Identification of coffee leaves using FT-NIR spectroscopy and SIMCA.

Area of Science:

• Agricultural Science
• Analytical Chemistry
• Botany

Background:

• Coffee beans are extensively studied, but coffee leaves, used for food and medicine, are less researched chemically.
• A need exists for rapid methods to identify different coffee leaf types and their characteristics.

Purpose of the Study:

• To develop a rapid screening method for identifying coffee leaf taxa.
• To differentiate coffee leaves based on taxon, aging stage, and harvest period.
• To assess the potential of FT-NIRS for coffee leaf analysis.

Main Methods:

• Fourier-Transform Near Infrared Spectroscopy (FT-NIRS) was applied to nine Coffea taxa leaves.
• Leaves were harvested over a year, dried, and ground homogeneously.
• SIMCA (Soft Independent Modeling of Class Analogy) analysis was used for spectral discrimination.

Main Results:

• FT-NIRS successfully discriminated spectral profiles across different coffee taxa.
• The method accurately identified the aging stage (mature vs. senescence) of coffee leaves (99% accuracy).
• Harvest period for mature leaves was identified with 90% accuracy.

Conclusions:

• FT-NIRS provides a rapid and effective method for classifying coffee leaf taxa.
• The technique can reliably determine the aging stage and harvest period of coffee leaves.
• This screening method has significant implications for the food and medicinal use of coffee leaves.