|Pordesimo, Lester - USDA, ARS, WYNDMOOR, PA|
|Scaboo, Andrew - UNIV. OF TN, KNOXVILLE|
|Pantalone, Vincent - UNIV. OF TN, KNOXVILLE|
Submitted to: Journal of Agricultural and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 24, 2006
Publication Date: November 1, 2006
Citation: Delwiche, S.R., Pordesimo, L.O., Scaboo, A.M., Pantalone, V.R. 2006. Measurement of inorganic phosphorus in soybeans with near-infrared spectroscopy. Journal of Agricultural and Food Chemistry. 54(19):6951-6956. Interpretive Summary: The most common form of stored phosphorus in soybean [Glycine max (L.) Merr.] is phytic acid (myo-inositol-1,2,3,4,5,6-hexakisphosphate). Accounting for approximately three quarters of phosphorus of wild type seed, phytic acid has a complementary relationship with inorganic phosphorus. Because of potential nutritional deficiencies associated with food and feed with high phytic acid that is caused by a decreased absorption of essential minerals, soybean breeding programs aimed at targeting low phytate releases are currently underway. As near-infrared (NIR) spectroscopy is a common tool for macronutrient analysis in breeding programs, its application to low phytate line development is foreseen as readily accepted, provided such modeling is possible. The study described herein utilized 191 recombinant inbred soybean lines derived from an initial cross of a low-phytate experimental line (Cx1834-1-2) with a high-yielding commercial cultivar. Spectral data collection consisted of diffuse reflectance (1100-2500 nm) of ground meal and single-bean transmittance (600-1900 nm) of whole seed. For the latter, 24 beans per sample were scanned and analyzed as either individual bean spectra or averages of each sample's beans. Partial least squares regression models were developed on a random selection of approximately three quarters of the samples, with the balance reserved for model validation. Results indicate that best performance was obtained with diffuse reflectance data, producing a standard error (RMSD) of cross-validation of 263 g/kg and a validation RMSD of 248 g/kg (for constituent ranges of 334-3370 g/kg and 408-2610 g/kg, respectively). The corresponding error terms for the 24-bean average transmittance spectra equations were 1.71 and 1.79 times larger; for single bean transmittance spectra equations, they were 2.31 and 2.29 times larger. While such error terms are comparatively larger than those for common macronutrient regressions such as those for protein and oil, this technique will be useful in the screening of soybean lines for low phytic acid.
Technical Abstract: This study explored the feasibility of 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. PLS regression models were individually developed for soy meal 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 error (RMSD) was 263 g/kg and 248 g/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.