Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur 721302, India.
Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur 721302, India.
Food Chem. 2015 Apr 1;172:880-4. doi: 10.1016/j.foodchem.2014.09.049. Epub 2014 Sep 28.
The feasibility of measuring phytic acid content in green gram (Vigna radiata) seeds was investigated by Fourier Transform Near-Infrared (FT-NIR) spectroscopic technique. Pure phytic acid standards of varying concentrations were scanned using FTNIR spectroscopy. The spectra were measured in diffused reflectance mode by keeping 100-1500 mg/100g standard of pure phytic acid in small sample cuvette. A calibration model was developed using pure phytic acid standards of varying concentrations in the near-infrared region (4000-12,000 cm(-1)). FT-NIR spectroscopy with chemometrics, using the first derivative plus vector normalisation method could predict the phytic acid content in green gram seeds samples. The developed model was validated using cross-validation technique. Maximum coefficient of determination (R(2)) value of 0.97 was obtained for the calibration model developed. The developed model was applied to predict phytic acid content in green gram seeds samples within 1-2 min. The developed procedure was further validated by recovery studies by comparing with UV spectroscopic method of phytic acid determination.
利用傅里叶变换近红外（FT-NIR）光谱技术研究了在绿豆（Vigna radiata）种子中测定植酸含量的可行性。使用 FTNIR 光谱法扫描了不同浓度的纯植酸标准品。在漫反射模式下，将 100-1500mg/100g 的纯植酸标准品放入小样品池进行测量。在近红外区域（4000-12000cm-1）使用不同浓度的纯植酸标准品建立了校准模型。使用一阶导数加向量归一化法的 FT-NIR 光谱和化学计量学可以预测绿豆种子样品中的植酸含量。使用交叉验证技术验证了所建立的模型。所建立的校准模型的最大决定系数（R2）值为 0.97。该模型可在 1-2 分钟内用于预测绿豆种子样品中的植酸含量。通过与植酸测定的紫外光谱法进行回收研究，进一步验证了所开发的程序。
