Monitoring the Concentrations of Na, Mg, Ca, Cu, Fe, and K in at Different Growth Stages by NIR Spectroscopy Coupled with Chemometrics.

, an edible seaweed, plays a crucial role in our daily lives by providing essential nutrients, including minerals, to the human body. The detection of mineral content during different growth stages of benefits the goals of ensuring product quality, meeting diverse consumer needs, and achieving quality classification. Currently, the determination of minerals in primarily relies on inductively coupled plasma mass spectrometry and other methods, which are time-consuming and labor-intensive. Thus, a rapid and convenient method was developed for the determination of six minerals (i.e., Na, Mg, Ca, Cu, Fe, and K) in via near-infrared (NIR) spectroscopy based on chemometrics. This study investigated the variations in minerals in from different growth stages. The effects of four spectral pretreatment methods and three wavelength selection methods, including the synergy interval partial least squares (SI-PLS) algorithm, genetic algorithm (GA), and competitive adaptive reweighted sampling method (CARS) on the model optimization, were evaluated. Superior CARS-PLS models were established for Na, Mg, Ca, Cu, Fe, and K with root mean square error of prediction () values of 0.8196 × 10 mg kg, 0.4370 × 10 mg kg, 1.544 × 10 mg kg, 0.9745 mg kg, 49.88 mg kg, and 7.762 × 10 mg kg, respectively, and coefficient of determination of prediction () values of 0.9787, 0.9371, 0.9913, 0.9909, 0.9874, and 0.9265, respectively. demonstrated higher levels of Mg and Ca at the seedling stage and lower levels of Cu and Fe at the maturation stage. Additionally, exhibited higher Na and lower K at the growth stage. NIR combined with CARS-PLS is a potential alternative for monitoring the concentrations of minerals in at different growth stages, aiding in the convenient evaluation and further grading of the quality of .