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We are a global food producer committed to delivering high-quality products and consistent consumer experiences through innovation in product development and manufacturing.
Food products containing meat pieces in gravy or jelly have several important visual quality attributes, including meat-piece size and shape, meat-piece color, background color, and the relative proportions of meat pieces and gravy or jelly. Variation in these attributes can affect the appearance, consistency, and overall presentation of the finished product.
Routine manufacturing quality checks currently rely heavily on visual inspection by production or quality personnel. This subjective approach makes it difficult to consistently quantify product characteristics, detect deviations, compare results across operators and production locations, and retain objective data for quality monitoring.
This creates an opportunity for automated imaging, sensing, and analytical technologies that convert product appearance into objective, repeatable, and recordable quality measurements.
We are looking for technologies capable of automatically capturing and analyzing the visual characteristics of food products containing meat pieces in gravy or jelly. Solutions may assess the product inline during processing, transfer, filling, or any other suitable stage of production. They may also assess the product using an automated online system, immediately after filling, through rapid at-line or near-line sampling.
Target visual attributes include: Meat-piece size and size distribution, Meat-piece shape and shape distribution, Meat-piece color, Background color of the gravy or jelly, Meat-piece-to-background ratio, defined as the relative proportions of meat pieces and the surrounding gravy or jelly.
- Computer-vision systems and automated imaging technologies (relevant capabilities: AI-enabled analysis, image segmentation, and object measurement)
- Digital color measurement and color-mapping systems
- Multispectral or hyperspectral imaging
- Other quantitative imaging or sensing approaches
- Two-dimensional or three-dimensional imaging
- Provides objective, repeatable, and recordable measurements or classifications of the target visual attributes, such as numerical data, distributions, deviation flags, or annotated images
- Requires minimal sample preparation and operator intervention and can be used consistently by production or quality personnel with limited specialist training
- Accurately detects deviations from an established product standard or reference range
- Suitable for, or adaptable to, routine use in a food-manufacturing environment
- Commercially available or supported by a clear pathway to an industrial proof of concept
- Automatically detects and flags defects or results outside established quality ranges
- Can be configured for different product types without extensive system redevelopment
- Captures images without requiring routine manual sampling
- Delivers an actionable result within 5 minutes
- Retains measurement data and relevant images for traceability, quality review, or model improvement
- Simultaneously assesses multiple target visual attributes
- Supports automated reporting, quality trending, and comparison across production batches or locations
- Supports continuous inline or online inspection without interrupting product flow
- Technologies requiring highly controlled laboratory imaging conditions without a credible pathway to manufacturing use
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