Wei Sisi, Huang Jing, Niu Ying, Tong Haibin, Su Laijin, Zhang Xu, Wu Mingjiang, Yang Yue
Zhejiang Provincial Key Laboratory for Water Environment and Marine Biological Resources Protection, College of Life and Environmental Science, Wenzhou University, Wenzhou 325035, China.
Foods. 2025 Jan 3;14(1):122. doi: 10.3390/foods14010122.
, 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 .
一种可食用海藻，通过为人体提供包括矿物质在内的必需营养物质，在我们的日常生活中发挥着至关重要的作用。检测该海藻不同生长阶段的矿物质含量，有助于实现确保产品质量、满足多样化消费者需求以及进行质量分级的目标。目前，该海藻中矿物质的测定主要依靠电感耦合等离子体质谱法和其他方法，这些方法既耗时又费力。因此，基于化学计量学，开发了一种通过近红外（NIR）光谱法快速便捷地测定该海藻中六种矿物质（即钠、镁、钙、铜、铁和钾）的方法。本研究调查了该海藻不同生长阶段矿物质的变化情况。评估了四种光谱预处理方法和三种波长选择方法，包括协同区间偏最小二乘法（SI-PLS）算法、遗传算法（GA）和竞争性自适应重加权采样法（CARS）对模型优化的影响。分别建立了钠、镁、钙、铜、铁和钾的优良CARS-PLS模型，预测均方根误差（RMSEP）值分别为0.8196×10 mg/kg、0.4370×10 mg/kg、1.544×10 mg/kg、0.9745 mg/kg、49.88 mg/kg和7.762×10 mg/kg，预测决定系数（R²）值分别为0.9787、0.9371、0.9913、0.9909、0.9874和0.9265。该海藻在幼苗期镁和钙含量较高，在成熟期铜和铁含量较低。此外，该海藻在生长阶段钠含量较高而钾含量较低。近红外结合CARS-PLS是监测该海藻不同生长阶段矿物质浓度的一种潜在替代方法，有助于方便地评估该海藻的质量并进行进一步分级。
