Abstract
Thymoquinone (TMQ) is the main therapeutic constituent in black cumin (Nigella sativa L.) seeds. Conventional quantification by high-performance liquid chromatography (HPLC) is accurate but unsuitable for large-scale screening. This study evaluated the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive alternative. A multi-year dataset of 780 seed samples was analyzed, and robust calibration models were developed using modified partial least squares regression. Independent validation of a two-year calibration equation using samples from a third year yielded a high predictive performance (r(2) = 0.85; SEP = 1.18 mg g(-1)). Adding part of the samples from the third year to the calibration contributed to further improvement in the prediction of the remaining samples, demonstrating the benefits of continuous equation updates. The calibration equation proved effective for selecting genotypes with high TMQ content, particularly when expanded with samples from the third year. Spectral analysis identified key wavelengths associated with TMQ content, with wavelengths around 2106 nm and 2254 nm being the most relevant. This work demonstrates the applicability of NIRS for rapid phenotyping of TMQ content in black cumin seeds.