Veselá Anezka, Barros António S, Synytsya Andriy, Delgadillo Ivonne, Copíková Jana, Coimbra Manuel A
Institute of Chemical Technology, Department of Carbohydrate Chemistry and Technology, Technická 1905, 166 28 Prague 6, Czech Republic.
Anal Chim Acta. 2007 Oct 3;601(1):77-86. doi: 10.1016/j.aca.2007.08.039. Epub 2007 Aug 26.
The combination of the near infrared (NIR) and Fourier-transform infrared (FTIR) absorbance spectra (1100-2500nm and 4000-600cm(-1)) of 100 cocoa powder samples was used to build calibration models for the determination of the content of fat, nitrogen, and moisture. The samples that comprised the dataset had an average composition of 13.51% of fat, 3.77% nitrogen, and 3.98% moisture. The fat content ranged from 2.42 to 22.00%, the nitrogen from 0.88 to 4.48%, and moisture from 1.60 to 7.80%. For NIR, the relative root mean square error of cross-validation (RMSECV) was 7.0% (R(2)=0.96) for fat, 1.7% (R(2)=0.98) for nitrogen, and 5.2% (R(2)=0.94) for moisture. For FTIR, the relative RMSECV was 10.4% (R(2)=0.94) for fat and 3.9% (R(2)=0.95) for nitrogen. However, for moisture, it was not possible to build a calibration model with suitable predictability. The combination of the NIR and FTIR domains (data fusion) by outer product analysis PLS1 allowed to predict these parameters and to characterise frequencies in one domain based on the information of the other domain. This work allows to conclude that the second derivative of NIR is the recommended procedure to quantify fat, nitrogen, and moisture content in cocoa powders by infrared spectroscopy.
利用100个可可粉样品的近红外（NIR）和傅里叶变换红外（FTIR）吸收光谱（1100 - 2500nm和4000 - 600cm(-1)）建立校准模型，用于测定脂肪、氮和水分含量。构成数据集的样品平均组成为：脂肪13.51%、氮3.77%、水分3.98%。脂肪含量范围为2.42%至22.00%，氮含量范围为0.88%至4.48%，水分含量范围为1.60%至7.80%。对于近红外光谱，交叉验证的相对均方根误差（RMSECV）脂肪为7.0%（R(2)=0.96），氮为1.7%（R(2)=0.98），水分为5.2%（R(2)=0.94）。对于傅里叶变换红外光谱，脂肪的相对RMSECV为10.4%（R(2)=0.94），氮为3.9%（R(2)=0.95）。然而，对于水分，无法建立具有合适预测能力的校准模型。通过外积分析PLS1对近红外和傅里叶变换红外光谱域（数据融合）进行组合，可以预测这些参数，并根据一个域的信息表征另一个域中的频率。这项工作可以得出结论，近红外二阶导数是通过红外光谱法定量可可粉中脂肪、氮和水分含量的推荐方法。
