Abstract
AbstractThe soybean-derived products are among the most important agricultural products in the USA and the world. Conventional analytical methods for soybean composition analysis are both time consuming and costly. Faster and less expensive methods are required for most practical applications. To improve the accuracy, reliability and sensitivity of NIR, major advancements in instrumentation, as well as, data analysis / calibration methodology are required. Novel NIR instruments, such as DA-NIR and FT-NIR spectrometers developed in recent years have the potential for improving significantly the quantification of soybean composition at a reasonable cost. We present representative calibrations and data for intact soybean composition analysis obtained at the University of Illinois at Urbana with cutting-edge NIR instrumentation that is currently commercially available.
Highlights
IntroductionReliability and sensitivity of Near Infrared Spectroscopy (NIR), major advancements in instrumentation, as well as, data analysis / calibration methodology are required
Faster and less expensive methods are required for most practical applications
We present representative calibrations and data for intact soybean composition analysis obtained at the University of Illinois at Urbana with cutting-edge Near Infrared Spectroscopy (NIR)
Summary
Reliability and sensitivity of NIR, major advancements in instrumentation, as well as, data analysis / calibration methodology are required. Novel NIR instruments, such as DA-NIR and FT-NIR spectrometers developed in recent years have the potential for improving significantly the quantification of soybean composition at a reasonable cost. We present representative calibrations and data for intact soybean composition analysis obtained at the University of Illinois at Urbana with cutting-edge NIR instrumentation that is currently commercially available at reasonable cost. Investigate and develop methodologies for NIR spectra pre-processing and data analysis in order to improve the accuracy and reliability of NIR measurements of soybean seed composition. Develop and improve calibrations of state-ofthe-art NIR instruments for measuring rapidly, accurately, and reproducibly major soybean components that are important for food applications, such as: protein, oil, moisture, and isoflavones.
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