Multispectral Food Taste Analysis Using Modular Testing Attachments
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for testing food taste attributes are labor-intensive, costly, and limited in frequency and scope, primarily focusing on size and appearance rather than taste characteristics, which are not readily available to consumers until after purchase.
Innovation Solution
A mobile, computer-controlled testing apparatus that uses modular attachments and multispectral testing to obtain scientific data values for attributes like acid, Brix, weight, size, and color, transforming these into consumer score values to provide a final taste score for food items, enabling objective selection based on desired taste attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of fruit followed by laboratory tests is used, then taste attributes can be measured, but the process is labor-intensive and costly
Solution Approach 1:
The patent replaces manual mechanical selection and laboratory testing with an automated imaging system using cameras and computer vision algorithms. The system captures images of individual fruits, automatically identifies and segments them, extracts taste-related features, and predicts taste attributes without human intervention, thereby reducing labor intensity and operational complexity.
Solution Approach 2:
The patent introduces computational algorithms and image processing techniques as intermediaries between the physical fruit and the taste measurement. The system uses digital images as an intermediary to capture fruit characteristics, processes these images through algorithms to extract relevant features, and generates taste predictions, replacing direct manual handling and laboratory analysis.
2Measurement precision
If laboratory testing is performed at remote locations, then taste data can be obtained, but testing frequency is limited to once or twice per growing season
Solution Approach 1:
The patent replaces remote laboratory testing with an on-site automated imaging system that can be deployed directly in the field or at storage facilities. This eliminates the need to transport samples to remote laboratories and enables frequent testing without logistical constraints, increasing productivity from once or twice per season to potentially daily or even real-time monitoring.
Solution Approach 2:
The system performs taste attribute prediction early in the growing season or at storage points before fruits are distributed, allowing growers and retailers to make informed decisions about sorting, pricing, and marketing strategies in advance, rather than waiting for end-of-season laboratory results.
3Measurement precision
If current testing methods focus on size and appearance, then those attributes can be measured, but taste characteristics remain unavailable to consumers
Solution Approach 1:
The patent uses computer vision and image processing to capture visual characteristics of fruits that correlate with taste attributes. The system analyzes color, texture, shape, and other visual features from images to predict taste properties, making taste information available through non-invasive optical measurement rather than requiring physical sampling or consumer trial.
Solution Approach 2:
The system provides feedback about taste attributes to consumers and stakeholders through the generated images and predictions. By analyzing visual features and predicting taste characteristics, the system creates an information feedback loop that allows consumers to make informed purchasing decisions based on objective taste predictions rather than subjective guesses or trial-and-error.
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
Enables frequent, cost-effective field testing of food items, providing consumers with meaningful taste information and aiding growers, wholesalers, and retailers in selecting crops or products with desired taste attributes, enhancing consumer experience and operational efficiency.
Implementation Method 1
a multispectral tester coupled to the universal attachment and structured to receive the substance from the universal attachment and test the substance to output scientific values
Data Source
AI summary
One embodiment relates to a system that includes a modular testing attachment comprising at least one of a crusher attachment, a squeezer attachment, and a blender attachment, the modular testing attachment configured to obtain a substance from food or crop products, a universal attachment coupled to the modular testing attachment and structured to receive and advance the substance from the food or crop products, a multispectral tester coupled to the universal attachment and structured to receive the substance from the universal attachment and test the substance to output scientific values, and a computing system operably coupled to the modular testing attachment and the multispectral tester and configured to selectively or automatically operate components thereof