可见-近红外光谱的螺旋藻生长品质指标快速无损检测

为了实现微藻生长过程品质指标的快速无损检测，提出了可见-近红外光谱技术检测不同红蓝光源组合培养条件下螺旋藻中叶绿素a和蛋白质的含量。采集不同含量红光和蓝光组合下螺旋藻在325～1 075 nm波段范围内的光谱信息，其中红光与蓝光的含量组合分别是(100%，0%)，(90%, 10%)，(70%，30%)，(50%, 50%)。同时测量叶绿素a和蛋白质的含量，建立偏最小二乘(PLS)预测模型。分别基于连续投影算法(SPA)选择了用于叶绿素a和蛋白质预测的特征波长，分别得到5个(404，440，518，662和875 nm)和4个(411，531，602和1 047 nm)特征波长。基于特征波长建立了PLS和多元线性回归(MLR)预测模型，SPA-MLR模型中叶绿素a和蛋白质预测集相关系数(correlation coefficient, R_p)分别是0.949和0.974，均方根误差(RMSEP)分别是0.018 8和0.006 74。结果表明：可见-近红外光谱检测螺旋藻藻体中叶绿素a和蛋白质含量是可行的，通过测量螺旋藻的光谱结合化学计量学方法可以实现对螺旋藻生长状况的检测。

Non-Destructive Determination of Growth Quality Indicators of Spirulina sp. Using Vis/NIR Spectroscopy

In order to detect the growth quality indicators of Spirulina sp. using a fast and on-destructive method, this study was carried out to predict chlorophyll a and protein content under different red and bule light combinations (100% red light, 90% red light+10% blue light, 70% red light+30% blue light and 50% red light+50% blue light) using Vis/NIR spectroscopy (325～1 075 nm). The chlorophyll a and protein content were predicted using partial least squares (PLS) models. Then successive projections algorithm (SPA) was used to identify effective wavelengths for chlorophyll a and protein, resulting in five (404, 440, 518, 662 and 875 nm) and four (411, 531, 602 and 1 047 nm) wavelengths, respectively. Based on the selected wavelengths, multiple linear regression (MLR) models were established, which obtained the r_p of 0.949 and 0.974, RMSEP of 0.018 8 and 0.006 74, respectively. The results demonstrated that Vis/NIR spectroscopy has the potential to be used for determination of chlorophyll a and protein content in Spirulina sp., and the growth condition can be monitored by the MLR equation and the corresponding spectral reflectance information.