Grain Kernel Protein Sieving Using Multi-Wavelength Spectroscopy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for sorting grains like wheat or barley based on protein content are inefficient and labor-intensive, particularly when dealing with large volumes, as analyzing individual kernels for protein content is difficult and time-consuming, leading to unnecessary sieving operations that reduce the usability of the grain.
Innovation Solution
A method and apparatus that utilize multi-wavelength spectroscopy to measure the protein content of individual kernels relative to their size, enabling the determination of optimal sieving thresholds to enhance the protein content of grain lots, thereby improving their usability for specific applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual kernels are analyzed for protein content, then protein content can be determined, but the process is difficult and time-consuming
Solution Approach 1:
The patent replaces manual mechanical analysis methods with automated optical spectroscopy systems that use light absorption characteristics to rapidly determine protein content. This substitution of mechanical/chemical analysis with optical measurement enables fast, non-contact analysis of individual kernels without the time-consuming manual processing required by traditional methods.
Solution Approach 2:
The patent measures multiple spectral parameters across different wavelengths to characterize protein content. By analyzing changes in light absorption at specific wavelengths and comparing them against reference values, the system rapidly determines protein content without physical disruption or time-consuming chemical analysis of each kernel.
2Measurement precision
If sieving operations are performed to separate kernels, then protein content can be enhanced, but unnecessary sieving reduces usability
Solution Approach 1:
The patent performs preliminary optical characterization of individual kernels to identify and classify them by protein content before any physical separation occurs. By pre-sorting kernels into categories based on their spectral properties, the system enables targeted sieving operations only where necessary, avoiding unnecessary separation processes that would reduce overall grain usability.
Solution Approach 2:
The patent applies different handling and processing strategies to different kernel populations based on their individually measured protein content. Kernels are differentiated into high-protein, medium-protein, and low-protein groups, each receiving appropriate treatment - whether that be retention, selective removal, or reclassification - thereby optimizing usability for specific purposes without unnecessary uniform sieving.
3Measurement precision
If kernels are sorted by size, then high protein fractions can be derived, but the process becomes complex
Solution Approach 1:
The patent employs a universal optical spectroscopy system that simultaneously measures multiple kernel properties including size, shape, and protein content through a single non-contact measurement process. This multi-functional approach eliminates the need for separate mechanical sorting devices for each property, reducing overall system complexity while enabling comprehensive kernel characterization and intelligent sorting decisions.
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 allows for more efficient use of grain by identifying and separating kernels based on protein content, optimizing the grain for various uses while minimizing unnecessary sieving, thus enhancing the overall value of the grain.
Implementation Method 1
A method and apparatus that utilize multi-wavelength spectroscopy to measure the protein content of individual kernels relative to their size
Data Source
Figure 1
Figure 2
Figure 3
AI summary
According to an example aspect of the present invention, there is provided a method comprising obtaining a sample of a lot of agricultural grain kernels, determining, from the sample, a kernel protein concentration as a first function of kernel size, determining, from the sample, a kernel mass as a second function of kernel size, determining, from the first function and the second function, a kernel protein mass as a third function of kernel size, and determining, from the second function and the third function, an effect of a sieving operation on a protein concentration of the lot of agricultural grain kernels.