How the variance of some extraction variables may affect the quality of espresso coffees served in coffee shops

J Sci Food Agric. 2016 Jul;96(9):3023-31. doi: 10.1002/jsfa.7472. Epub 2015 Nov 2.

Abstract

Background: To improve the quality of espresso coffee, the variables under the control of the barista, such as grinding grade, coffee quantity and pressure applied to the coffee cake, as well as their variance, are of great importance. A nonlinear mixed effect modeling was used to obtain information on the changes in chemical attributes of espresso coffee (EC) as a function of the variability of extraction conditions.

Results: During extraction, the changes in volume were well described by a logistic model, whereas the chemical attributes were better fit by a first-order kinetic. The major source of information was contained in the grinding grade, which accounted for 87-96% of the variance of the experimental data. The variability of the grinding produced changes in caffeine content in the range of 80.03 mg and 130.36 mg when using a constant grinding grade of 6.5.

Conclusion: The variability in volume and chemical attributes of EC is large. Grinding had the most important effect as the variability in particle size distribution observed for each grinding level had a profound effect on the quality of EC. Standardization of grinding would be of crucial importance for obtaining all espresso coffees with a high quality. © 2015 Society of Chemical Industry.

Keywords: barista; espresso coffee; physical-chemical analyses; variables.

Publication types

  • Comparative Study

MeSH terms

  • Algorithms
  • Caffeine / analysis
  • Coffea / chemistry*
  • Coffee / chemistry*
  • Cooking / instrumentation
  • Cooking / standards
  • Food Handling* / instrumentation
  • Food Handling* / standards
  • Food Quality*
  • Guidelines as Topic
  • Hydrogen-Ion Concentration
  • Italy
  • Kinetics
  • Logistic Models
  • Mechanical Phenomena
  • Models, Chemical*
  • Particle Size
  • Pressure
  • Quality Control
  • Reproducibility of Results
  • Restaurants*
  • Seeds / chemistry*
  • Workforce

Substances

  • Coffee
  • Caffeine