Delwiche Stephen R, Pordesimo Lester O, Scaboo Andrew M, Pantalone Vincent R
Beltsville Agricultural Research Center, Instrumentation and Sensing Laboratory, Building 303, BARC-East, Agricultural Research Service, US Department of Agriculture, Beltsville, Maryland 20705-2350, USA.
J Agric Food Chem. 2006 Sep 20;54(19):6951-6. doi: 10.1021/jf060919n.
This study explored the feasibility of near-infrared (NIR) quantitative and qualitative models for soybean inorganic phosphorus (Pi), which is complementary to phytic acid, a component of nutritional and environmental importance. Spectra, consisting of diffuse reflectance (1100-2500 nm) of ground meal and single-bean transmittance (600-1900 nm) of whole seed, were collected on 191 recombinant inbred soybean lines. Partial least-squares regression models were individually developed for soy meal diffuse reflectance, single-bean transmittance, and averaged (24 beans/line) whole seed transmittance data. The best performance was obtained with diffuse reflectance data, in which the standard errors (rmsd) were 263 and 248 mg/kg for cross-validation and validation sets, respectively. Model accuracy was lower for the 24-bean average transmittance spectra and still lower for single beans. Despite the overall poorer modeling ability of Pi with respect to the common macronutrient NIR regressions, such as those for protein and oil, this technique holds promise for use in breeding programs.
本研究探讨了大豆无机磷（Pi）近红外（NIR）定量和定性模型的可行性，无机磷是植酸的补充成分，植酸在营养和环境方面具有重要意义。在191个重组自交大豆品系上收集了光谱数据，包括豆粕的漫反射（1100 - 2500 nm）和整粒种子的单粒透光率（600 - 1900 nm）。分别针对豆粕漫反射、单粒透光率以及平均（每行24粒）整粒种子透光率数据建立了偏最小二乘回归模型。漫反射数据的性能最佳，交叉验证集和验证集的均方根误差（rmsd）分别为263和248 mg/kg。24粒平均透光率光谱的模型精度较低，单粒种子的模型精度更低。尽管与蛋白质和油等常见常量营养素的近红外回归相比，Pi的整体建模能力较差，但该技术在育种计划中仍具有应用前景。
