Digital Bostwick Flow Analysis for Rapid Multidimensional Viscosity Screening

Overview

The proposed digital Bostwick flow analysis upgrades the conventional Bostwick consistometer—a low-cost, familiar instrument used to measure flow in semi-solid foods—with fixed-camera video capture and image analysis. Instead of relying on a single end-point flow distance, it records the complete flow evolution and derives multiple time-dependent and spatial descriptors, including displacement over time, flow rate, and characteristics of the advancing flow front. These descriptors can be correlated with laboratory rheology to produce practical indicators of viscosity, consistency, and related flow behavior.

This approach is designed as a rapid at-line workflow for routine manufacturing environments. It offers substantially more rheological information than a traditional single-distance Bostwick reading without requiring expensive laboratory equipment. Potential applications include quality control, formulation screening, and process monitoring for products such as stirred yoghurt, gravies, sauces, and other semi-solid or particulate-containing foods.

Technical specifications

Key features:

• Uses a standard Bostwick consistometer with a fixed camera to record the entire flow process
• Image analysis extracts dynamic descriptors: time-dependent displacement, flow rate, and spatial characteristics of the advancing flow front
• Machine-learning-assisted analysis will explore combinations of descriptors to improve classification and prediction of viscosity and consistency
• Low-cost and rapid, with familiar hardware suited to routine manufacturing environments
• Staged validation will assess robustness across formulation, temperature, and process variation, and evaluate the influence of particulates

The method upgrades existing Bostwick hardware rather than requiring a completely new instrument. The digital descriptors can be correlated with rotational rheometry data to generate practical proxies for rheological parameters. The use of a fixed camera and image analysis keeps the workflow simple and at-line, while the machine-learning component can be introduced as sufficient data become available.

Technology readiness level

The concept builds on prior proof-of-concept work in stirred yoghurt, in which video-tracked Bostwick flow showed strong correlations between dynamic flow descriptors and multiple rheological parameters measured using rotational rheometry. The current development stage is early applied research, with the next phase being a staged validation and adaptation program.

The proposed validation program will characterise samples spanning acceptable and out-of-specification consistency ranges, extract dynamic and spatial flow descriptors, and evaluate them against laboratory rheology to identify robust indicators. It will then challenge the method across formulation, temperature, and process variation, and assess particulate interference and separation effects. The intended outcome is a validated at-line workflow, performance criteria, and recommendations for further automation or device integration. Limitations to be addressed include sensitivity to particulates and performance across broad formulation variation; these are not yet fully characterised.