Recipient Organization
VIRGINIA POLYTECHNIC INSTITUTE
(N/A)
BLACKSBURG,VA 24061
Performing Department
Food Science & Technology
Non Technical Summary
Over the last five years the US hard cider industry has grown dramatically and almost unprecedentedly (estimated at an annualized rate of more than 25%, Fabien-Ouellet & Conner, 2018). Virginia has led the Southeast in this growth, and is now the state with the 10th highest number of cideries (23; The Cyder Market LLC, 2018). As apples are one of the 20 most valuable agricultural crops in the state (http://www.vdacs.virginia.gov/agriculture-top20.shtml), the development of this new value-added product is a key opportunity for Virginia. However, while cider is a growth industry, it also lacks product identity to distinguish it from other alcoholic beverages, and this is a key barrier to further growth (Fabien-Ouellet & Conner, 2018). In the US, industry associations have suggested that the industry should define categories and definitions for cider. For example, the United States Association of Cider Makers (USACM) defines cider as "modern", "heritage", or "specialty", with the last category including a number of subcategories including "wood-aged", "sour", and "ice" ciders (United States Association of Cider Makers, 2017). These definitions are based on a combination of production specifications and expected sensory and/or organoleptic outcomes that consumers should be able to perceive. The overall point of both categorization systems is that ciders that belong to a category should be more similar to each other in their sensory properties than to ciders from other categories. However, there is no evidence that consumers are aware of, agree with, or are capable of using these definitions and categories (Fabien-Ouellet & Conner, 2018; Tozer, Galinato, Ross, Miles, & McCluskey, 2015). In fact, the literature on the sensory attributes of hard ciders, in particular from the perspective of consumers, is extremely limited. Most of the existing sensory lexicon for ciders has developed among and for cider producers, and its utility in communicating sensory attributes, value, and desirability to consumers is unproven (Fabien-Ouellet & Conner, 2018). In recent years, only Tozer et al. (2015) have conducted any direct consumer research with hard ciders: they have shown that there is a complex relationship between liking, basic sensory attributes, and willingness-to-pay (WTP) for craft ciders. It is therefore not clear that existing cider categories and descriptors are useful for producers to communicate value to consumers, or that they are useful for consumers seeking to make purchase decisions. This knowledge gap must be bridged to support hard cider producers in Virginia and beyond. Sensory-evaluation methods (Lawless & Heymann, 2010; Qin, Petersen, & Bredie, 2018) can be employed to ascertain how consumers perceive ciders and what product attributes drive sensory perceptions and liking, as well as purchase intent. These consumer-derived cider descriptions and categories can then be employed by producers and industry groups to adjust or even redefine cider categories and employ more effective descriptive labels and language to connect products with consumer expectations. Virginia currently has 23 commercial hard-cider producers, the most in the Southeast (The Cyder Market LLC, 2018). According to Federal statistics, over 45 million gallons of cider were produced in the US in 2017 (https://ttb.gov, December 2017), representing sustained increases in cider production since 2007 (https://ttb.gov, various years). Market reports support and supplement the conclusion that cider as a sector is growing extremely quickly: for example, between 2013 and 2017, premium hard cider sales grew 30% in the US, while small-production cider sales grew even more quickly (The Nielsen Company, 2018). In Virginia, hard-cider producers range from small, regional and craft producers (for example, Foggy Ridge and Albemarle CiderWorks) to nationally distributed (Bold Rock). Cider, as a product, is historically important in the United States, and over the last 11 years it has grown exponentially as a sector of the fermented beverage market. For example, during 2015-16 sales of Virginia ciders increased 52% (Sangjib, 2016) and sales of cider have continued to grow year-over-year in the last 5 years (https://ttb.gov, various years). In many ways, the state of the cider sector in Virginia currently parallels the state of the wine industry several decades ago, with rapid year-over-year growth and an increasingly valuable regional reputation; the wine industry is now one of the most important value-added agricultural sectors in Virginia, contributing $1.4 billion to the Virginia economy and $94 million in direct tax revenue to the state (Frank Rimerman + Co LLP, 2017). Furthermore, apples are already one of the top 20 crops grown in Virginia (ranked #15 according to the most recent 2016 data: http://www.vdacs.virginia.gov/agriculture-top20.shtml), contributing $36,000,000 annually to the state's economy. The cider industry represents an opportunity for existing and new producers to develop new avenues of sales, utilizing both existing production and driving growth in apple production. In the same way as Virginia is now known for quality wine production throughout the Mid-Atlantic and the East Coast in general (Coy, 2016), Virginia has the opportunity to be known as a center of quality cider production at a range of different scales; this is particularly important as one of the fastest growing segments of the fast-growing cider industry is the craft and regional producer (https://ciderassociation.org/). This project will help increase the value of Virginia apple production by supporting the growth of the cider industry in the state. A challenge for small- to mid-sized producers--like many cideries in Virginia--is access to sensory evaluation for routine quality control and marketing purposes. While sensory evaluation is extremely valuable for producers (Stone, Bleibaum, & Thomas, 2012) the expense and specialized facilities normally required are a barrier to widespread adoption of good sensory-evaluation practice by producers. Sensory evaluation is key to small producers to provide consistent products, understand the outcomes of processing and ingredient changes, and meet consumer expectations. The current project will develop sensory methods for use in and beyond Virginia cider.The long-term goals of this project are to develop novel sensory evaluation methodologies which will be applied to Virginia ciders for purposes of product development, quality assurance, and marketing and communication (Objective 1); to use these methods to determine whether existing categories for cider (Great Lakes International Cider and Perry Competition, 2017; United States Association of Cider Makers, 2017) are useful and applicable to Virginia ciders (Objective 2); and to transfer knowledge of these sensory techniques to cider producers to support production quality and agricultural sustainability (Objective 3). Objectives 1 and 2 will use rapid descriptive techniques from sensory evaluation, and Objective 3 will involve cooperation with Extension and Agricultural Economics to identify and communicate best practices and associated value. The ultimate goal of this project is to grow the cider industry in the US; improved product identity facilitates this growth through increasing consumer engagement and allows producers to improve quality. In addition, the project will increase fundamental knowledge about the sensory properties of American cider and about methodologies for rapid product characterization. The research and extension activities involved in this project will increase the value of Virginia apple and hard cider production.
Animal Health Component
30%
Research Effort Categories
Basic
30%
Applied
30%
Developmental
40%
Goals / Objectives
The three main objectives for this project are:Develop novel, rapid sensory-evaluation methods which can be applied to categorizing and describing ciders and other alcoholic beverages.Using a representative sample of ciders produced in Virginia, conduct a sorting study to identify the sensory categories and important attributes to consumers of these products.Using the lexicon from 1a, conduct a Check-All-That-Apply (CATA) study of the same representative sample of ciders produced in Virginia.Based on a comparison and synthesis of the results from 1a and 1b, produce generalizable conclusions about the comparative usefulness of Sorting and CATA methods as rapid descriptive methods for the same set of samples.Compare consumer perceptions of Virginia? Cider to existing frameworks from cider manufacturers.Using a sample of ciders that represent United States Association of Cider Makers (USACM) categories, conduct consumer research with sorting and CATA to determine whether these categories are useful and applicable to Virginia ciders.Produce a rapid, standardized CATA lexicon for cider with cider-category suggestions based on CATA term clusters, for describing sensory attributes of American cider and communicating sensory attributes to consumers.Disseminate results of sensory research and "best-practice" sensory tools to Virginia cideries.Develop a simple CATA tool that cideries can use for in-house sensory evaluation.Work with Extension Specialists and agents to pilot, optimize, and disseminate CATA tool, and with scientists in Agricultural and Applied Economics Department at Virginia Tech to assess the economic impact of the CATA tool.
Project Methods
Procedures for Objective 1:To accomplish Objective 1a, we will survey ciders produced throughout Virginia. For our sample set, we will choose 30-40 ciders that represent the breadth of producers through the state as well as the USACM styles, and are regularly available in the market. We will recruit human subjects over the age of 21 (N = 70) to perform a "sorting task" on random subsets of these ciders (no subject can sort more than about 20 ciders) to determine the underlying similarities and differences between the products (Chollet, Lelièvre, Abdi, & Valentin, 2011; Chollet et al., 2014). Briefly, subjects are simultaneously presented with k ciders in opaque glasses, labeled with 3-digit codes, and in randomized order. They are instructed to sort the samples into at least 2 and no more than k - 1 groups, and to label each group of ciders with a few descriptive adjectives. All testing will be done in the Virginia Tech Sensory Evaluation Lab (VT SEL), in the Human and Agricultural Biosciences Building (HABB1, Blacksburg, VA) using standard good practices for sensory evaluation (Lawless & Heymann, 2010), including expectoration to prevent intoxication. The grouping patterns of each subject can then be transformed into dissimilarity matrices and analyzed by multivariate statistics like Multidimensional Sorting (MDS; Rencher, 2002) or DISTATIS (Abdi, Williams, Valentin, & Bennani?Dosse, 2012) to produce group consensus conclusions about patterns. Discriminant-based DISTATIS can further determine whether the USACM styles coincide with consumers' perceived categorizations, and Barycentric Text Projection (Lahne et al., 2018) will be used to analyze the relationship between the adjectives assigned to groups and individual ciders. Throughout, computational statistical approaches--e.g., bootstrapping, permutation tests, "jackknife" (Abdi & Williams, 2010; Abdi et al., 2012)--will be used to produce inference.Using the first-pass sensory lexicon produced in 1a, pursuant to Objective 1b we will conduct a Check-All-That-Apply (CATA; Meyners & Castura, 2014) assessment of the same representative set of ciders. CATA is a rapid sensory method that allows untrained consumers to accomplish descriptive tasks with a pre-defined vocabulary. Subjects simply select a set of attributes (usually with a limit of 5-6 attributes per sample) from a pre-defined list (approximately 20 attributes) for each sample, and the data is analyzed in aggregate to provide sample profiles. Untrained consumers over the age of 21 (N = 60) will be recruited to use the CATA vocabulary to assess subsets of the original sample set (so that no consumer is assessing more than 7 ciders in a single session) using a Balanced Incomplete Block Design in the VT SEL, using general good principles for sensory evaluation including expectoration to avoid intoxication. The overall data will be analyzed by Partial Triadic Correspondence Analysis (Abdi, 2017, in development) to determine whether the CATA vocabulary can significantly separate individual ciders. Discriminant Correspondence Analysis (DICA; Abdi, 2007) will be used to determine whether cider categories are significantly associated with their appropriate sensory descriptors.In Objective 1c we will compare the group and individual cider consensus plots--from the assorted multivariate analyses described above--to determine whether rapid methods like sorting with text (1a) and CATA (2a) can be adequately substituted for "gold-standard" Descriptive Analysis for providing accurate and actionable sensory profiles for a set of samples. We will not collect additional data for this objective; rather, we will combine the various results on the same samples from 1a and 1b into a single dataset and analyze it using approaches from the STATIS framework (Abdi et al., 2012). Specifically, we will compare the spatial configurations and the explanatory power of each approach to solving the problems of (1) assigning descriptive attributes to products and groups of products and (2) separating products into groups based on their sensory attributes. This analysis will add to the existing literature on rapid sensory methodologies, as to this point there have been relatively few studies that have collected these types of data on the same samples. We will publish the results of this objective in appropriate, peer-reviewed sensory journals.Procedures for Objective 2:Pursuant to Objective 2a, we will determine whether existing USACM cider category guidelines are employed by consumers through a sorting + CATA study. We will select a new sample set of ciders from Virginia comprising 10-15 previously unselected ciders from Virginia representing the current USACM cider categories (existing estimates of the Virginia cider market indicate there are sufficient ciders produced in Virginia to support this breadth of sampling: The Cyder Market LLC, 2018). Untrained consumers over the age of 21 (N = 70) will be recruited to conduct a sorting task with the CATA lexicon identified above. Briefly, consumers will follow the instructions for sorting outlined in 1a, but instead of providing their own adjectives, they will use the pre-provided lexicon to describe groups (with the option to add new descriptors to justify group formation if necessary). We will collect comments from consumers to determine whether the CATA lexicon covers the samples effectively. Using similarity measures we will determine whether existing USACM cider categories are perceived by consumers. If they are not--a possibility we consider likely--we will use clustering algorithms on both the sorting distances and the CATA descriptors to suggest new, consumer-driven cider categories.Using the results of 2a, in Objective 2b we will use both qualitative (e.g., multi-reader text analysis, Symoneaux & Galmarini, 2014) and quantitative (e.g., unguided hierarchical cluster analysis--HCA, Rencher, 2002) approaches to reanalyze the multiple datasets characterizing VA ciders generated to this point to form a final sensory-based categorization and lexicon for Virginia ciders. We will work with Extension specialists and agents located at Virginia Tech, local producers, and industry organizations like the USACM to understand how best to disseminate this information (e.g., a "cider wheel", a "map of cider", or perhaps a new type of tool).Procedures for Objective 3:For Objective 3a we will turn the CATA lexicon and tool tested in 2a and verified in 2b into a tool that can be used by cideries throughout Virginia (and beyond). To accomplish this, we will develop a set of clear instructions for how to conduct CATA on ciders in field trials (e.g., at cideries or festivals), including instructions for general good sensory practice. We will develop data entry forms in a generally accessible form and instructions for transcribing data collected using paper-and-pen collection sheets into the appropriate format. To make analysis of the CATA data accessible to cideries, we will develop a user-friendly web-application (https://www.rstudio.com/products/shiny/) hosted at Virginia Tech, linked through the FST website, to automate the analysis so that it accessible to all producers. .For Objective 3b we will work with Extension, with USACM, and with other producers to disseminate this utility widely. We expect all cideries in VA (23 cideries) to at least test the lexicon tool, and more than half (>12) to use the web-application to analyze their ciders. We will work with faculty (Dr. Clint Neill) in the Agricultural and Applied Economics Department at Virginia Tech to develop economic-impact measures that can be applied to track the long-term utility of this tool. A widely-used and agreed-upon cider lexicon and set of categories will help producers and consumers communicate and help producers to increase their profitability and sustainability in the long term.