Year: 2022
Type: conference-abstract
Abstract: Coffee is considered a stable product with a long shelf-life, although, after roasting, it is still an effective 'chemical reactor' because of the high reactivity of its components. During storage, roasted coffee undergoes chemical and physical changes that can affect its quality. The changes in sensory properties are generally attributed to the loss of volatile compounds that are characteristic of the aroma of roasted coffee, and the appearance of oxidation products that can cause off-flavours. Storage conditions are closely related to these sensory changes. Several authors have shown that storage temperature is a fundamental parameter for maintaining the quality of the product over time [1-5]. The presence of oxygen, which is, in turn, related to packaging technology, and moisture are another important elements to consider in the deterioration/ alteration of coffee aroma. Despite their number, the studies in this field have always focused on one or two compounds in the expression of coffee staling and not on the synergism between the components of the whole coffee volatilome [2]. Due to the complexity and dynamics of the chemistry involved, coffee oxidation studies have mainly been conducted on a single species, package or condition. This study investigates the volatilome of good quality and oxidised coffee from different packaging (i.e. standard with metallic barrier and Eco-caps) by combining HS-SPME-GC-MS/FPD with a machine learning approach to define a potential fingerprint that can describe the oxidised note of roasted coffee.
Institution: University of Turin
Language: English
Topic: Coffee research and impacts
Subfield: Pharmacology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: Regione Puglia
OpenAlex ID: W7217246262