Qualitative properties of roasting defect beans and development of its classification methods by hyperspectral imaging technology

Food Chem. 2017 Apr 1:220:505-509. doi: 10.1016/j.foodchem.2016.09.189. Epub 2016 Sep 29.

Abstract

Qualitative properties of roasting defect coffee beans and their classification methods were studied using hyperspectral imaging (HSI). The roasting defect beans were divided into 5 groups: medium roasting (Cont), under developed (RD-1), over roasting (RD-2), interior under developed (RD-3), and interior scorching (RD-4). The following qualitative properties were assayed: browning index (BI), moisture content (MC), chlorogenic acid (CA), trigonelline (TG), and caffeine (CF) content. Their HSI spectra (1000-1700nm) were also analysed to develop the classification methods of roasting defect beans. RD-2 showed the highest BI and the lowest MC, CA, and TG content. The accuracy of classification model of partial least-squares discriminant was 86.2%. The most powerful wavelength to classify the defective beans was approximately 1420nm (related to OH bond). The HSI reflectance values at 1420nm showed similar tendency with MC, enabling the use of this technology to classify the roasting defect beans.

Keywords: Coffee; Hyperspectral imaging; Moisture content; Qualitative properties; Roasting defects.

MeSH terms

  • Alkaloids / analysis
  • Caffeine / analysis
  • Chlorogenic Acid / analysis
  • Coffea / chemistry*
  • Coffea / classification*
  • Cooking / instrumentation
  • Cooking / methods*
  • Discriminant Analysis
  • Hot Temperature
  • Image Processing, Computer-Assisted / methods*
  • Least-Squares Analysis

Substances

  • Alkaloids
  • Chlorogenic Acid
  • Caffeine
  • trigonelline