Meat Quality Spectrometer Using Merged Optical Sensors
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Solution Overview
Problem
Current methods for multi-index meat quality detection using near-infrared spectroscopy face challenges such as large equipment volume and high costs due to the need for multiple optical sensing components, and inefficiencies in building prediction models from large spectral data sets, particularly for multi-index predictions.
Innovation Solution
An integrated rapid non-destructive detection system that includes a spectrometer and an industrial tablet computer with a model embedding module, model determining module, and index prediction module, which determines the minimal resolution required for quality index prediction using chemometric methods to reduce equipment size and cost while maintaining detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple optical sensing components are used for multi-index detection, then detection accuracy is improved, but equipment volume and cost increase
Solution Approach 1:
The patent merges multiple optical sensing components into a single spectrometer that can detect multiple quality indexes (color, tenderness, water holding capacity, pH, protein content, fat content, moisture content, total viable counts, total volatile basic nitrogen, biogenic amines) simultaneously. This consolidation maintains comprehensive detection capability while reducing equipment volume and cost.
Solution Approach 2:
The spectrometer is designed with multi-functionality to perform various detection tasks for different meat quality indexes using a single device. The system uses one spectrometer to replace what would traditionally require multiple specialized optical sensing components, achieving universal detection capability across all measured parameters.
2Measurement precision
If multiple optical sensing components are used for multi-index detection, then detection accuracy is improved, but equipment cost increases
Solution Approach 1:
The patent merges multiple optical sensing components into a single spectrometer that can detect multiple quality indexes (color, tenderness, water holding capacity, pH, protein content, fat content, moisture content, total viable counts, total volatile basic nitrogen, biogenic amines) simultaneously. This consolidation maintains comprehensive detection capability while reducing equipment volume and cost.
Solution Approach 2:
The spectrometer is designed with multi-functionality to perform various detection tasks for different meat quality indexes using a single device. The system uses one spectrometer to replace what would traditionally require multiple specialized optical sensing components, achieving universal detection capability across all measured parameters.
3Measurement precision
If large amount of spectral data is used for prediction modeling, then prediction accuracy is improved, but modeling efficiency decreases
Solution Approach 1:
The patent extracts and selects only the most relevant spectral data features for building prediction models. Instead of using all available spectral data, the system identifies and incorporates only the essential spectral characteristics needed for accurate prediction, thereby maintaining high prediction accuracy while significantly improving modeling efficiency.
Solution Approach 2:
The patent changes the parameters of spectral data processing by transforming raw spectral data into processed spectral features through chemometric methods. This parameter transformation reduces the dimensionality and complexity of the data while preserving the essential information needed for accurate predictions, thus improving modeling efficiency.
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
The system enables non-destructive, cost-effective, and efficient multi-index meat quality detection by optimizing the number of detector elements and using spectral fusion to improve prediction model efficiency and stability, suitable for large-scale sample analysis.
Implementation Method 1
Near-infrared spectroscopy has been successfully used in the evaluation of meat quality in recent years
Data Source
AI summary
An integrated rapid non-destructive detection system for multi-index of meat quality comprises a spectrometer for obtaining near-infrared spectra of a sample; an industrial tablet computer, comprising: a model embedding module for storing multiple prediction models; a model determining module connected with model embedding module and configured to call prediction model; an index prediction module connected with spectrometer and model determining module for receiving near-infrared spectra and predicting index data of the sample combining with called prediction model; wherein the number of detector elements of spectrometer is determined by an ultimate minimal resolution, and a resolution of the sample is controlled to the ultimate minimal resolution during an acquisition process; which realizes automatic black-white calibration, non-destructive detection of multi-index, improves building efficiency of model, while maintaining building stability, and optimizes detection instrument volume.