Texture Analysis SolutionsBaked Beans Bulk Firmness
- Objective batch sampling for desired quality correlated to sensory panel data
- Repeatable firmness measurement process developed to benefit from a software-controlled texture analyzer
- Precision compression-shear fixture for bulk sample analysis of bite and mouthfeel
- Quantified hardness texture for clear raw ingredient supply variation and processing influence checks
A large processor of several different varieties of baked beans was looking for a way to supplement their current sensory methods. While these subjective methods are important to the company, a more objective method would add extra validation to the information already gathered from panels.
As with most food products, controlling the texture of baked beans takes constant manipulation of the processing controls to produce a product that is not only consistent, but also up to quality standards.
Changes in the incoming raw ingredients, coupled with different operators subjective view of “good” and “bad” product can often lead to inconsistencies in the final product. Controlling this subjectivity with an objective method is necessary in the manufacturing of a constant product.
Before testing, samples were allowed to equilibrate to room temperature (about 72°F) to ensure that this would not have an effect on the samples. The sample was then emptied into a colander where the sauce was rinsed off using lukewarm water. Each replication was done by putting 100 grams of product into a CS-1 Standard Shear Cell.
This cell consists of 10 blades that first compress and then shear through the product. Testing was done using a TMS-Pro Texture Analyzer with a 2500N load cell. The peak force values from this test are an indication of the firmness of the product. This gives the processor valuable information about the product that they can relate back to things like proper cook time, soak time, etc.
- Simple and quick test that gives the manufacturer an objective result that can be related to traditional sensory methods
- Able to predict how consumers will react to product when results are compared to the sensory panel data.
- Overall consistency and quality of the product can be improved by applying texture data to historical sensory data and known limits