Department of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences, 901 83 Umeå, Sweden.
TARI - Faroe Seaweed, FO-100 Tórshavn, Faroe Islands.
Food Chem. 2023 Mar 15;404(Pt B):134700. doi: 10.1016/j.foodchem.2022.134700. Epub 2022 Oct 19.
Seaweed is considered a potentially sustainable source of protein for human consumption, and rapid, accurate methods for determining seaweed protein contents are needed. Seaweeds contain substances which interfere with common protein estimation methods however. The present study compares the Lowry and BCA protein assays and protein determination by N-ratios to more novel spectroscopic methods. Linear regression of the height or the integrated area under the Amide II band of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) was used to predict seaweed protein with good prediction performance. Partial least squares regression (PLSR) was performed on both DRIFTS and near-infrared (NIR) spectra, with even higher prediction accuracy. Spectroscopy performed similar to or better than the calculated N-ratio of 4.14 for protein prediction. These spectral prediction methods require minimal sample preparation and chemical use, and are easy to perform, making them environmentally sustainable and economically viable for rapid estimation of seaweed protein.
海藻被认为是人类食用的潜在可持续蛋白质来源,因此需要快速、准确的方法来测定海藻蛋白含量。然而,海藻中含有干扰常用蛋白质测定方法的物质。本研究比较了 Lowry 和 BCA 蛋白测定法以及 N-比法与更新型的光谱方法。利用漫反射红外傅里叶变换光谱(DRIFTS)酰胺 II 带的高度或积分面积的线性回归来预测海藻蛋白,具有良好的预测性能。对 DRIFTS 和近红外(NIR)光谱进行偏最小二乘回归(PLSR),具有更高的预测准确性。光谱法的预测结果与计算得到的 4.14 的 N-比法相当,甚至更好,可用于预测蛋白质。这些光谱预测方法所需的样品制备和化学使用量最少,易于操作,因此在快速估计海藻蛋白方面具有环境可持续性和经济可行性。