Qiao Y, van Kempen T A T G
Department of Animal Science, North Carolina State University, Raleigh 27695, USA.
J Anim Sci. 2004 Sep;82(9):2596-600. doi: 10.2527/2004.8292596x.
The objective of this study was to compare three infrared spectroscopy techniques for routine evaluation of AA in animal meals. Animal meals (n = 54) with known AA contents were scanned with a near (NIRS), mid (FTIR), and Raman infrared spectrometer. For NIRS and Raman, samples were scanned "as is", whereas for FTIR, samples had to be finely ground before scanning to obtain reasonable spectra. Both FTIR and Raman data suffered from noise; for Raman, this prevented the development of calibrations. Using derivatized spectral data and a standardized outlier removal procedure, calibrations for nutritionally relevant AA could be developed that were equivalent for both NIRS and FTIR. The variation across AA tested explained (r2) by these calibrations was 70% for NIRS and 68 + 3% for FTIR. Removing spectral data between 4,000 and 2,000 cm(-1) from the FTIR data improved calibrations (P = 0.09) and explained an average of 77% of the variation with prediction errors lower than obtained with NIRS (P < 0.01). However, FTIR calibrations based on the entire or the shortened spectrum contained fewer samples than did NIRS calibrations (41 and 39 vs. 48, respectively; P < 0.01) because more samples were removed as outliers. In conclusion, Raman did not yield acceptable spectra for animal meals. For FTIR, sample preparation was more time-consuming because the samples required grinding before analysis. Using the entire mid-infrared range, FTIR calibrations were comparable to NIRS calibrations. Calibrations for FTIR were improved by eliminating wave numbers that exhibited more noise, resulting in prediction errors better than those for NIRS. Thus, FTIR has the potential to yield better calibrations for AA in animal meals than NIRS, but it requires greater care in sample preparation and scanning.
本研究的目的是比较三种红外光谱技术用于动物饲料中氨基酸(AA)的常规评估。使用近红外光谱仪(NIRS)、中红外光谱仪(FTIR)和拉曼红外光谱仪对已知AA含量的动物饲料(n = 54)进行扫描。对于NIRS和拉曼光谱,样品按原样扫描,而对于FTIR,样品在扫描前必须精细研磨以获得合理的光谱。FTIR和拉曼数据都存在噪声;对于拉曼光谱,这阻碍了校准模型的建立。使用衍生光谱数据和标准化的异常值去除程序,可以建立与NIRS和FTIR等效的营养相关AA校准模型。这些校准模型对所测试AA的变异解释率(r2),NIRS为70%,FTIR为68±3%。从FTIR数据中去除4000至2000 cm(-1)之间的光谱数据可改善校准模型(P = 0.09),平均解释77%的变异,预测误差低于NIRS(P < 0.01)。然而,基于全光谱或缩短光谱的FTIR校准模型所包含的样品数量少于NIRS校准模型(分别为41和39个,而NIRS为48个;P < 0.01),因为更多样品作为异常值被剔除。总之,拉曼光谱无法为动物饲料提供可接受的光谱。对于FTIR,样品制备更耗时,因为样品在分析前需要研磨。使用整个中红外范围,FTIR校准模型与NIRS校准模型相当。通过消除噪声较大的波数,FTIR校准模型得到改善,预测误差优于NIRS。因此,FTIR有可能为动物饲料中的AA提供比NIRS更好的校准模型,但在样品制备和扫描方面需要更谨慎。