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Non-Destructive Prediction of Protein, Starch, & Moisture using NIR Spectroscopy
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1 - Modeling Erosion of Particulate Matter
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8 - ARS Scientist Wins The Andersons Research Grant Program: Team Competition
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10 - Non-Destructive Prediction of Protein, Starch, & Moisture using NIR Spectroscopy
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12 - From Granaries to Insectaries: NIR Technology Helps Human Health
13 - Insects Play Hide and Seek in Wheat
14 - Near-Infrared Spectroscopy Detects Honey Bee Queen Insemination
15 - Sensor offers a Promising Means to Determine the Moisture Content of Grain During Storage or Transportation in Cargo Holds
16 - Pulsewave? Technology Reduces Grain to Flour at Lower Energy Costs

Starch, protein, and moisture are major constituents of the maize kernels and comprise approximately 80% of the kernel mass.  To select kernels with desirable composition traits for breeding, geneticists and breeders need seed composition information.  Standard lab methods are destructive which prohibits planting selected seeds that have the desired compositions.  A non destructive, near-infrared reflectance (NIR) spectroscopic instrument was used in this research to classify individual maize kernels.  The NIR instrument was used to determine starch, protein, and moisture content of individual maize seeds.  The NIR instrument collects both seed weight and spectral data at a rate of 4-6 s/kernel and NIR spectra alone at up to 10 kernels/s.  These results give significant improvements over previous single-kernel NIR systems.  The calibrations reported here make the NIR instrument a valuable and practical tool for high throughput measurement of the major chemical constituents in single maize kernels.

For more information contact: 
Dr. Paul Armstrong at   


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