4.7 Article

Non-Invasive Single-Grain Screening of Proteins and Other Features by Combination of Near-Infrared Spectroscopy and Nuclear Magnetic Resonance

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AGRONOMY-BASEL
卷 13, 期 5, 页码 -

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MDPI
DOI: 10.3390/agronomy13051393

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single seed analysis; protein; magnetic resonance imaging; near-infrared spectroscopy; time-domain nuclear magnetic resonance spectroscopy

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The non-invasive analysis of seeds is of great interest in seed research and industry. In this study, the combination of near-infrared spectroscopy (NIRS) and time-domain nuclear-magnetic-resonance spectroscopy (TD-NMR) was demonstrated to be a practical approach for individual seed measurements. The method showed high accuracy in estimating nitrogen content, water content, and seed weight of individual oat grains.
The non-invasive analysis of seeds is of great interest to experimental biologists and breeders. To reach a high varietal identity and purity of seed material, it is often necessary to access features of individual seeds via the screening of mutant populations. While near-infrared spectroscopy (NIRS) and time-domain nuclear-magnetic-resonance spectroscopy (TD-NMR) are well-known in seed research and industry for bulk seed measurements, their application for individual seeds is challenging. Here we demonstrate how to overcome this limitation using a practical approach to cereal grains using oat (Avena sp.) as a model. For this, we generated a representative collection of oat seeds from the ex situ German federal gene bank, which includes wide variation in grain size, shape, and coloration. Next, we established a short experimental pipeline to exemplify how to improve the procedure for individual seed measurements. In its current state, the method is ready to use for the high-accuracy estimation of nitrogen (protein) content (R-2 = 0.877), water content (R-2 = 0.715), and seed weight (R-2 = 0.897) of individual oat grains. This work introduces the combination of NIRS and TD-NMR as an efficient, precise, and, most importantly, non-destructive analytic platform for a high throughput analysis of individual intact seeds.

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