Combining Chemical Information From Grass Pollen in Multimodal Characterization.

Area of Science:

• Analytical Chemistry
• Plant Science
• Biochemistry

Background:

• Pollen chemical composition analysis is vital for agriculture, ecology, and allergology.
• Understanding biochemical variations in pollen is crucial for various scientific disciplines.

Purpose of the Study:

• To evaluate the potential of combined spectroscopic and spectrometric methods for characterizing biochemical differences in pollen.
• To assess the classification and characterization abilities of different analytical techniques using a model system.

Main Methods:

• Analysis of *Poa alpina* pollen samples using Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, surface-enhanced Raman scattering (SERS), and MALDI-TOF MS.
• Application of ANOVA Simultaneous Component Analysis (ASCA) to separate variance sources.
• Utilizing consensus principal component analysis (CPCA) to integrate data from different methods.

Main Results:

• Spectroscopic and spectrometric methods provided complementary information on pollen chemical composition.
• ASCA successfully separated variance attributed to pollen populations and growth conditions.
• CPCA integrated data, revealing underlying global information by combining complementary chemical data.

Conclusions:

• Combined spectroscopic and spectrometric approaches effectively characterize biochemical differences in pollen.
• The study demonstrates a powerful multi-analytical strategy for detailed pollen analysis.
• Linking molecular information with phenotypic data offers potential insights into pollen chemistry's environmental influences.