College of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, 210095 Nanjing, China.
School of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, 214122 Wuxi, China.
Food Chem. 2015 Jan 15;167:264-71. doi: 10.1016/j.foodchem.2014.06.117. Epub 2014 Jul 5.
Visible and near-infrared spectra in interactance mode were acquired for intact and sliced beet samples, using two portable spectrometers for the spectral regions of 400-1100 nm and 900-1600 nm, respectively. Sucrose prediction models for intact and sliced beets were developed and then validated. The spectrometer for 400-1100 nm was able to predict the sucrose content with correlations of prediction (rp) of 0.80 and 0.88 and standard errors of prediction (SEPs) of 0.89% and 0.70%, for intact beets and beet slices, respectively. The spectrometer for 900-1600 nm had rp values of 0.74 and 0.88 and SEPs of 1.02% and 0.69% for intact beets and beet slices. These results showed the feasibility of using the portable spectrometer to predict the sucrose content of beet slices. Using simple correlation analysis, the study also identified important wavelengths that had strong correlation with the sucrose content.
采用两种便携式分光光度计,分别采集了完整和切片甜菜的漫反射可见近红外光谱,光谱范围分别为 400-1100nm 和 900-1600nm。建立并验证了完整和切片甜菜中蔗糖的预测模型。400-1100nm 分光光度计对完整和切片甜菜的蔗糖含量进行预测,其预测相关系数(rp)分别为 0.80 和 0.88,预测标准误差(SEP)分别为 0.89%和 0.70%。900-1600nm 分光光度计的 rp 值分别为 0.74 和 0.88,SEP 值分别为 1.02%和 0.69%。结果表明,便携式分光光度计可用于预测切片甜菜的蔗糖含量。通过简单相关分析,确定了与蔗糖含量具有强相关性的重要波长。