1980
DOI: 10.1016/s0003-2670(01)83881-2
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Correlation of objective chemical measurements and subjective sensory evaluations. wines of vitis vinifera variety 'pinot noir' from france and the united states

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Cited by 34 publications
(9 citation statements)
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“…Wine flavor is affected by the amounts of volatiles produced during fermentation [22,23]. Determination of the major volatiles, such as higher alcohols (1-propanol, isobutyl alcohol, and amyl alcohols), isoamyl acetate, 2-phenyl ethanol, and methanol revealed differences between the studied types of wines, indicating differences in their organoleptic properties ( Table 3).…”
Section: Volatilesmentioning
confidence: 99%
“…Wine flavor is affected by the amounts of volatiles produced during fermentation [22,23]. Determination of the major volatiles, such as higher alcohols (1-propanol, isobutyl alcohol, and amyl alcohols), isoamyl acetate, 2-phenyl ethanol, and methanol revealed differences between the studied types of wines, indicating differences in their organoleptic properties ( Table 3).…”
Section: Volatilesmentioning
confidence: 99%
“…As such, there has recently been a trend to unify these disparate approaches to¯avor analysis. Such an approach has been applied to the analysis of beer [12], water [23] and wine [24]. Aishima (1991) has also reviewed various studies using this approach on the¯avor analysis of orange juice, milk, soy sauce, canned tuna, carrots and cabbage [6].…”
Section: Combination Of Techniquesmentioning
confidence: 99%
“…Materials or mixtures characterized by many measurements can be classified into categories, for example, origin, by pattern recognition methods. Examples of identification or classification problems drawn from diverse areas are found in the literature: manufacturers and grades of papers (22), quarry sites of archeological artifacts (23), sources of atmospheric particulate matter (24), classification ofwines (25), determination of the origin of olive oil samples (26), identification of crude oil samples (27), selection of adsorbates for chemical sensor arrays (28), determination of the clinical status of patients from urine samples (29), classification ofcancer cells (30), the study of acute lymphocytic leukemia (31), classification ofhuman brain tissues (32), detection ofcystic fibrosis heterozygotes (33), and the classification of bacteria (34).…”
Section: Selected Applications Of Pattern Recognitionmentioning
confidence: 99%