Cider as referred to in this study is the product of fermented apple juice that may contain 0.5% to 8.5% alcohol by volume (ABV) (Alcohol and Tobacco Tax and Trade Bureau, 2015). Cider is the fastest growing segment of the U.S. alcohol beverage market; production increased 22-fold over the last 10 years, from 775,031 gal of cider in 2007 to 17,503,535 gal in 2016 (Alcohol and Tobacco Tax and Trade Bureau, 2017). A major challenge to a sustained growth of the U.S. cider industry is the increasing labor shortages faced by apple growers across the nation (Thilmany, 2001). Cider apples are harvested by hand in the United States, and when labor is unavailable, profits are unrealized from unharvested fruit and their incurred production costs. Since 2011, the Washington State University (WSU) cider program has been evaluating the mechanization of cider apple harvest as a long-term solution to growers’ vulnerable dependency on hand labor. Alexander et al. (2016) and Miles and King (2014) have demonstrated the efficacy of mechanically harvesting ‘Brown Snout’ specialty cider apples with an over-the-row shake-and-catch small fruit harvester in terms of fruit yield and juice quality characteristics (i.e., the raw materials). Mechanical harvest imparted greater bruising to ‘Brown Snout’ fruit than hand harvest, and this physical damage resulted in significant yield loss postharvest when fruit were not immediately processed or cold-stored. The juice quality characteristics of ‘Brown Snout’ fruit did not differ because of harvest method when fully mature fruit were stored for 0, 2, or 4 weeks at 32 or 56 °F.
The present study advanced the assessment of mechanical harvest of ‘Brown Snout’ by evaluating cider quality (i.e., the finished product). Sensory evaluation of cider quality was performed using a trained panel and an e-tongue. Sensory panels, involving screened individuals trained to describe their sensory experiences using specific terminology and metrics, are often used to guide product development in contrast to consumer tasting panels that are used to test market acceptability (Meilgaard et al., 2006). Sensory panelists’ perceptions can provide an indication of ordinary consumer response and can detect minute differences in product characteristics. Sensory panelists can also become fatigued and subject to biases, and the process incurs a large time commitment and accordingly high cost. The e-tongue is a powerful tool that provides for an analytical measurement of taste profiles. E-tongues can be calibrated to consistently provide objective data, contrary to the human brain whose reaction can vary daily in response to biological, emotional, and environmental variables. Furthermore, e-tongues can evaluate samples that are potentially harmful to humans. However, e-tongues lack the streamlined integration of the human sensory system that can combine data from multiple senses to form classifications or judgments.
It was expected that machine harvest of ‘Brown Snout’ fruit would ultimately provide for a darker colored and less astringent and bitter cider than hand harvest. The physical damage imparted by mechanical harvest results in fruit that is vulnerable to enzymatic oxidation, a process that results in browning and chemical alteration of phenolics, as well as physiochemical interactions that can include binding of phenolics with insoluble solids (e.g., polysaccharides) (Guyot et al., 2008; Lea, 1990; Nicolas et al., 1994; Renard et al., 2001). The size, structure, and stereochemistry of phenolics, predominantly procyanidins in cider, are important as they influence the perception of cider’s beverage characteristic astringency and bitterness (Lea and Arnold, 1978). Also, mechanization of harvest could provide for a metallic taste as this response has been associated with food products that are oxidized and have had prolonged contact with metals (deMan, 1999). Experiments have shown machine-harvested grapes (Vitis vinifera) to contain up to six times the content of iron than hand-harvested grapes, levels that can result in a perceived metallic taste (Loubère, 1990). It was also expected that duration of ambient storage of fruit would augment the effect of harvest method as time would allow for a greater extent of oxidation and polymerization of phenolics, especially in fruit damaged during harvest. Variation in sensory perception due to year of harvest was expected as the previous mechanization studies assessing fruit yield and juice quality characteristics demonstrated a significant year effect (Alexander et al., 2016; Miles and King, 2014). Finally, the e-tongue has been shown to complement human evaluations of similar products such as wine, but the need for further optimization would not be surprising as this study is the first to involve cider (Baldwin et al., 2011). Legin et al. (2003) demonstrated the ability of an e-tongue to distinguish red and white wines from different geographical areas as well as vintages, and the ability to predict the scoring of trained panelists with 8% to 13% error.
In this 2-year study, fermented juice produced from machine-harvested and hand-harvested ‘Brown Snout’ that was ambient stored (56 °F) for 0, 2, and 4 weeks postharvest was evaluated using a trained panel and e-tongue. The sensory profiles of the ciders were compared by the harvest method, fruit ambient storage time, and year of harvest, and the complementation of human evaluations by the e-tongue in profiling cider was assessed.
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Color attributes (principal and secondary terms), reference standards, and reference intensities [low (L), medium (M), and high (H)] used by the eight trained panelists in evaluating cider apple samples on a 15-cm line scale.
Aroma, flavor, mouthfeel, and taste attributes (principal and secondary terms), reference standards, base solutions of reference standards, and reference intensities used by the eight trained panelists in evaluating apple cider samples on a 15-cm line scale.
Aftertaste attributes used by the eight trained panelists in evaluating apple cider samples on a ordinal and binary scale.