Chemical composition, sensory descriptive analysis, and comprehensive flavor characterization of American chestnuts (Castanea dentata)

Yang, Wenxi

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https://hdl.handle.net/2142/127484 Copy

Description

Title

Chemical composition, sensory descriptive analysis, and comprehensive flavor characterization of American chestnuts (Castanea dentata)

Author(s)

Yang, Wenxi

Issue Date

2024-12-06

Director of Research (if dissertation) or Advisor (if thesis)

Cadwallader, Keith R.

Doctoral Committee Chair(s)

Miller, Michael J.

Committee Member(s)

• Rodriguez, Braulio Macias
• Torrico, Damir Dennis

Department of Study

Food Science & Human Nutrition

Discipline

Food Science & Human Nutrition

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• American chestnut
• chemical compositions
• sensory descriptive analysis
• flavor analysis

Abstract

This study provides a first investigation into the chemical composition, sensory attributes, and flavor profile of American chestnuts (Castanea dentata) and other selected U.S.-grown chestnut cultivars. The objectives were to examine differences in chemical composition, perform sensory descriptive analysis, and systematically identify and quantify potent odorants in chestnuts. Chemical composition analysis of 4 chestnut species, including the American chestnuts, revealed significant variability among cultivars, with the American chestnut showing notably high levels of protein and fatty acids. Sensory descriptive analysis (DA) was conducted to characterize the aroma and taste profiles of American chestnuts across three sample preparation procedures (raw, roasted, and steamed). Significant differences were observed among cooking methods for most aroma attributes, highlighting unique sensory characteristics linked to each cooking process. Flavor analysis focused on identifying and quantitating potent odorants in American chestnuts across sample preparation procedures. Fifty-eight odorants were detected, with 40 potent odorants identified using aroma extract concentration analysis (AECA) and aroma extract dilution analysis (AEDA). 4-Hydroxy-2,5-dimethylfuran-3(2H)-one (HDMF) was detected as the most potent odorant (log3FD of 9), followed closely by 2-furfurylthiol (log3FD of 8). Methional, dihydromaltol, and sotolon had the next highest log3FD values of 7. These compounds were identified as the most potent odorants in both American chestnuts and Benton Harbor chestnut varieties. Twenty-nine selected odorants were accurately quantitated by stable isotope dilution analysis (SIDA), including seven highly volatile odorants by use of headspace solid-phase microextraction (HS-SPME) and 22 medium and semi-volatile odorants by direct solvent extraction combined with solvent-assisted solvent extraction (DSE-SAFE). Odor-activity values (OAVs) were calculated on the basis of the quantitation results (OAV = concentration divided by odor detection threshold). The four odorants consistently having the highest OAVs were 3-methylbutanal, methional, (E)-2-nonenal, and 2-methoxy-4-vinylphenol, though their order varied among chestnuts depending on harvest year. A PLS model built using year 3 orthonasal sensory (aroma profile) and OAV data highlighted relationships between sample preparation procedures, sensory attributes, and odorants, demonstrating that certain odorants could be linked to specific sensory characteristics. The four major aroma-forming pathways contributing to the aroma of American chestnuts were lipid oxidation, the Maillard reaction/Strecker degradation, and thermal degradation. These findings contribute to a deeper understanding of the composition, sensory, and flavor characteristics of American chestnuts, providing foundational data to support the development of new applications and further research into chestnut flavor and sensory profiles.

Graduation Semester

2024-12

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/127484

Copyright and License Information

Copyright 2024 Wenxi Yang

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