b 3.3b Cooked/Milky 2.0c 2.5a 2.0c 2.3b Whey 2.0a 2.0a 2.0a 2.0a Milkfat/Lactone 2.3a 2.3a 2.3a 2.3a Resinous 2.0b ND ND 2.5a Campfire/Marshmallow ND 2.0a 2.0a ND Meaty 2.6a ND 1.6b ND Ashy 2.8a 1.4b 1.8b 1.5b Sour 3.0a 3.0a 3.0a 3.0a Salty 3.5a 3.5a 3.5a 3.5a Sweet 2.0a 2.0a 2.0a 2.0a Umami 2.5a 2.5a 2.5a 2.5a Smoke Intensity Aftertaste 2.3a 2.0a 2.3a 2.3a Attributes were scored on a 0 to 15-point scale, with 0=not intense at all and 15=extremely intense, consistent with the SpectrumTM universal intensity scale (Meilgaard et al.,1999). Different letters in rows following means signify significant differences (p < 0.05) Attributes not listed were not detected. ND – not detected

CHAPTER 3: CONSUMER PERCEPTION OF SMOKED CHEDDAR CHEESE

Consumer Perception of Smoked Cheddar Cheese R. S. Del Toro-Gipson, P. V. Rizzo, D. J. Hanson, M. A. Drake*

Dept. Food, Bioprocessing and Nutrition Sciences, Southeast Dairy Foods Research Center, North Carolina State University, Raleigh, NC 27695

*Corresponding author: MaryAnne Drake Box 7624, Department of Food Science North Carolina State University Raleigh, NC 27695-7624 Phone: 9191-513-4598 Fax: 919-513-0014 Email: [email protected]

ABSTRACT The objective of this study was to evaluate consumer perceptions of smoked cheese through focus groups, surveys, and central location testing. Three focus groups (n=29) were conducted with consumers of smoked cheese. Subsequently, two online surveys were conducted.

The purpose of the first survey (n=1195) was to understand types of smoked cheeses consumed and if consumers associated specific wood smokes with smoked cheese. Next, an Adaptive

Choice-Based Conjoint (ACBC) (n=367) was designed to evaluate consumer perception of different attributes of smoked cheese. Maximum Difference scaling and familiarity questions were also included in the ACBC survey. Following the surveys, a central location test (n=135) was conducted with three cheeses smoked with different woods at a low and high intensity (six cheeses total). Hierarchical Bayesian (HB) estimation, one-way analysis of variance, agglomerative hierarchical clustering and two-way analysis of variance (smoke type x intensity level) was used to interpret the collected data. Results from the focus groups indicated that smoked cheese was perceived as an artisan, high-end product and that appearance and price were strong purchase factors. In general, consumers were not aware of how smoked flavor was imparted to cheese, but when informed of the processes, they preferred cold-smoked cheese to the addition of liquid smoke flavor. Results from both surveys confirmed focus group observations. Consumers perceived flavor differences among different wood smokes and smoked products. Method of smoking, smoke intensity, type of wood, and type of cheese were the most important attributes for purchase of smoked cheese. When tasting, consumers differentiated smoke aroma and flavor among cheeses and preferred cherry smoked cheeses over apple or hickory smoked cheeses. Understanding consumer perceptions of smoked cheese will give insight into the desired experience that consumers expect when purchasing smoked cheese.

Key Words: smoked cheese, focus groups, conjoint analysis, MaxDiff, consumer acceptance test

INTERPRETIVE SUMMARY

This study provides an understanding of consumer preferences and perceptions of smoked cheese that allows for an understanding of how to market and strategically position smoked cheese to satisfy consumers. The segmentation of smoked cheese consumers identifies a holistic view of different types of consumers and allows smoked cheese producers to better meet consumer expectations.

INTRODUCTION

Smoked food products have grown in popularity significantly, and more specifically, the smoked cheese market has grown as a specialty category of flavored cheese (Market Research

Future ®, 2019). With the growth of the smoked cheese market, there is a need to understand how consumers perceive different smoked cheese products, and what the drivers of liking are for product-specific attributes. Studies have attempted to characterize the sensory properties of smoked foods. There is an existing descriptive sensory language for smoked foods in general

(Jaffe et al., 2017) that contains terms such as smoky (overall), ashy, woody, musty/dusty, musty/earthy, burnt, acrid, pungent, petroleum-like, creosote/tar, cedar, bitter, metallic, and sour.

Additionally, a study was recently conducted in which pulled pork was prepared with two different types of smokers and four different types of woods, including hickory, apple, oak and mesquite (Swaney-Stueve et al., 2019). Pulled pork smoked with hickory wood had the highest overall liking and appearance characteristics, demonstrating consumer-perceived flavor differences due to specific wood smokes. In a more limited study, Rehman et al. (2003)

61 evaluated the effects of the application of natural hickory wood smoke on ripening of Cheddar cheese and determined the effects of smoking before or after ripening on cheese quality. Sensory properties and consumer perception have not been evaluated for smoked cheese smoked with different woods.

Focus groups are a qualitative research tool that involves 8-12 panelists and a moderator who encourages discussion amongst the panelists related to a specific topic (Drake, 2007). The moderator encourages discussion that follows a predetermined guide. Focus groups allow for a discussion with panelists that contains consumer focused language, as well as insight that may not be able to be collected through solely quantitative methods (Jervis and Drake, 2014). Focus groups have been used in sensory science for a variety of reasons, such as to characterize the consumer experience with products (Lee and Lee, 2007; Childs et al., 2008), understand consumer behavior (Boquin et al., 2014; Eaton et al., 2019), and to understand children’s food perceptions and preferences (Jervis et al., 2014).

Conjoint analysis is a technique used to measure consumer trade-offs through survey responses to preferences and intentions to buy (Green, 2004). In practice, conjoint analysis has the ability to uncover and quantify concealed attitudes that may not represent explicitly stated values, signifying that this tool is useful for gaining true information from consumers (Caruso et al., 2009). There are several well-established conjoint analysis methods, and one of the most commonly used methods is adaptive choice-based conjoint analysis (ACBC). ACBC involves a consider-then-choose model where respondents are shown a variety of product concepts, and their product choices are based on the responses they give. Following selection of products, respondents then participate in choosing products from a series of product concepts (Jervis et al.,

2012). Desirable product concepts and specific attributes of a product that are most appealing are the outcomes.

Maximum differential scaling (MaxDiff) or ‘Best Worst Scaling’ is another survey question afterward that is used to understand how respondents place importance on a single product issue or attribute. In best worst scaling, a respondent chooses one item that they think is best or most ‘attribute’ and one that is the worst or least ‘attribute’ from a series of sets that contain different combinations of a larger master set of items (Lee et al., 2007). The basis for using best worst scaling is that there are many methodologies to measure consumer values, and they all conclude that an individual’s values have a large impact on his or her beliefs, attitudes, behavior and preferences (Corfman, et al., 1991; Schwartz and Bardi, 2001). MaxDiff scaling has been used to evaluate consumer preferences for a variety of food products, including ground beef (Lusk and Parker, 2009; Chrysochou, 2014), olive oil (Dekhili et al., 2011), bacon (McLean et al., 2017), and dark chocolate (Thomson et al., 2010).

The combination of a variety of quantitative and qualitative consumer acceptance methodology allows for a complete understanding of consumer perceptions and preferences for smoked cheese products. The objective of this study was to evaluate the sensory properties and consumer perceptions of smoked cheese through focus groups, surveys and central location testing. Focus groups were conducted with self-identified consumers of smoked cheese. An online survey was conducted to generate demographic information and general information about smoked food consumption, and an adaptive choice-based conjoint was conducted to evaluate consumer trade-offs and smoked cheese attribute preferences. A central location test was then conducted to evaluate consumer acceptance of smoked cheese and the ability of consumers to differentiate between smoked cheeses of different intensities and smoke types.

MATERIALS AND METHODS Focus Groups

Three 90 min focus groups were conducted to understand consumer perception of smoked cheese. Self-reported frequent (at least once a month) consumers (n=29) (29% males,

71% females; 18-64 y, approximately n=10 per group) of smoked cheese participated. All subjects were recruited from an online database of more than 10,000 consumers in the

Raleigh/Durham, NC area maintained by the Sensory Service Center at North Carolina State

University. A moderator facilitated discussion through the use of a planned moderator guide

(Figure 1). Focus groups were audio and video recorded for subsequent reference. A note taker observed the focus groups through a webcam in an adjacent room and took notes of key points mentioned by participants. Panelists were compensated with a gift card to a local store for their participation.

General Survey

An online survey was developed using Lighthouse Studio (Sawtooth Software version

9.53., Orem, UT). The survey was uploaded to a database of over 10,000 consumers, maintained by the North Carolina State University Sensory Service Center. The purpose of the survey was to quantify the findings of focus groups and to gather general data about smoked food product consumption. Survey participants (n=1195) were 18 years of age or older, and were self- identified consumers of smoked foods. Participants were then given a list of smoked foods including cheese, meat, fish, beverages, and other (Table 1). Depending on the selection made from this list, participants were then asked if they consumed more specific products within each category. For each product selected, panelists were asked which of the list of wood smokes they liked best with the selected product. The list of wood smokes included: alder, apple, cedar, cherry, hickory, mesquite, maple, oak, pecan, other, and unsure/I do not know. Consumers were

64 also asked if they had a favorite wood smoke, if there were any smoked cheese products that they consumed that were not mentioned in the survey or if they were interested in trying smoked cheeses that they have not previously tried, and if they would like to comment on anything else pertinent to smoked food. After completion of the survey, participants were entered into a drawing to receive a gift card to a local shopping store.

Smoked Cheese Survey

An online survey was developed using Lighthouse Studio (Sawtooth Software). The survey was uploaded to the same database used in the general survey, maintained by the North

Carolina State University Sensory Service Center. Participants from the first survey were not specifically recruited, as the goal was to recruit specifically smoked cheese consumers. A 3- month waiting period occurred between the first survey and the second survey to discourage learned behavior. The purpose of the survey was to further quantify the findings of the focus groups and to determine decision-making processes that influence the purchase of smoked cheese. The use of the same software for both surveys removed any software bias. Survey participants (n= 367) were 18 years of age or older, and were self-identified consumers of smoked cheese. The survey consisted of a conjoint analysis exercise, an importance question exercise, and a MaxDiff exercise as well. After completion of the survey, participants were entered into a drawing to receive a gift card to a local shopping store.

For the conjoint analysis, seven attributes (smoke intensity, smoking method, type of cheese, type of smoke, location of cheese in the grocery store, appearance of smoked cheese, and specific label) were selected with different levels within each attribute (Table 2). These attributes were chosen based on representation of characteristics observed with smoked cheese products from the focus groups and the general smoked foods survey. The ACBC was designed with a

‘Build-Your-Own’ task, then eight screening tasks with four product concepts per task with the possible responses of “a possibility” or “won’t work for me” for each product concept. Four

‘must have’ questions and five ‘unacceptable’ questions were included in the survey. Following the screening tasks, ten question choice tasks were included in a tournament section. A maximum of 20 product concepts were brought into the Choice Tournament section, and there were three concepts per choice task. Following the ACBC task, consumers were asked a series of importance questions asking about the importance of various smoked cheese attributes using a 5- point scale that ranges from 1 (“Not Important at All”) to 5 (“Very Important”).

The final section of the ACBC survey included a MaxDiff exercise. The best-worst scaling task was designed so that participants had to select the ‘Least Important’ and ‘Most

Important’ attributes for 10 sets of best-worst questions with 5 product attributes per set. The attributes included in the exercise were appearance/color of cheese, packaging and labels, price, brand, smoke intensity, organic label, natural label, use of liquid smoke, use of natural wood smoke, type of smoke/wood source (Ex. Mesquite, Hickory), and type of cheese (ex. Mozzarella,

Gouda, Cheddar). Respondents were asked, “Please consider how important different features are when selecting a smoked cheese to purchase. Considering only these 5 features, which is the

Most Important and which is the Least Important?” The attributes were presented to each participant in a randomized design.

Descriptive Analysis

Six smoked Cheddar cheeses were manufactured in duplicate by Hilmar Cheese

Company (Hilmar, CA, U.S.A) via exposing cheese curds to natural wood smoke (McLeod,

2017). The cheeses tested were apple smoked at low intensity, apple smoked at high intensity, cherry smoked at low intensity, cherry smoked at high intensity, hickory smoked at low

66 intensity, and hickory smoked at high intensity. All cheeses were 2 mo old on receipt and evaluation. Sensory properties of smoked cheese were documented by descriptive sensory analysis. Panelists expectorated samples and cleansed palates with room temperature deionized water between samples. Data was collected using Compusense Cloud (Compusense, Guelph,

Canada). A trained sensory panel (n=6, 3 females, 3 males, ages 23-54 y) evaluated the flavor properties of the smoked Cheddar cheeses and an unsmoked, control Cheddar cheese using an established Cheddar cheese flavor lexicon (Drake et al., 2001) with specific smoke terms added

(Del Toro-Gipson et al., 2019) and a 0 to 15 universal intensity scale consistent with the

Spectrum MethodTM (Lawless and Heymann, 2010). Each panelist had at least 150 h of experience with descriptive analysis of cheese flavors. Smoked Cheddar cheese (2 cm3) was served in lidded 60 mL clear plastic soufflé cups (Dar Container, Mason, MI) with random three- digit blinding codes and evaluated at 15 °C. Each panelist evaluated each cheese in duplicate.

Central Location Testing

Descriptive analysis confirmed distinct smoke-specific flavor profiles of the cheeses and different overall smoke flavor intensities within each smoke type. A target number of n=135 smoked cheese consumers were recruited from a database of more than 10,000 consumers maintained by the North Carolina State University Sensory Service Center (Raleigh, N.C.,

U.S.A). Consumers were recruited via Compusense Cloud (Compusense, Guelph, Canada).

There were 29% males and 71% females with an even age distribution (18-54 y). Self-reported smoked cheese consumers were people who purchased and consumed Cheddar cheese and smoked cheese at least once every month. Consumer acceptance testing took place over two days, and consumers who participated were compensated with a $20 Amazon gift card.

Samples were cut into 2 cm3 blocks and placed into 60 mL soufflé cups with a 3-digit blinding code. Data was collected using Compusense Cloud (Compusense, Guelph, Canada).

Participants signed a consent form followed by a ballot consisting of questions about smoked cheese samples. Consumers were asked to evaluate overall liking, smoke aroma intensity, and a variety of appearance and flavor attributes. Sample orders were randomized, balanced, and pre- assigned to each consumer before the test started, and each consumer evaluated 3 cheese samples each day.

As consumers arrived for their test, they were provided an iPad loaded with Compusense

Cloud and were then verbally instructed as well. Consumers were first asked to evaluate the appearance and color of each sample. The overall appearance and color liking was scaled using a

9-point hedonic scale, where 1= dislike extremely and 9=like extremely, followed by just-about- right (JAR) questions about the color, where 1 and 2= too light, 3= just about right, and 4 and 5= too dark. Following this, consumers were asked to evaluate the aroma and smoke intensity of the sample using a 9-point Hedonic and JAR scale for aroma. Consumers were then asked to evaluate the overall liking, overall flavor liking, smoky flavor liking, and smoke flavor intensity using a 9-point hedonic scale. These questions were followed by just-about-right (JAR) questions for overall flavor, smokiness, and smoke to cheese flavor balance. Consumers were then asked to select from a list of attributes to describe the smoked cheese sample; the list of attributes consisted of: earthy, dirt, fresh tobacco, woody, ashy, charcoal, meaty, smoky, fruity, cherry, vanilla, sweet, plastic, spicy, marshmallow, campfire, cinnamon, milky, buttery, salty, sharp, mild and the option of an ‘other’ with a comment box to clarify this section. Following this exercise, consumers answered a 5-point purchase intent question where 1 or 2= would not buy, 3= might or might not buy, and 4 or 5= probably would buy.

Between samples, consumers were instructed to cleanse their palate by rinsing with deionized water and taking a bite of unsalted cracker during an enforced 3 min rest period between each sample. Once consumers finished all samples, they were asked a set of demographic questions to better define their experience with smoked cheeses and foods.

Consumers were asked to select from a list which attributes influenced their selection of smoked cheese; the list included: appearance/color of cheese, packaging and labels, price, brand, smoke intensity, organic label, natural label, use of liquid smoke, use of natural wood smoke, type of smoke/wood source, type of cheese, and other (with a specification area). Consumers were asked how they used/consumed smoked cheese, and they could select from a list including: eat it straight, cold (added to compliment food like a condiment ex. salads, sandwiches), cold (as an ingredient ex. dips, salads), cold (as an appetizer or part of a cheese tray, hot (added to compliment food like a condiment ex. tacos, eggs, vegetables, burgers, fries, chili), hot (as an ingredient ex pizza, casserole, mac and cheese, quiche, sauces, nachos), and other (with a specification area). Consumers were then asked to select from a list and rank their top 4 choices of smoked cheese and the list included: Brie, Gouda, Cheddar, Mozzarella, Provolone, Ricotta,

Gruyere, and other (with a specification area). Following this, consumers were then asked to select from a list and rank their top 4 choices of the types of wood smoke they were familiar with for smoked cheese, and the list included: apple, alder, cherry, cedar, hickory, maple, mesquite, oak, pecan and other (with a specification area).

Statistical Analysis

Focus group data was analyzed by the frequency of responses and used to generate a journey map with key learnings and consumer perceptions. Individual utility scores from the conjoint survey and MaxDiff scores were determined through Hierarchical Bayesian (HB)

69 estimation (Sawtooth Software Lighthouse Studio, Orem, UT). Utility scores and importance scores were compared through one-way analysis of variance with Fisher’s least significant difference (95% confidence). Consumer segmentation was examined by cluster analysis through agglomerative hierarchical clustering to generate three clusters, and then k-means clustering was used to characterize the clusters via XLSTAT version 19.5.2018 (Addinsoft, Paris, France) with

Euclidean distances and Wards linkage to categorize similar respondents into groups. Consumer liking scores were analyzed by a two-way analysis of variance (ANOVA) for smoke type x intensity with Fisher’s least significant difference test at a significance level of p<0.05.

Consumer liking scores were also used for segmentation via cluster analysis. Consumer JAR scores were evaluated by chi-squared analysis, and purchase intent was evaluated using a

Kruskal-Wallis test with Dunn’s post hoc test. Check-all-that-apply questions were analyzed with a k-proportions test.

RESULTS Focus Groups

Panelists primarily demonstrated awareness of smoked gouda, followed by Cheddar, mozzarella, provolone and muenster cheeses. Panelists were generally unaware of different wood smokes related to cheese but could name different wood smokes within the context of meat and fish. Major purchase factors included flavor, for use in recipes, and for special occasions.

Panelists specifically said that they would purchase smoked cheese for special occasions like holiday parties or dinner parties because it elevated the experience. Panelists generally considered smoked cheese to be a high-end item, but there was some debate as to if smoked cheese was ‘artisan’. Factors that influenced purchasing included price, brand, availability, and simplicity of the smoked cheese packaging. Panelists were generally unable to think of brands of smoked cheese and could not identify a ‘gold standard’ brand for smoked cheese.

The discussion related to smoked cheese processing began with panelists considering how meat is smoked; following this, they were asked to consider how cheese is smoked. There was a general lack of knowledge about the process of smoking cheese, however, panelists were able to deduce that cheese could melt with the addition of high heat, and acknowledge that this would be an important consideration in cheese smoking. After much discussion, panelists were given definitions that described cold smoking and the addition of liquid smoke to cheese.

General perceptions of cold smoking were that it was the favorable method for smoking cheese and that it appeared to be a more natural and ‘fancier’ process because of the work that the process required. General perception of liquid smoke was that it seemed like a cheaper process than cold smoking, that the liquid smoke seemed like a chemical additive, and that though it might be more consistent in production, it was less artisanal overall. A major distinction between

71 consumer perception of cold smoke and liquid smoke addition was that cold smoking produced smoked cheese and that the addition of liquid smoke produced smoke flavored cheese. However, when the trade-off between price and smoking method was presented to consumers, consumers generally agreed that they would prefer cold smoked cheese if it cost less or the same as cheese with added liquid smoke, but if it cost more it might not be desired.

Smoked cheese flavors that panelists were looking for included savory and toasted notes, with low sweetness. When texture was considered, panelists wanted smoked cheese to be somewhat soft and creamy, but not to deviate too far from the original texture of the unsmoked cheese. When appearance was considered, most panelists said that they would want a smoked cheese with a brownish/yellow appearance to indicate that it went through the smoking process.

When asked how smoked cheese was consumed, there was a mix of consumers who said they used it in recipes and consumers who said they consumed it alone. Panelists cared about different wood smokes in the scope of how it affected their pairings with other foods and wines.

General Survey

Of the surveyed participants (n=1195), 91.5% said they consumed smoked meat, 66.9% said they consumed smoked cheese, 49.4% consumed smoked fish, 19.3% consumed smoked beverages, and 2.34% consumed ‘other’ smoked products. Table 3 shows the complete list of selection frequency of product and smoke combinations from the survey.

Conjoint Analysis

No respondents had an RLH value below 0.333, so all data was used in the analysis.

Utility scores (zero-centered) are derived from hierarchical Bayesian estimation analysis and higher scores are representative of more appealing levels within an attribute (Orme, 2010). The

72 average utility estimations indicated that the ideal smoked cheese for the surveyed consumers

(n=367) was a medium intensity smoked cheese, with smoke generated from wood chips, Gouda,

Hickory wood smoked cheese, purchased at the cheese counter, with a brownish/yellow smoke color exterior, and an all-natural label claim (Figure 2). Importance scores with higher scores indicate higher importance of an attribute for consumers, as opposed to lower scores which represent a less important attribute (Orme, 2010). Consumers regarded smoking method as the most important factor, followed by smoke intensity, type of smoke, type of cheese, location of smoked cheese in the grocery store, specific label, and appearance of smoked cheese (Figure 3).

Three consumer clusters were identified based on individual importance scores; a typical consumer cluster (n=86), an all natural cluster (n=118), and a connoisseur cluster (n=163) (Table

4, Figure 3). Additional analysis of the mean utility scores was conducted according to the importance score clusters, and similar findings were reported (Figure 4). Demographic information (gender, age, ethnicity, marital status, education, employment, income) was distinct among some ACBC clusters (p<0.05) (data not shown). ACBC typical consumer cluster was significantly lower in population of Black/African American ethnicity, and higher in students.

The all natural cluster was significantly lower in the engaged population and higher in the married and 5-6 people/household population. The connoisseur cluster was significantly lower in population of people ages 55-64 y. Additionally, when asked about factors that influenced purchase, the typical consumer cluster was significantly high in smoke intensity as a purchase factor and ACBC all natural cluster was significantly high in the use of natural wood smoke as a factor for purchase.

The ACBC typical consumer cluster (n=86) placed high importance on the smoke intensity of smoked cheese. Within the attributes of smoke intensity, the ACBC typical consumer

73 cluster was generally most interested in a medium or low intensity cheese, and placed low utility on high smoke intensity cheese. The ACBC all natural cluster (n=118) placed high importance on the smoking method used for smoked cheese. In the attribute of smoking method, all segments placed higher utility on smoke generated from wood chips, but the ACBC all natural cluster placed the highest utility on smoke generated from wood chips. Additionally, the all natural cluster placed the highest utility on an ‘All Natural’ label claim. The ACBC connoisseur cluster placed a high importance on the type of cheese, type of smoke used for smoking cheese, the location of the smoked cheese in the grocery store, the appearance of smoked cheese, and the specific label for the smoked cheese. Within the attributes of type of cheese, the ACBC connoisseur cluster placed the highest utilities on Gouda and Cheddar cheese. Table 5 contains the importance scores for smoked cheese attributes from the conjoint survey. Consumers from the ACBC typical consumer cluster gave the highest importance score to type of cheese and smoke intensity. Consumers from the ACBC all natural cluster gave the highest importance score to the use of natural wood smoke. Consumers from the ACBC connoisseur cluster gave the highest importance score to the type of cheese. Additionally, consumers from the ACBC connoisseur cluster rated price and brand higher in importance than the other clusters.

MaxDiff

MaxDiff scores for all consumers and clusters can be found in Table 6. The attributes that were considered to be most appealing by the consumers were type of cheese, price, and type of smoke/wood source. These attributes were consistent with the conjoint results. The attributes considered least appealing by consumers were brand, packaging and labels, presence of a natural label, and presence of an organic label. In all consumer segments, type of cheese was considered the most appealing attribute. In the typical consumer cluster, the attribute considered most

74 appealing after the type of cheese was the smoke intensity, which was consistent with the conjoint results. In the all natural cluster, the attribute considered most appealing after the type of cheese was the use of natural wood smoke, which was also consistent with conjoint results. In the connoisseur cluster, the attribute considered most appealing after the type of cheese was the price.

Descriptive Analysis of Smoked Cheese

Smoked cheeses were differentiated by descriptive analysis (Table 7). Principal component (analysis) explained 68% of the variability on 2 PC’s (Figure 5). Principal component

1 (41%) was comprised of overall aroma, smoke aroma, cooked/milky, whey, milkfat/lactone, campfire/marshmallow, meaty/smoky, ashy, overall smoke flavor intensity and salty and sweet tastes. Principal component 2 (27%) was comprised of fruity, waxy/green and phenolic flavors and sour and umami tastes. The low intensity Apple, Cherry, and Hickory smoked Cheddar cheeses were characterized by cooked/milky, waxy green, whey, and milkfat/lactone aromatics and sweet tastes. The high intensity Apple smoked Cheddar cheese was characterized by fruity, and campfire/marshmallow aromatics and sour tastes. The high intensity Apple and Hickory smoked Cheddar cheese was characterized by high overall aroma and smoke aroma, meaty/smoky and ashy aromatics.

Central Location Testing of Smoked Cheese

Smoked cheese consumer purchase and consumption habits were consistent with results from the online survey (results not shown). Consumers were asked to rank the importance of factors that influenced their purchase of smoked cheese. The top influencing factor was flavor, followed by price and availability. Consumers reported that of the types of smoked cheese they

75 purchased, most frequently purchased was Cheddar, followed by Gouda and Mozzarella. Of the recruited panelists, 79.3% reported that they preferred medium smoke intensity smoked cheeses.

Of all the cheeses evaluated, overall appearance liking scored at parity (Table 8). Color liking of the samples was highest for high intensity Cherry and lowest for low intensity Hickory, however, the color JAR scores were not different among the cheeses. Aroma liking was highest for high intensity Hickory and lowest for high intensity Apple. Perceived smoke aroma intensity was highest for high intensity Hickory, and lowest for low intensity Cherry.

Low intensity Cherry smoked Cheddar cheese received the highest overall liking score, as well as the highest overall flavor liking and smoky flavor liking. Additionally, low intensity

Cherry smoked cheeses had the lowest perceived smoke flavor intensity. High intensity Cherry and low intensity Apple smoked Cheddar cheeses were the next most liked smoked cheeses.

Following this, the high intensity Apple, the low intensity Hickory and the high intensity

Hickory smoked Cheddar cheeses were the next preferred, with no significant differences in overall liking. Smoky flavor liking and smoke flavor intensity was at parity for all of these samples, with the exception of low intensity Hickory that had a lower smoke flavor intensity.

Purchase intent was at parity for all cheeses. Consumers were given the option to select from a list of attributes the attributes that they detected in the smoked cheese product. Overall, there were no significant differences between terms selected for each of the cheeses. The most frequently selected attributes were smoky, woody, and campfire (Table 8).

A two-way ANOVA was conducted that examined the effect of smoke type and intensity on all liking scores in the consumer acceptance test (Table 9). There was a statistically significant interaction between the effects of smoke type and smoke intensity for the perceived smoke aroma intensity (F (2, 804) = 4.428, p=0.012) and for smoke flavor intensity (F(2, 804) =

11.201, p=<0.0001). In general, consumers perceived larger differences in smoke aroma and flavor between the high and low Cherry and Hickory wood smoked cheeses compared to the apple wood smoked cheeses, consistent with trained panelists. Smoke type effects (p<0.05) were noted for overall liking and flavor liking (Overall liking=6.7a, 6.4ab, and 6.2b for Cherry, Apple and Hickory, respectively and flavor liking= 6.6a, 6.3b, and 6.2b for Cherry, Apple, and

Hickory, respectively).

Demographic information was asked at the end of the test. Consumers reported that the top attributes influencing their selection of smoked cheese were appearance/color of cheese, type of cheese, and smoke intensity. Consumers reported that they most used and consumed smoked cheese alone, cold as an appetizer or part of a cheese tray, and hot added to compliment food like a condiment. Consumers were most familiar with Cheddar, Gouda, and Provolone smoked cheese, and their top three rankings of smoked cheese were Cheddar, Gouda, and Mozzarella.

The types of wood smoke that consumers were familiar with for smoked cheese was Hickory,

Mesquite and Apple, and their top three rankings of wood smokes followed this order.

Cluster analysis was conducted with the consumer liking data (Figure 6). Patterns in the

CLT cluster consumer liking were consistent with the consumer cluster attributes identified from conjoint importance scores. The CLT typical consumer cluster (n=71) showed significant differences among cheeses only in smoke aroma intensity and smoke flavor intensity. The CLT all natural cluster (n=29) was the only cluster to show significant differences in overall appearance liking. The CLT connoisseur cluster (n=35) showed significant differences in aroma liking, smoke aroma intensity, overall liking, overall flavor liking, smoky flavor liking, and smoke flavor intensity.

DISCUSSION Focus Groups

The lack of consumer familiarity with smoked cheese indicates that consumers may choose smoked cheeses based on their past experiences with the unsmoked version of these cheeses. Panelists were able to conceptualize many types of wood and smoked meats or fish that they had consumed, but were unable to make those same connections with smoked cheeses.

Consumers commented that they believed smoked cheese to be a ‘high-end’ item but not necessarily artisan. This is likely due to the contrasting methods of manufacture of smoked cheese. When consumers consider smoked cheese that had been cold smoked, they were more likely to consider it high-end and artisan. However, when consumers considered smoked cheese that was created via the addition of liquid smoke, they still considered it ‘high-end’ due to it being a specialty cheese, but they were less likely to consider this type of product artisan.

When prompted with definitions explaining the two methods of smoking cheese, addition of liquid smoke and cold smoking, consumers almost immediately perceived liquid smoke to be a lesser method of smoking, due to its ‘artificial’ nature. This perception is an interesting contrast to the older study conducted by Mcilveen and Vallely (1996) which found that consumers of processed, smoked cheese preferred cheese flavored with smoke flavoring as opposed to cold smoked cheese. It leads to the idea that consumers may have differing views about the flavor of smoked cheese and the method used to produce the final smoked cheese, or that consumer perceptions and beliefs have changed in the past 20 years. They may prefer the liquid smoked flavored cheese when blindly tasting the product, but with the addition of information about how the product was produced they have adverse opinions about the addition of liquid smoke. The discussion related to flavor and appearance characteristics of smoked cheese revealed that

78 despite consumers purchasing smoked cheeses with the type of cheese they are most familiar with (i.e. Gouda, Cheddar, etc.), they still want the smoked cheese product to be a specialty experience. Consumers expressed an interest to learn more about how to use smoked cheese in food and wine pairings, as well as to learn about more ways to use smoked cheese as an ingredient. Consumer interest provides an opportunity for producers of smoked cheese to promote different ideas and situational uses for smoked cheeses.

Surveys

The data obtained from the general survey showed that consumers could conceptually differentiate between different woods with different products. This information guided the development of the conjoint survey in that it allowed questions to be designed with different levels, such as type of wood smoke and smoke intensity. Data from the conjoint analysis survey was reflective of the general survey; consumers most preferred smoked Gouda cheese followed by Cheddar and they most preferred Hickory wood smoke.

The identified consumer clusters from the individual importance scores showed similar trends across all analyses. The ACBC typical consumer cluster was truly only concerned with the aspect of smoke intensity, while the ACBC all natural cluster was only concerned with smoking method which reflects focus group sentiments about preference for cold smoking over the addition of liquid smoke. The analysis of the importance scores further confirmed these findings.

The ACBC typical consumer cluster placed a high importance on smoke intensity, the ACBC all natural cluster was concerned most with the use of natural wood smoke, and the ACBC connoisseur cluster was most concerned with the type of cheese. General themes identified from the importance scores were that consumers cared most about the type of cheese and least about the importance of brand, which reflects the focus group data and the notion that there is no

79 identified ‘gold standard’ brand of smoked cheese. The MaxDiff scores also reflected these same ideals. For all consumers surveyed, the type of cheese had the highest score, and the brand had the lowest score. When MaxDiff data was analyzed by cluster, all ACBC clusters gave the highest score to the type of cheese; however, the second highest score was smoke intensity for the ACBC typical consumer cluster, use of natural smoke for the ACBC all natural cluster, and price for the ACBC connoisseur cluster. Past research conducted with dairy products (Jervis et al., 2012; Kim et al., 2013) indicated that intrinsic cues, such as sensory attributes, drive purchase intent more than extrinsic cues, such as brand name or packaging labels, specifically when consumers have the opportunity to taste the product. Price was an extrinsic attribute that also scored within the top factors of importance for all consumer clusters. However, the ‘high- end’ perception consumers have of smoked cheese indicates that smoked cheese is not an item that most consumers would purchase on a regular basis and instead more for special occasions.

Due to these perceptions, it is likely that price is of less concern to most consumers and that though cost is an important factor for purchase, consumers are more focused on the experience they have when consuming smoked cheese.

Descriptive Analysis and Consumer Acceptance Testing

The principal component analysis generated from the descriptive analysis data placed all of the low intensity smoked Cheddar cheeses on the left side of the axis and all of the high intensity smoked Cheddar cheeses placed on the right side of the axis. The low intensity smoked

Cheddar cheeses were terms used to describe unsmoked Cheddar cheese; cooked, whey, milkfat/lactone, sweet, and umami (Drake et al., 2001). This result confirms that the lower intensity version of the smoked Cheddar cheeses maintained many of the same aromatics that an unsmoked cheese would. With the addition of longer smoking duration, the high intensity

80 smoked cheeses developed distinct aromatics specific to specific wood smokes. Del Toro-Gipson et al. (2019) recently demonstrated that trained panelists could distinguish specific wood smoke aromas alone in sniff jars and when applied to Cheddar cheeses, similar to results in this study.

Trained panelists documented differences in the smoke aroma and flavor among the high and low intensity smoked cheeses for each wood type, but they also documented specific flavors and intensities unique to each wood type. Cherry, apple and hickory wood smoke imparted distinct flavors to the cheeses.

The highest overall liking score for the smoked Cheddar cheeses was for the low intensity

Cherry smoked Cheddar cheese which had the lowest overall smoke flavor intensity by trained panel profiling. The lowest overall liking score was for high intensity Hickory smoked Cheddar cheese which had the highest overall smoke flavor intensity. These results indicate that consumers were able to perceive differences among smoked cheeses, and that liking of smoked

Cheddar cheeses changed with the smoke intensity and smoke source. The differences in overall liking further corroborate the research by Del Toro-Gipson et al. (2019) that aromas from different wood smokes are different and can be characterized, even by untrained consumers. A recent study conducted by Swaney-Stueve (2019) also reported consumer preferences for pulled pork smoked with different wood smokes. Pulled pork smoked with hickory wood had the highest overall liking and appearance characteristics, indicating that wood smoke preferences may change for consumers when they taste different foods smoked with the same wood source.

Additionally, the results of the consumer acceptance test directly contrast the results of the conjoint analysis, in which the consumers placed the highest utility on hickory smoke and the lowest utility on cherry smoke in the smoke type attribute (Figure 2). A likely reasoning for this stark contrast is that consumers are most familiar with smoked foods in the context of meat, and

81 hickory smoked meat is a popular option as seen by the results of the smoked foods survey

(Table 3). Cherry smoked meat was less popular amongst consumers in the smoked foods survey. When asked to consider their ideal product build for smoked cheese, past experiences and familiarity may dictate consumer choices. As a result, producers of smoked cheese may benefit from producing a variety of products with different branding and packaging types, in order to allow consumers to develop expectations about the variety and types of smoked cheese available. Producers of smoked cheese may also want to utilize appearance and marketing factors to entice consumers to choose products that they know they will enjoy.

The cluster analysis of the CLT consumers generated consumer segments that were consistent with the clusters identified from the individual importance scores generated by the conjoint analysis. The only significant differences in liking scores for the CLT typical consumers were in smoke aroma intensity and smoke flavor intensity, which follows the ACBC typical consumer cluster, which solely placed importance on the smoke intensity of smoked cheese. The

CLT all natural cluster was the only consumer cluster to show differences in overall appearance liking. This cluster attribute indicates that the cluster was focused on the appearance of the smoked cheese, which may serve as an indication to these consumers of how ‘natural’ the smoked cheese is. A brownish smoked cheese indicates that it was naturally cold smoked, which is an attractive and important attribute for both this CLT cluster and the ACBC all natural cluster. The CLT connoisseur cluster followed similar behavior to the ACBC connoisseur cluster, in which they were concerned with a variety of attributes of smoked cheese, including type of cheese, type of smoke, location of smoked cheese in the grocery store, appearance of smoked cheese, and specific label.

CONCLUSION Smoked cheese is a somewhat unrefined concept for consumers. Consumers can conceptually perceive differences between different wood smokes and products with different wood smokes. Additionally, consumers have preferences for the type of smoked cheese they consume and preferences for the wood source used. However, consumers are generally unaware of the process to manufacture smoked cheese. Consumer purchase habits reflect a desire for flavor and experience alone without a strong interest in specific brands or a specific ‘ideal’ smoked cheese. Identified consumer clusters were documented from consumer preferences with actual cheese tasting and from conjoint analysis, and the consistency of these results between

ACBC and CLT clusters indicates that these clusters are true representations of the actual smoked cheese consumers and their preferences and desires. Producers of smoked cheese have the opportunity to further educate consumers via packaging, marketing, and recipe knowledge.

Additionally, with a focus on transparency in the food industry, consumers would benefit from learning more about smoked cheese so that they feel informed when making purchasing decisions.

ACKNOWLEDGMENTS Funding was provided in part by the National Dairy Council (Rosemont, IL), Dairy West

(Meridian, ID), and Hilmar Cheese (Hilmar, CA).

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Table 1. Product options in the general survey (Survey 1) Product Specifics Wood Smokes Brie Gouda Cheddar Mozzarella Cheeses -Alder Provolone -Apple Ricotta -Cedar Gruyere -Cherry Other -Hickory Ham -Mesquite Meat Sausage -Maple Bacon -Oak Salmon -Pecan Fish Trout -Other Beer -‘Unsure/I don’t know’ Beverage Coffee Cocktails Other (Please Specify)

Introduction a. Moderator: Focus Group guidelines and purpose. b. Participant Introductions

II. Focus Area 1: Smoked Cheese General a. When you eat smoked cheese, what types of cheeses do you eat? (Mozzarella, cheddar, etc) b. What types of woods are used to smoke the cheeses you like? i. Cherry ii. Apple iii. Hickory iv. Maple v. Etc. c. Do you have a favorite wood smoke? Why? d. What does the wood smoke contribute to the final smoked cheese product? i. Are there noticeable differences in flavor when one wood is used over another? ii. Do you seek out specific woods? Why or why not?

III. Focus Area 2: Smoked Cheese Purchasing Factors a. Why are you purchasing smoked cheese? b. For what occasion would you purchase smoked cheese? i. Potential occasions for smoked cheese (try to get focus group thinking about occasions they might buy smoked cheese for; do they want to ‘show it off’ or is it more of a casual food item?): PROBE – is smoked cheese a special occasion only product? 1. Dinner party? 2. Birthday party? 3. Holiday party? 4. Regular evening as a snack or to compliment a meal? ii. Is smoked cheese a low-end or high-end item? iii. Is smoked cheese artisan? c. What factors influence your purchase? Brand? Quality? Color? i. How do these factors influence your decisions? d. What brands of smoked cheese do you purchase? i. Are there differences between brands that make you purchase one brand over another?

IV. Focus Area 3: Process a. How familiar are you with the process of smoking meat? i. How do you think this relates to smoked cheese? b. How do you think smoke/smoked flavor is added to smoked cheese? PROBE for understanding of natural (cold) smoke process vs adding liquid smoke i. Liquid smoke- Add to curd during the cheese-making process ii. Cold Smoking- Smoking cheese at room temperature iii. Are both of these processes natural? PROBE for feelings

c. How do you feel about the smoking method of adding liquid smoke? d. How do you feel about the cold smoking method? e. Now that you know several methods of smoking foods that are specific to cheese (liquid smoke, cold smoking) has your opinion of smoking methods changed? i. Do you think one method is more or less desirable than the rest?

V. Focus Area 4: Flavor, Appearance, Other Characteristics a. When thinking about the flavor of smoked cheese, is there anything specific you are looking for? b. When thinking about the appearance of smoked cheese, is there anything specific you are looking for? i. Is smoked cheese appearance indicative of quality? ii. Is the appearance of smoked cheese noticeably different than regular cheese? c. When thinking about the texture of smoked cheese, is there anything specific you are looking for? i. IS the texture of smoked cheese noticeably different than regular cheese? d. Aside from flavor, are there major differences between smoked cheese and non- smoked cheese? e. Smoke Intensity: What do you know about the intensities of smoked cheese products? i. How would you scale or rate the intensities of a product? f. Is smoked cheese a natural product? g. Do cheeses smoked with different wood sources taste different to you?

VI. Focus Area 5: Applications a. Do consumers smoke cheese at home? b. When you consume smoked cheese, do you consume it by itself or in a recipe? Do you cook with it? PROBE: is this a table cheese or a cooking cheese? i. If you consume smoked cheese by itself, do you pair it with anything? c. Have you ever considered cooking with smoked cheese? d. How versatile is smoked cheese in cooking/baking? e. Do you think using smoked cheese in food products affects the recipes you use it in? (focus on comments about intensity) f. Can you use smoked cheese as a replacement for regular cheese in recipes? g. What is your ideal smoked cheese? (Focus on what the focus group says first or what attributes they emphasize the most when answering this question)

VII. Wrap-Up a. Summarize b. Final Comments- Before we leave, is there anything you would like to add that was not mentioned?

Figure 1. Moderator guide for smoked cheese focus groups

Table 2. Attributes and levels used in the ACBC conjoint survey (Survey 2) Attributes Levels Low Intensity Smoke Intensity Medium Intensity High Intensity Smoke generated from wood chips Method of Smoking Liquid smoke (in a bottle and applied to products) Gouda Cheddar Type of Cheese Provolone Mozzarella Hickory Maple Type of Wood Apple Mesquite Chery Cheese Counter Located near Milk/Dairy products Location in Grocery Store Located near Deli/Bakery items Located near cheese shreds Brownish, yellow smoke color exterior Appearance/Color of Cheese Regular exterior appearance No label claim Label Claim Organic All natural

Table 3. Smoked foods general and specific product and specific-wood smoke selection frequency, (n=1195 consumers) (Survey 1) Smoke General Specific d Food Product Smoked Product Unknow Genera Selectio Food Selectio Ald Appl Ceda Cherr Hicko Mesqui Mapl Peca Oth Oak n/I don't l n Specific n er e r y ry te e n er Know Produc Frequen Products Frequen ts cy (%) cy (%) 2.3 44.4 17.1 19.4 40.3 20.8 30.6 0.5 Brie 27.0% 53.2% 31.9% 6.0% % % % % % % % % 2.0 34.8 19.7 14.1 28.4 20.2 24.5 0.2 Gouda 80.5% 55.3% 36.5% 12.7% % % % % % % % % 3.9 33.3 19.0 10.6 25.5 26.3 22.0 0.0 Cheddar 69.8% 63.3% 41.9% 8.1% % % % % % % % % Smoke Mozzare 7.2 22.9 18.9 16.0 21.3 26.9 22.7 1.1 46.9% 44.5% 28.8% 19.5% d 66.90% lla % % % % % % % % Cheese Provolon 5.6 21.5 16.7 14.7 21.5 26.6 21.5 1.0 49.4% 50.4% 39.2% 16.5% e % % % % % % % % 7.4 22.3 18.2 13.2 21.5 19.0 19.8 0.0 Ricotta 15.1% 26.5% 26.5% 33.1% % % % % % % % % 9.9 25.3 19.3 18.3 29.2 27.2 22.8 0.5 Gruyere 25.3% 44.6% 30.2% 12.9% % % % % % % % % Other 1.9% N/A 1.2 40.1 13.8 57.0 13.1 14.4 0.7 Ham 70.4% 9.1% 65.4% 34.3% 6.2% % % % % % % % 0.9 32.3 12.7 11.1 50.6 13.8 12.4 0.1 Sausage 74.5% 58.2% 37.8% 7.9% Smoke % % % % % % % % 91.50% d Meat 1.6 43.4 11.1 63.0 11.8 12.3 0.4 Bacon 76.9% 9.3% 66.5% 30.6% 4.6% % % % % % % % Meat 17.1% N/A Other

Table 3. (continued). General Smoke Specific Smoked Product d Food Product Food Unknow Selectio Specifi Selectio Alde Appl Ceda Cherr Hicko Mesqui Mapl Peca Oth General Oak n/I don't n c n r e r y ry te e n er Product Know Frequen Product Frequen s cy (%) s cy (%) 14.8 33.0 19.3 21.1 13.9 0.2 Salmon 96.3% 6.2% 9.1% 42.7% 34.3% 20.0% % % % % % % Smoked 49.50% 13.2 19.0 22.9 17.6 32.7 18.1 0.0 Fish Trout 34.7% 7.8% 50.2% 34.6% 16.6% % % % % % % % Other 6.1% N/A 38.2 15.5 32.5 32.5 40.7 18.7 0.8 Beer 53.2% 5.7% 26.8% 9.8% 13.8% % % % % % % % Smoked 32.1 11.5 23.1 45.5 17.3 38.5 1.9 Beverag 19.30% Coffee 67.5% 3.2% 16.7% 3.9% 21.8% % % % % % % % es Cocktai 45.6 13.3 41.1 40.0 24.4 24.4 0.0 39.0% 4.4% 23.3% 14.4% 11.1% ls % % % % % % % Other 2.30% Other 1.3% N/A

Overall Mean Utility Scores for All Attributes and Levels 80.0 A

60.0 A A 40.0 A A 20.0 B B A A B B B B 0.0 C C B C -20.0 C

C MeanUtility Score -40.0 D D -60.0 C

-80.0 B

Apple

Maple

Gouda

Cherry

Hickory

Organic

Cheddar

Mesquite

Provolone

AllNatural

Mozzarella

LowIntensity

HighIntensity

No No claim label

CheeseCounter

MediumIntensity

Locatednear cheeseshreds

Regularexterior appearance

Locatednear Deli/Bakeryitems

Locatednear Milk/Dairyproducts

Smokegenerated from woodchips

Brownish,yellow smoke colorexterior Liquid (in Smoke a bottle andapplied to products) Smoke Intensity Method of Smoking Type of Cheese Type of Wood Location in Grocery StoreAppearance/Color of Cheese Label Claim Figure 2. Overall mean utility scores for attribute levels for the total population (n=367) from the smoked cheese conjoint survey. Zero-centered utility values for levels within attributes. Letters indicate significant differences (p<0.05) within each attribute for the total population. (Survey 2)

Attribute Importance Scores by Cluster 45.0 ACBC Typical Consumer Cluster (n=86) 40.0 ACBC All Natural Cluster (n=118) ACBC Connoisseur Cluster (n=163) 35.0 Overall (n=367)

30.0

25.0

20.0

15.0 MeanImportance Score

10.0

5.0

0.0 Smoke Intensity Smoking Method Type of Cheese Type of Smoke Location of Smoked Appearance of Specific Label Cheese in Grocery Smoked Cheese Store Attributes

Figure 3. Attribute importance scores from smoked cheese conjoint survey for segmented consumer clusters. (Survey 2) *Sum of importance score values for each cluster is 100 points total and scores are interpreted as ratio-scaled values.

Table 4. Attribute importance scores for consumer clusters (Survey 2) ACBC Typical ACBC All ACBC Overall (n=367) Consumer Natural Cluster Connoisseur cluster (n=118) Cluster (n=163) ACBC Attributes (n=86) Smoking Method 21.1a 16.7 38.3 10.7 Smoke Intensity 18.7b 34.6 13.7 14.0 Type of Smoke 18.7b 13.3 13.7 25.2 Type of Cheese 17.8b 12.9 13.1 23.8 Location of Smoked Cheese in Grocery Store 10.0c 8.7 9.0 11.5 Specific Label 7.7d 7.7 6.9 8.4 Appearance of Smoked Cheese 6.0e 6.1 5.3 6.4 *Sum of importance score values for each cluster is 100 points total and scores are interpreted as ratio-scaled values. **Means in overall population row followed by a different letter are different (p<0.05)

Mean Utility Scores Clustered by Importance Scores ACBC Typical Consumer Cluster (n=86) 200 ACBC All Natural Cluster (n=118)

150

100

-50

Centered Centered UtilityMeans -

-100 Zero

-150

-200

Apple

Maple

Gouda

Cherry

Hickory

Organic

Cheddar

Mesquite

Provolone

AllNatural

Mozzarella

LowIntensity

HighIntensity

No No labelclaim

CheeseCounter

MediumIntensity

Locatednear cheeseshreds

Regularexterior appearance

Locatednear Deli/Bakeryitems

Locatednear Milk/Dairyproducts

Smokegenerated from woodchips

Brownish,yellow smoke colorexterior Liquid Liquid (in a Smoke bottle applied and to products) Smoke Intensity Method of Smoking Type of Cheese Type of Wood Location in Grocery StoreAppearance/Color of Cheese Label Claim Figure 4. Mean utility scores from smoked cheese conjoint survey for segmented consumer clusters. (Survey 2)

Table 5. Scaled importance scores for smoked cheese attributes (n=367), (Survey 2). ACBC All ACBC ACBC Typical Natural Connoisseur All (n=367) Consumer Cluster Cluster Cluster (n=86) (n=118) (n=163) Appearance/Color of Cheese 3.0d 2.9 2.9 3.1 Packaging and Labels 2.3f 2.3 2.2 2.3 Price 3.6b 3.4 3.4 3.7 Brand 2.0g 2.1 1.8 2.1 Smoke Intensity 3.3c 3.8 3.2 3.2 Organic label 2.0g 2.0 1.9 2.1 Natural Label 2.2f 2.3 2.2 2.2 Use of Liquid Smoke 2.5e 2.4 3.0 2.1 Use of Natural Wood Smoke 3.4bc 3.4 3.9 3.1 Type of Smoke/Wood Source (ex. Mesquite, Hickory) 3.1d 3.2 3.0 3.2 Type of Cheese (ex. Mozzarella, Gouda, Cheddar) 3.9a 4.0 3.8 4.0 *Importance was scored on a 5-point scale where 1 = not at all important and 5 = very important. **Means in a row followed by a different letter are different (p<0.05)

Table 6. Maximum Difference (MaxDiff) scaling of smoked cheese attributes by cluster (n=367), (Survey 2) ACBC ACBC Typical All Overall ACBC Connoisseur Label Consumer Cluster Natural (n=367) Cluster (n=163) (n=86) Cluster (n=118) Type of Cheese (Ex. Mozzarella, Gouda, Cheddar) 22.3a 21.1 21.5 23.6 Price 16.5b 15.0 15.6 17.9 Type of Smoke/Wood Source (Ex. Mesquite, 14.0c 13.8 13.6 14.3 Hickory) Use of Natural Wood Smoke 13.3c 13.4 17.1 10.7 Smoke Intensity 13.2c 17.4 12.0 11.9 Appearance/Color of Cheese 10.0d 7.5 9.1 11.9 Use of Liquid Smoke 3.1e 3.1 4.1 2.4 Organic Label 2.7e 3.5 2.2 2.6 Natural Label 2.5ef 2.9 2.7 2.0 Packaging & Labels 1.6fg 1.6 1.5 1.6 Brand 0.9g 0.7 0.7 1.2 *Sum of values in each column is 100 total points and results are interpreted as ratio-scaled values, so a higher score indicates a higher MaxDiff ranking (more appealing) **Means in a row followed by a different letter are different (p<0.05)

Table 7. Trained panel mean sensory attributes of smoked Cheddar cheeses and unsmoked control Cheddar cheeses Mild Cheddar Apple Cherry Hickory Control Low High Low High Low High Unsmoked Overall Aroma 2.5d 2.7cd 3.3b 2.2d 3.4b 3.0bc 4.2a Smoke Aroma ND 2.3c 3.1b 1.8d 3.4b 2.6c 4.0a Cooked 4.1a 3.1c 3.0c 3.3b 3.0c 3.3b 3.0c Whey 3.5a 4.8a 2.5a 2.7a 2.5a 2.7a 2.4a Milkfat/Lactone 3.6a 3.2b 3.2b 3.2b 3.1b 3.2b 3.1b Campfire/Marshmallow ND 1.6d 2bc 1.8c 2.5a 2.0c 2.2b Meaty/Smoky ND ND 1.0b ND ND 1.1b 3.6a Ashy ND 2.2d 3.1a 1.2e 2.2d 2.7c 2.8b Sour 2.8a 2.8a 2.8a 2.8a 2.9a 2.8a 2.8a Salty 3.2a 2.9ab 2.9b 2.9b 2.9ab 3.1ab 3.1ab Sweet 2.0b 2.1ab 2.3a 2.2a 2.1ab 2.0b 2.0b Umami 1.9b 2.7a 2.6a 2.7a 2.7a 2.7a 2.7a Overall Smoke Intensity ND 2.3d 3.3b 1.7e 3.2b 2.8c 4.1a Fruity ND ND ND ND 0.9a ND ND Waxy Green ND 0.9b 1.4a ND ND ND ND Phenolic ND ND ND 0.6a 0.6a ND ND Attributes were scored on a 0 to 15-point scale, with 0=not intense at all and 15=extremely intense. Different letters in rows following means signify significant differences (p < 0.05) ND – not detected. Attributes not listed were not detected in these cheeses.

Biplot (axes PC1 and PC2: 68 %)

4 Fruity High Intensity Cherry-smoked Phenolic Sour Cheddar

Campfire/Marshmallow 2 Umami Low Intensity Cherry-smoked Cheddar

Cooked

PC2 (27 %) (27 PC2 0 Smoke Aroma Sweet Low Intensity Hickory- Overall Aroma Low Intensity Apple-smoked smoked Cheddar -1 Cheddar Overall Smoke Intensity Whey High Intensity Hickory- smoked Cheddar High Intensity Apple-smoked Salty Cheddar Meaty/Smoky -2 Milkfat/Lactone Waxy Green Ashy

-3 -4 -3 -2 -1 0 1 2 3 4 5 PC1 (41 %)

Attributes Sample

Figure 5. Principal component biplot of smoked Cheddar cheeses

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Table 8. Consumer acceptance scores for smoked cheeses (n=135) Cherry- Cherry- Hickory- Hickory- Apple-LOW Apple-HIGH LOW HIGH LOW HIGH Overall Appearance Liking 7.3a 7.4a 7.3a 7.4a 7.2a 7.2a Color Liking 7.3ab 7.3ab 7.4ab 7.5a 7.2b 7.3ab Too Light 6.7%a 3.7%a 8.1%a 5.2%a 10.4%a 9.6%a Color JAR Just About Right 84.4%a 91.9%a 86.7%a 88.9%a 83.7%a 85.2%a Too Much 8.9%a 4.4%a 5.2%a 5.9%a 5.9%a 5.2%a Aroma Liking 6.8ab 6.7b 6.9ab 6.9ab 6.9ab 7.0a Not Enough 29.6%a 17.0%ab 31.1%a 20.7%ab 28.1%a 10.4%b Aroma Aroma JAR Just About Right 61.5%a 64.4%a 63.0%a 66.7%a 60.7%a 71.1%a Too Much Aroma 8.9%a 18.5%a 5.9%a 12.6%a 11.1%a 18.5%a Smoke Aroma Intensity 5.3cd 5.7bc 4.6e 5.7b 5.0de 6.3a Overall Liking 6.4ab 6.3b 6.8a 6.5ab 6.2b 6.1b Flavor Liking 6.4ab 6.2b 6.8a 6.4ab 6.2b 6.2b Overall Too Weak 19.3%b 19.3%b 38.5%a 15.6%b 25.9%ab 13.3%b Flavor Just About Right 53.3%a 55.6%a 56.3%a 61.5%a 52.6%a 53.3%a Strength Too Strong 27.4%a 25.2%a 5.2%b 23.0%a 21.5%a 33.3%a Smoky Flavor Liking 6.2a 6.1a 6.4a 6.3a 6.1a 6.1a Smoke Flavor Intensity 6.1a 6.1a 4.5c 6.1a 5.5b 6.5a Not Smoky 23.0%ab 17.0%b 41.5%a 19.3%b 30.4%ab 14.8%b Smokiness Enough JAR Just About Right 49.6%a 48.9%a 50.4%a 55.6%a 47.4%a 48.1%a Too Smoky 27.4%a 34.1%a 8.1%b 25.2%a 22.2%ab 37.0%a Too Cheesy/Not Enough Smoky 21.5%b 18.5%b 40.0%a 17.8%b 25.2%ab 11.9%b Smokiness/ Flavor Cheese Just About Right 43.0%a 46.7%a 47.4%a 51.9%a 45.9%a 48.1%a Flavor JAR Too Smoky/Not Enough Cheese 35.6%a 34.8%a 12.6%b 30.4%a 28.9%a 40.0%a Flavor

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Table 8 (continued). Cherry- Cherry- Hickory- Hickory- Apple-LOW Apple-HIGH LOW HIGH LOW HIGH Earthy 6.0%a 6.3%a 5.4%a 4.5%a 5.1%a 5.5%a Dirt 0.9%a 1.0%a 0.9%a 0.9%a 1.2%a 0.6%a Fresh Tobacco 0.8%a 1.1%a 0.4%a 1.3%a 1.0%a 1.7%a Woody 10.0%a 11.0%a 8.0%a 10.7%a 11.9%a 11.6%a Ashy 6.8%a 6.3%a 3.7%a 6.5%a 6.0%a 6.7%a Charcoal 7.0%a 6.8%a 5.2%a 7.3%a 6.2%a 9.2%a Meaty 4.0%a 3.6%a 3.5%a 4.7%a 2.7%a 3.2%a Smoky 17.6%a 17.7%a 15.8%a 18.5%a 16.8%a 18.5%a Fruity 0.9%a 0.4%a 0.9%a 0.7%a 0.8%a 0.4%a Cherry 0.8%a 1.3%a 1.5%a 1.3%a 0.2%a 1.0%a Smoked Vanilla 0.2%a 0.4%a 0.2%a 0.4%a 0.2%a 0.2%a Cheese Sweet 1.7%a 1.5%a 2.4%a 1.9%a 1.6%a 2.1%a CATA* Plastic 2.8%a 2.9%a 1.3%a 3.0%a 3.7%a 2.1%a Spicy 0.2%a 0.8%a 0.0% 0.2%a 0.4%a 0.6%a Marshmallow 0.6%a 0.2%a 0.2%a 0.7%a 0.4%a 0.8%a Campfire 9.5%a 8.9%a 7.6%a 9.0%a 7.0%a 10.3%a Cinnamon 0.4%a 0.2%a 0.0% 0.0% 0.0% 0.2%a Milky 3.6%a 4.0%a 6.9%a 3.7%a 4.9%a 3.4%a Buttery 4.2%a 4.6%a 6.3%a 4.1%a 5.8%a 3.8%a Salty 4.5%a 5.1%a 6.5%a 5.4%a 5.7%a 3.6%a Sharp 8.3%a 8.6%a 10.4%a 7.5%a 8.2%a 5.9%a Mild 7.9%a 6.7%a 11.9%a 7.1%a 9.6%a 7.1%a Other 1.3%a 0.8%a 1.3%a 0.6%a 0.8%a 1.5%a Purchase Intent 3.3a 3.3a 3.4a 3.3a 3.1a 3.1a

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Table 8 (continued). Appearance/Color 83.7% of cheese Packaging and 36.3% Labels Price 80.0% Brand 36.3% Smoke Intensity 71.1% Organic Label 18.5% Natural Label 23.7% Attributes Use of Liquid Influencing 14.1% Smoke Selection of Use of Natural Smoked 40.0% Cheese Wood Smoke Type of Smoke/Wood Source (Ex. 52.6% Mesquite, Hickory) Type of Cheese (Ex. Mozzarella, 83.7% Gouda, Cheddar) Other 0.7%

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Table 8 (continued). Eat it straight 88.9% Cold: added to compliment food like a condiment 62.2% (salads, sandwiches) Cold: as an ingredient (dips, 41.5% salads) Cold: as an appetizer or part 78.5% Use/Consu of a cheese tray mption of Hot: added to Smoked compliment food Cheese like a condiment (Tacos, eggs, 65.2% vegetables, burgers, fries, chili) Hot: as an ingredient ([izza, casserole, mac 57.8% and cheese, quiche, sauces, nachos) Other 0.7% Frequency Selected Rank

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Table 8 (continued). Brie 36.3% 2.8 Gouda 77.0% 1.8 Types of Cheddar 91.9% 1.7 Smoked Mozzarella 60.7% 2.5 Cheese Provolone 52.6% 2.7 Familiar Ricotta 19.3% 3.1 With Gruyere 37.0% 2.9 Other (Please 0.70% NA Specify) Apple 74.8% 2.4 Alder 11.1% 3.5 Types of Cherry 56.3% 2.6 Wood Cedar 57.0% 2.8 Smoke Hickory 88.1% 1.8 Familiar Maple 60.7% 2.7 with for Mesquite 85.2% 2.3 Smoked Oak 50.4% 3.0 Foods Pecan 30.4% 2.8 Other (Please 0.0% NA Specify) Data Represents 135 consumers Different letters in rows following means signify significant differences (p < 0.05) Liking attributes were scored on a 9-point hedonic scale where dislike extremely=1 and like extremely=9 JAR questions were scored on a 5-point scale where 1 or 2 = too little, 3 = just about right, and 4 or 5 = too much. Percentage of consumers that selected these options is presented and statistical lettering was determined by Chi-square Intensity attributes were scored on a 9-point hedonic scale where 1=not at all smoky and 9=very smoky Purchase Intent was scored on a 5-point scale where 1 or 2= would not buy, 3= may or may not buy, and 4 or 5= would buy *Check-all-that-apply question. Total does not add up to 100% Rank is reported as average ranking for each sample. A lower average rank indicates a better ranking score.

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Table 9. Two-way ANOVA (smoke type x intensity) for consumer liking means for smoked Cheddar cheese evaluation (n=135 through each sample) Overall Smoke Overall Smoky Smoke Color Aroma Overall Appearance Aroma Flavor Flavor Flavor Liking Liking Liking Liking Intensity Liking Liking Intensity Cherry*HIGH 7.4a 7.5a 6.9ab 5.7b 6.5ab 6.4ab 6.3a 6.1a Cherry*LOW 7.3a 7.4ab 6.9ab 4.6e 6.8a 6.8a 6.4a 4.5c Apple*LOW 7.3a 7.3ab 6.8ab 5.3cd 6.4ab 6.4ab 6.2a 6.1a Apple*HIGH 7.4a 7.3ab 6.7b 5.7bc 6.3b 6.2b 6.1a 6.1a Hickory*HIGH 7.2a 7.3ab 7.0a 6.3a 6.1b 6.2b 6.1a 6.5a Hickory*LOW 7.2a 7.2b 6.9ab 5.0de 6.2b 6.2b 6.1a 5.5b Pr > F(Model) 0.537 0.452 0.419 < 0.0001 0.040 0.073 0.810 < 0.0001 Pr > F(Smoke Type) 0.159 0.170 0.184 0.011 0.011 0.028 0.406 < 0.0001 Pr > F(Intensity) 0.562 0.314 0.941 < 0.0001 0.133 0.139 0.502 < 0.0001 Pr > F(Smoke 0.966 0.925 0.453 0.012 0.816 0.682 0.991 < 0.0001 Type*Intensity) Liking attributes were scored on a 9-point hedonic scale where 1 = dislike extremely and 9 = like extremely. Intensity attributes were scored on a 9-point hedonic scale where 1 = not at all smoky and 9 = very smoky. 1. LSD = Least significant difference

106

Typical Consumer Cluster (n=71) 9 8 7 Apple Low 6 Apple High 5 Cherry Low 4 Cherry High 3 Hickory Low 2 1 Hickory High Overall Color Liking Aroma Liking Smoke Aroma Overall Liking Overall Flavor Smoky Flavor Smoke Flavor Appearance Liking Intensity Liking Liking Intensity

Connoisseur Cluster (n=35) 9 8 7 Apple Low 6 Apple High 5 Cherry Low 4 Cherry High 3 Hickory Low 2 Hickory High 1 Overall Color Liking Aroma Liking Smoke Aroma Overall Liking Overall Flavor Smoky Flavor Smoke Flavor Appearance Liking Intensity Liking Liking Intensity

107

All Natural Cluster (n=29) 9 8

7 Apple Low 6 Apple High 5 Cherry Low 4 Cherry High 3 Hickory Low 2 Hickory High 1 Overall Color Liking Aroma Liking Smoke Aroma Overall Liking Overall Flavor Smoky Flavor Smoke Flavor Appearance Liking Intensity Liking Liking Intensity

Figure 6. Consumer acceptance test liking scores for consumer clusters (n=135)

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APPENDICES

109

APPENDIX A: Factor loadings for descriptor tags for smoke aroma projective mapping Descriptor Tag F1 F2 F3 Smoky 0.899 0.007 0.198 Ashy/Charcoal 0.863 0.222 0.140 Guiacol/Meaty 0.707 0.196 0.264 Woody/Bark 0.693 0.401 0.206 Spicy/Cinnamon -0.686 0.051 0.431 Resinous/Terpene -0.765 0.027 0.163 Plastic -0.846 0.355 -0.019 Fresh Tobacco 0.385 0.567 -0.540 Earthy/Dirt 0.254 0.714 -0.215 Fruity/Cherry -0.212 -0.643 0.027 Sweet -0.477 -0.658 -0.196 Vanillin/Marshmallow 0.114 -0.839 -0.339

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APPENDIX B: SELECTION FREQUENCY OF PRODUCT AND SMOKE COMBINATION SELECTION, NUMBERS REPRESENT THE AMOUNT OF TIMES EACH COMBINATION WAS SELECTED (SURVEY 1)

Frequency of Ham Pecan 111 Product Combination Selection Salmon Maple 110 Bacon Hickory 559 Mozzarella Mesquite 108 Bacon Maple 530 Cheddar Cedar 106 Ham Hickory 503 Ham Cherry 106 Sausage Hickory 474 Provolone Oak 105 Ham Maple 438 Sausage Cedar 103 Sausage Maple 412 Bacon Pecan 103 BaconApple 365 Trout Hickory 103 Gouda Hickory 356 Mozzarella Oak 101 Cheddar Hickory 353 Ham Oak 101 SausageApple 332 Sausage Pecan 101 HamApple 308 Bacon Oak 99 Sausage Mesquite 308 Brie Apple 96 Ham Mesquite 264 Bacon Cherry 93 Bacon Mesquite 257 Gouda Cherry 91 Salmon Hickory 243 Gruyere Hickory 90 Gouda Mesquite 235 Sausage Cherry 90 Cheddar Mesquite 234 Brie Maple 87 Gouda Apple 224 Mozzarella Apple 86 Provolone Hickory 199 Mozzarella Pecan 85 Salmon Mesquite 195 Provolone Apple 85 Salmon Cedar 188 Provolone Maple 85 Cheddar Apple 186 Provolone Pecan 85 Gouda Maple 183 Salmon Apple 84 Mozzarella Hickory 167 Gouda Unknown/I Gouda Pecan 158 don't know 82 Provolone Mesquite 155 Mozzarella Maple 80 Cheddar Oak 147 Salmon Pecan 79 Cheddar Maple 142 Bacon Cedar 78 Gouda Oak 130 Mozzarella Unknown/I Gouda Cedar 127 don't know 73 Cheddar Pecan 123 Mozzarella Cedar 71 Salmon Oak 120 Trout Mesquite 71 Brie Hickory 115 Coffee Maple 71 Salmon Unsure/I don't Ham Cedar 70 know 114 Brie Mesquite 69 Sausage Oak 112 Trout Oak 67

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Brie Pecan 66 Trout Unsure/I don't Provolone Cedar 66 know 34 Provolone Unknown/I Coffee Unsure/I don't don't know 65 know 34 Sausage Unsure/I don't Beer Hickory 33 know 64 Ricotta Hickory 32 Gruyere Mesquite 61 Ricotta Mesquite 32 Mozzarella Cherry 60 Mozzarella Alder 27 Coffee Pecan 60 Ricotta Apple 27 Cheddar Cherry 59 Trout Alder 27 Gruyere Maple 59 Coffee Oak 27 Provolone Cherry 58 Ricotta Maple 26 Gruyere Oak 55 Gruyere Unknown/I Salmon Cherry 52 don't know 26 Gruyere Apple 51 Coffee Hickory 26 Beer Oak 50 Ricotta Pecan 24 Coffee Apple 50 Ricotta Oak 23 Ham Unsure/I don't Beer Pecan 23 know 48 Cheddar Alder 22 Trout Cedar 47 Provolone Alder 22 Beer Apple 47 Ricotta Cedar 22 Gruyere Pecan 46 Cocktails Oak 22 Brie Oak 45 Cocktails Pecan 22 Cheddar Unknown/I Sausage Alder 21 don't know 45 Cocktails Hickory 21 Brie Cherry 42 Gruyere Alder 20 Cocktails Apple 41 Beer Cedar 19 Ricotta Unknown/I Coffee Cedar 18 don't know 40 Beer Unsure/I don't Beer Cherry 40 know 17 Beer Maple 40 Ricotta Cherry 16 Gruyere Cedar 39 Trout Cherry 16 Bacon Unsure/I don't Brie Unknown/I don't know 39 know 13 Trout Apple 39 Gouda Alder 13 Brie Cedar 37 Bacon Alder 13 Gruyere Cherry 37 Cocktails Mesquite 13 Trout Pecan 37 Beer Mesquite 12 Cocktails Cherry 37 Cocktails Cedar 12 Trout Maple 36 Cocktails Unsure/I Coffee Cherry 36 don't know 10 Cocktails Maple 36 Ricotta Alder 9 Salmon Alder 35

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Ham Alder 9 Brie Other 1 Beer Alder 7 Gouda Other 1 Coffee Mesquite 6 Gruyere Other 1 Brie Alder 5 Sausage Other 1 Ham Other 5 Salmon Other 1 Coffee Alder 5 Beer Other 1 Mozzarella Other 4 Cheddar Other 0 Provolone Other 4 Ricotta Other 0 Cocktails Alder 4 Trout Other 0 Bacon Other 3 Cocktails Other 0 Coffee Other 3

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APPENDIX C. DEMOGRAPHIC INFORMATION FOR ACBC CONSUMER CLUSTERS (SURVEY 2)

ACBC ACBC ACBC Typical All Connoisse

Consumer Natural ur

Cluster Cluster Cluster (n=86) (n=118) (n=163) Male 17.4% 24.6% 26.4% Gender Female 82.6% 75.4% 73.6% 18-24 11.6% 11.9% 16.0% 25-34 29.1% 27.1% 32.5% 35-44 19.8% 22.0% 23.3% Age Group 45-54 16.3% 16.9% 17.8% 55-64 17.4% 17.8% 7.4% 65 years or older 5.8% 4.2% 3.1% White/Caucasian 76.7% 74.6% 72.4% Black/African American 4.7% 13.6% 16.0% Hispanic/Latino 2.3% 3.4% 1.2% Ethnicity Asian/Pacific Islander 11.6% 6.8% 5.5% Other/Mixed Race 1.2% 0.8% 4.3% Prefer Not to Answer 3.5% 0.8% 0.6% Single 33.7% 30.5% 39.3% Engaged 5.8% 0.8% 7.4% Marital Status Married 50.0% 60.2% 43.6% Separated/Widowed/Div 10.5% 8.5% 9.8% orced Some high school 0.0% 0.8% 0.0% High school Graduate 2.3% 3.4% 1.8% Some college 11.6% 14.4% 17.8% Associate's degree 5.8% 6.8% 6.7% Education Bachelor's degree 46.5% 47.5% 47.9% Graduate or Professional 32.6% 26.3% 25.8% Degree Other (please specify) 1.2% 0.8% 0.0% Full-time 55.8% 66.1% 69.3% Part-time 9.3% 14.4% 9.2% Not employed, looking 4.7% 2.5% 3.1% for work Employment Not employed, not 1.2% 4.2% 3.1% looking for work Student 20.9% 8.5% 12.3% Retired 7.0% 4.2% 2.5% Prefer not to answer 1.2% 0.0% 0.6% Income <$19,999 7.0% 5.9% 6.1%

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$20,000-$39,999 11.6% 5.9% 11.7% $40,000-$59,999 11.6% 20.3% 22.1% $60,000-$79,999 22.1% 17.8% 17.8% $80,000-$99,999 22.1% 17.8% 16.6% >$100,000 25.6% 32.2% 25.8% 1-2 people 61.6% 51.7% 52.1% 3-4 people 32.6% 35.6% 44.2% People in Household 5-6 people 4.7% 12.7% 3.7% 7+ people 1.2% 0.0% 0.0% Yes 43.0% 45.8% 47.9% Children No 57.0% 54.2% 52.1% 1 child 15.1% 12.7% 14.1% 2 children 20.9% 18.6% 27.0% Children 3 children 4.7% 10.2% 4.9% 4 children 2.3% 4.2% 1.2% 5+ children 0.0% 0.0% 0.6% I am the primary shopper 89.5% 86.4% 89.6% (~75%-100%) I equally split the grocery shopping 8.1% 10.2% 9.2% Primary Shopper (~50%) I do some of the grocery 2.3% 2.5% 1.2% shopping (~25%) I do not do any grocery 0.0% 0.8% 0.0% shopping (0%) I do all of the food 40.7% 44.9% 47.9% preparation I do most of the food 48.8% 42.4% 42.9% preparation Food Preparation I do some of the food 9.3% 12.7% 8.6% preparation I do none of the food 1.2% 0.0% 0.6% preparation Standard Grocery Stores (Harris Teeter, Kroger, 96.5% 95.8% 96.9% Food Lion, etc.) Discount Grocery Stores 83.7% 80.5% 86.5% (Wal-Mart, Target, etc.) Premium Grocery Stores Groceries (Fresh Market, Whole 62.8% 68.6% 63.2% Foods, etc.) Bulk Supplier (Costco, 53.5% 61.0% 56.4% Sam's Club, etc.) Farmers Markets 57.0% 52.5% 55.8% Other (please specify) 7.0% 5.9% 4.3%

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Milk 96.5% 95.8% 95.7% Eggs 93.0% 98.3% 96.3% Butter 96.5% 97.5% 98.2% Cottage Cheese 58.1% 56.8% 54.6% Yogurt 91.9% 93.2% 94.5% Heavy Cream 70.9% 69.5% 69.9% Products Coffee 90.7% 84.7% 85.9% Frozen Pizza 79.1% 72.0% 84.7% Mozzarella Cheese 93.0% 95.8% 93.3% Iced Tea 67.4% 66.1% 72.4% Cold Brew Coffee 55.8% 52.5% 54.6% Iced Coffee 59.3% 49.2% 55.8% Smoke Cheese Frequency 4.0a 3.9 3.6 Familiarity with Smoked Cheese 3.5a 3.5 3.6 Familiarity with Different Woods used to make 2.5a 2.6 2.6 Smoked Cheese Familiarity with Different Cheeses that are smoked 3.0a 3.1 3.0 Familiarity with Process of Adding Liquid Smoke 1.8a 1.8 2.0 Familiarity with Process of Cold Smoking Cheese 1.5a 1.6 1.8 Appearance/Color of 51.2% 61.9% 64.4% Cheese Packaging and Labels 27.9% 29.7% 36.8% Price 79.1% 83.1% 83.4% Brand 17.4% 18.6% 28.2% Smoke Intensity 83.7% 62.7% 64.4% Organic label 19.8% 22% 23.3% Natural Label 24.4% 24.6% 30.7% Qualities Influencing Use of Liquid Smoke 10.5% 16.9% 19.0% Smoked Cheese Purchase Use of Natural Wood 59.3% 73.7% 56.4% Smoke Type of Smoke/Wood Source (ex. Mesquite, 64.0% 61.9% 69.3% Hickory) Type of Cheese (ex. Mozzarella, Gouda, 87.2% 89.8% 92.0% Cheddar) Other (please specify) 0.0% 0.8% 1.2%

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APPENDIX D: DEMOGRAPHIC INFORMATION AND CONSUMPTION CHARACTERISTICS OF SMOKED CHEDDAR CHEESE CONSUMERS IN THE CONSUMER ACCEPTANCE TEST (N=135)

Male 29.6% Gender Female 70.4% 18-24 years old 14.1% 25-34 years old 37.0% Age 35-44 years old 21.5% 45-54 years old 18.5% 55-64 years old 8.9% $20,000-$39,999 14.1% $40,000-$59,999 23.7% Income $60,000-$79,999 22.2% $80,000-$99,999 16.3% >$100,000 23.7% I am the primary shopper (~75%-100%) 96.3% Household Shopping I equally split the grocery shopping (~50%) 3.7% White/Caucasian 60.7% Black/African American 20.7% Ethnicity Hispanic/Latino 5.2% Asian/Pacific Islander 12.6% Other/Mixed Race 0.7% Milk 98.5% Eggs 97.0% Butter 94.8% Cottage Cheese 74.8% Yogurt 97.0% Cheddar Cheese 99.3% Products Purchased/ Consumed Heavy Cream 80.0% in Past 6 Months Coffee 87.4% Frozen Pizza 88.1% Mozzarella Cheese 94.8% Iced Tea 85.2% Iced Coffee 80.0% Cold Brew Coffee 74.8% Every day 20.0% Cheddar Cheese Consumption More than once a week 61.5% Frequency 2-4 times a month 11.9% Once a month 4.4% Less than once a month 1.5% Beer Cheddar Cheese 36.3% Products Purchased/ Consumed Sharp Cheddar Cheese 97.8% in Past 6 Months Smoked Cheddar Cheese 71.1%

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Garlic and Dill Cheddar Cheese 35.6% Chipotle Cheddar Cheese 55.6% Tomato Basil Cheddar Cheese 38.5% Every day 7.4% Smoked Cheese Consumption More than once a week 28.1% Frequency 2-4 times a month 28.1% Once a month 5.9% Less than once a month 1.5% Brie 46.7% Gouda 57.8% Cheddar 68.9% Types of Smoked Cheese Mozzarella 52.6% Purchased Provolone 51.1% Ricotta 30.4% Gruyere 36.3% Other (Please Specify) 0.0% Price 57.8% Availability 54.1% Factors Influencing Smoked Brand 42.2% Cheese Purchase Health 31.1% Flavor 68.9% Package 36.3% Other (Please Specify) 0.7% 28.1% Yes Smoked Cheese Acceptor (n=38) No 0% 1-2 people 47.4% 3-4 people 48.1% Household Size 5-6 people 2.2% 7+ people 1.5% Yes 43.7% Children in Household No 55.6% 1 Child 18.5% 2 Children 21.5% Children Age Groups 3 Children 2.2% 4 Children 1.5% 5+ Children 0.0% Apple 88.9% Alder 18.5% Cherry 59.3% Wood Smokes Familiar With Cedar 65.9% Hickory 91.9% Maple 72.6%

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Mesquite 91.1% Oak 57.8% Pecan 43.0% Other (Please Specify) 0.0% Low Intensity 9.6% Preferred Smoke Intensity Medium Intensity 79.3% High Intensity 10.4%

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