Seed Sorting Using Near-Infrared Spectroscopy for Anthocyanin Detection
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Solution Overview
Problem
Existing methods for sorting blue and white seeds in the BLue Aleurone hybrid cereal system face inefficiencies due to environmental factors causing color degradation and the inability to reliably distinguish between single and double blue seeds, leading to impurities and economic losses in seed breeding and processing.
Innovation Solution
The use of near-infrared (NIR) spectroscopy to determine the presence and concentration of organic colorants like anthocyanins in seeds, allowing for precise sorting and differentiation between single blue, double blue, and white seeds without relying on visual light, using specific wavelength ranges and spectroscopic methods such as PCA, PLS-R, and SVM models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mechanical separation using optical cameras detecting visual light spectrum is used, then seed sorting can be performed, but separation efficiency is poor and multiple rounds are required due to color degradation and mis-coloration under environmental conditions
Solution Approach 1:
The patent changes the detection parameter from visual light spectrum to near-infrared (NIR) spectrum. Specifically, it uses NIR wavelengths (700-2500 nm) to detect anthocyanin content in seeds, which provides stable absorption characteristics regardless of environmental conditions. This parameter change enables reliable differentiation between blue and white seeds based on anthocyanin concentration without being affected by color fading or mis-coloration that plagues visual inspection methods.
Solution Approach 2:
The patent replaces the mechanical/optical camera-based sorting system with a spectroscopic detection system using near-infrared radiation. Instead of relying on visual light reflection and camera image processing, the system uses NIR spectrometry to measure anthocyanin absorption spectra, providing more reliable and automated seed classification in a single pass.
2Device complexity
If visual light spectrum detection is used for seed sorting, then the process is simple, but it cannot reliably distinguish between single blue, double blue, and white seeds due to color loss and environmental factors
Solution Approach 1:
The patent transitions from simple visual light detection to near-infrared spectroscopic detection. The NIR method measures absorption at specific wavelengths (particularly around 530 nm for anthocyanins) to determine precise anthocyanin content. This enables the system to distinguish between single blue seeds (lower anthocyanin), double blue seeds (higher anthocyanin), and white seeds (no anthocyanin) based on quantitative spectral data rather than qualitative color appearance.
3Reliability
If multiple rounds of separation are performed to achieve pure seed pools, then seed purity increases, but time consumption and processing complexity increase
Solution Approach 1:
The patent performs preliminary action by using NIR spectroscopy to achieve accurate seed classification in a single sorting pass. The method pre-identifies and separates all seed types (white, single blue, double blue) based on their anthocyanin content before any subsequent processing. This eliminates the need for multiple separation rounds, reducing processing time while maintaining high seed purity through the reliable spectral detection method.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables high-precision sorting and quality control, ensuring seed purity and meeting market standards by accurately detecting and distinguishing between different seed types based on anthocyanin content, even under conditions where visual inspection is compromised.
Implementation Method 1
obtain a near infrared (NIR) spectrum of at least a subset of the sample; determining presence of an organic colorant in at least the subset of the sample based on the obtained NIR spectrum
Data Source
AI summary
The present invention relates to a method for categorizing/sorting seeds, the method comprising the steps of: providing (S11) a sample including at least one seed; obtaining (S12) a near infrared, NIR, spectrum of at least a subset of the sample; determining (S14) presence of an organic colorant in at least the subset of the sample based on the obtained NIR spectrum; and categorizing/sorting (S19) at least the subset of the sample based on the determination. Based on this, mis-colored white seed and blue seed with a fading blue color can be properly categorized. Further, it is also possible to distinguish between single blue and double blue seed.