Automation and AI-assisted colony enumeration: Supporting next-generation laboratory and microbiological workflows

By Benjamin Brand, AI Solutions Manager

ALS Environmental, Australia & New Zealand 

Commercial laboratories across Australia and Aotearoa/New Zealand are navigating an increasingly complex operational landscape, shaped by growing sample volumes, tighter turnaround expectations and greater emphasis on traceability and delivery across networks. 

These pressures are driving broader conversations around sustained investment in laboratory automation and the future of smart laboratories, critical infrastructure to meet the demands of modern environmental testing.

Our ACED colony counter, currently deployed in ALS laboratories across Australia, is a practical example of this shift. Using machine vision, it enables task-intensive datasets to be handled efficiently, enabling our analysts to focus on high-level interpretation and review to enhance the environmental decision-making process.

The challenge with traditional colony counting workflows

Microbiological analysis remains a critical component of both environmental monitoring and public health assessment. Colony counting techniques are routinely applied across drinking water and wastewater programs, air monitoring and soil microbiology to quantify bacterial and fungal growth.

Under traditional laboratory workflows, colony interpretation relies heavily on manual review and analyst judgement. While highly effective, this process can introduce variability between operators, particularly in situations where colony morphology is complex, overlapping growth occurs or laboratories are managing high sample throughput. At scale, even marginal inconsistencies can have implications for data quality and comparability.

As laboratories modernise analytical workflows, automation and computer vision technologies are increasingly being explored as tools to help improve consistency, scalability and workflow efficiency.

The ACED colony counter

The ACED colony counter uses high-resolution imaging and algorithm-assisted interpretation to identify and enumerate microbial colonies on agar plates. The systems are capable of rapidly analysing plates while applying standardised interpretation parameters across large sample batches.

Its primary value lies not in throughput alone, but in standardisation. Each agar plate is assessed against defined interpretation parameters, applied uniformly regardless of analyst, laboratory location or operational demand. For clients managing large or complex monitoring programs, whether in drinking water compliance, wastewater management, healthcare or environmental assessment, this level of reproducibility represents a meaningful improvement in the quality and reliability of scientific results.

It is important to note that ACED’s role is supportive. Rather than supplanting technical expertise, it reinforces the basics that governance and accountability is what’s most important. Analytical oversight and quality review remain integral to ALS workflows. The ACED system addresses the repetitive aspects of manual plate counting, replacing variability with consistent and reliable testing at scale.

Supporting a broad range of clients and monitoring programs

Automated microbiological workflows are relevant across a wide range of sectors and end-users. This includes water authorities and councils managing drinking water and wastewater compliance programs, occupational health specialists, healthcare networks monitoring hygiene standards and environmental consultants supporting contaminated land or groundwater programs. All share a common interest in consistent and traceable microbiological data.


Looking ahead

As monitoring programs continue to expand in scale and complexity, advanced laboratory systems are set to play an increasing role in supporting compliance with environmental regulations and public health reporting requirements.

At ALS, technologies such as the ACED colony counter reflect the growing integration of high-quality testing services with smarter digital capabilities to support decision-making across the industries we serve.


About Benjamin Brand 

Benjamin Brand is the AI Solutions Manager at ALS Environmental in Australia and New Zealand, where he leads the development and deployment of AI-assisted analytical tools and digital laboratory solutions across the Environmental business in the region.


About ALS

ALS is a global leader in testing, providing comprehensive testing solutions to clients in a wide range of industries from contaminated land to resource recovery. Using state-of-the-art technologies and innovative methodologies, our dedicated teams deliver high-quality testing services and personalised solutions supported by local, site-specific expertise. We help our clients leverage the power of data-driven insights for a safer and healthier world.

This article was submitted as a sponsored feature to e-cronicle.

Disclaimer

The views and information in this publication are those of the author and not the Australasian Land & Groundwater Association Ltd (ALGA), which acts solely as publisher. This publication does not constitute legal advice, and no warranty is given as to its accuracy or completeness. To the extent permitted by law, ALGA and the author accept no liability. Readers should seek independent professional advice if required.