Application of spectroscopic techniques for analysis of Faba beans

The escalating demand for health-promoting functional foods has spurred the commercial cultivation of protein-rich crops, notably Vicia faba beans. With their inherent capacity for nitrogen enrichment through symbiotic nitrogen (N2) fixation and the ability to diversify crop rotations, faba beans offer a multifaceted solution to the constraints imposed by other crop species, thereby contributing to ecosystem enrichment. To meet the rising demand for faba beans, while preserving their nutritional value, the imperative arises to employ swift and cost-effective evaluation strategies. This study systematically gathers samples from three distinct geographical regions, specifically Hammel, Gamborg, and Sejet, comprising ten varieties and two farming practices, namely organic and conventional. By scrutinizing the correlations between these agricultural parameters and the resulting chemical composition, the research aims to elucidate the influence of external factors on the nutritional quality of faba beans. The aim of this study is to determine the optimal spectroscopic approach for precise evaluation and to compare the effects of different data preprocessing methods on data quality. Three spectroscopic methods, namely Visual and Near-Infrared Spectroscopy (Vis-NIR), Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR), and Proton Nuclear Magnetic Resonance Spectroscopy (¹H NMR), are employed. These methods, when combined with other data preprocessing techniques like Multiplicative Scatter Correction, Second Derivative, and Extended Multiplicative Scatter Correction, help to a complete analysis. Principal Component Analysis (PCA) is used effectively to improve data analysis, resulting in more accurate and clear results. This multifaceted investigation underscores the profound impact of geographical origin, variety, and farming practices on the chemical/nutritional composition of Faba beans The findings show that geographical origin has a greater impact on the composition of Faba beans than variety. This is demonstrated by clear groupings in PCA analysis across spectroscopy techniques, highlighting different characteristics. For example, Sejet and Gamborg samples have significant levels of starch and moisture, but Hammel samples have higher protein levels and a valuable nutritional composition. All three employed techniques yield valuable information regarding samples composition, with each Vis-NIR, ATR-FTIR, and ¹H NMR —providing unique insights. Vis-NIR facilitates rapid, non-destructive analysis of chemical composition, moisture, and organic matter. ATR-FTIR provides detailed information on functional groups and chemical bonding specificity. All techniques require specialized equipment and trained operators. Despite this, ¹H NMR provides high-resolution structural information and hydrogen atom quantification and was used for the untargeted metabolic screening of the faba samples. The choice of spectroscopic technique depends on the specific research objectives. Additionally, the careful selection of data preprocessing methods plays a crucial role in ensuring data quality and obtaining reliable results from the data analysis.