AI Technology and the Lab of the Future

In 2022, Agilent announced its acquisition of advanced artificial intelligence (AI) technology developed by Virtual Control, an AI and machine learning software developer that creates innovative analysis solutions in lab testing. Agilent will integrate the software, known as ACIES, into its industry-leading gas chromatography and mass spectrometry (GS/MS) platforms to improve the productivity, efficiency and accuracy of high-throughput labs the company serves around the world.

ACIES automates the labour-intensive task of gas chromatography/mass spectrometry data analysis improving efficiency in the laboratory workflow, from sampling to reporting. Agilent will integrate the technology into its MassHunter software package for LC/MS and GC/MS instruments.

 

Digital labs

This move by Agilent signals that the digital age is very much here for laboratories. Science has always driven the world forward and now it will do the same for laboratories.

The lab of the future is a concept built on the foundation of digitalised labs. It encompasses smart technological workflow systems that are connected and capable of collecting vast amounts of data via integrated automation.

A digitalised lab should be considered a more advanced lab as it has more access to data. With data being key to transforming science, increasing amounts of data generated in any lab, let alone a digitally connected lab, could be a game-changer – but only if it’s collected and synthesised into information and knowledge that is useful.

The digital environment (i.e., paperless work in an electronic format) capitalises on digitalisation. It incorporates all of the necessary instrumentation for complete data analysis and enables the full value of the data for decision-making. The ability to monitor operations and provide more sophisticated insights is a core reason for introducing AI into the operational lab environment.

 

 

Transforming science

Artificial intelligence (AI) is often defined as the ability of a machine to learn how to solve cognitive challenges. However, in the context of scientific methodology and laboratory interconnectivity, AI is starting to be used for capturing data to model human observation and decision-making processes.

Taken forward, connecting all instruments in a lab via AI enables the opportunity for an even more astute understanding of the interactions between technology and also users, potentially providing an all-inclusive view of all laboratory operations.

Accessing this powerful source of information will become a necessary component of scientific productivity. This is an inevitable next step in creating lab management systems that are so efficient and provide knowledge that is so valuable that only AI will be able to produce them.

AI, coupled with universal sensing capabilities to detect and monitor a range of variables, e.g., an instrument’s power draw, enables companies to realise certain operational and financial benefits to their business and plan for the future. Through high-quality and readily available insights, AI enables the simultaneous monitoring of all equipment usage in the lab and holistic capacity tracking.

Watch our webinar on Industrialising High-Throughput Glycoproteomics Using AI for Clinical Use

 

Staying competitive in a competitive world

Globally, scientific innovation is accelerating, so labs need to consider the technology investments required to become digitally enabled in order to keep up and stay competitive. We live in a data-driven world, so scientific laboratories must fundamentally transform how they create, manage, and effectively use all the data that is generated in their lab ecosystem. Achieving and sustaining a competitive edge in a world of constant change will require the continual transformation of lab operations and scientific data management. This will be the first and most important step toward becoming a truly digitalised lab.

 

Standardising honey fingerprinting methods

Although previous work has been done developing case studies for fingerprinting foodstuffs, including honey, the approaches among laboratories have been different regarding sample preparation and instrumental conditions. There are also differences in terms of data processing and analysis. As a result, two laboratories analysing the same sample may obtain slightly different results. Ideally, developing a standardised fingerprinting method that could be used across all LC/MS-based workflows, enabling the same testing technique to be used across multiple laboratories, would be optimal and where future work is aimed.

Read our article on Fingerprinting Honey to Ensure Purity

When addressing the issues of food safety, product quality, and authenticity, each may be governed by separate sets of regulations. For example, looking at the residues of contaminants in honey, such as pesticides, there may be differences globally. Countries may have their restrictions for the maximum limit for specific compounds. Contaminants are a part of the picture when considering fingerprinting for honey, but permitted levels may vary between countries.

Additionally, as samples come from the field to the lab for testing, there is potential interest in reversing this and bringing the lab out into the field instead. This interesting but not yet recognised capability would enable regulators and the global food industry to respond more quickly to honey contamination and food fraud.

Step into the future, elevate your business and talk to our team of experts about how you can improve the productivity, efficiency and accuracy of your lab.

Food and Cannabis Elemental Analysis Part 2: Elemental Sample Prep for the Food and Agriculture Lab – Optimizing Your System for High Matrix Samples

Trace elemental analysis of foods and cannabis products is essential to ensure that products are suitable for consumption. The analysis of minerals and additional trace elements is also important because it provides labelling information that is required when these products are used as nutritional.

Agilent has presented a webinar series that focuses on elemental sample preparation to optimise high matrix samples in the food and agriculture testing space.

 

Part 1

We will cover the entire Agilent elemental portfolio. Each of the different instruments’ strengths and how they meet the challenges that food and cannabis labs have.

 

Part 2

We will focus on preparing your samples, including microwave digestion. We will also cover how to optimize your system for high matrix samples and a diverse sample set.

 

Part 3

We will put it all together, with running samples live in the lab. We will also share additional tips and tricks for obtaining excellent analytical results in these difficult matrices.

This focused information on spectroscopy applications is valuable for the emerging cannabis market as well as analysts who are seeking to master skills for food testing.

 

Speakers

Jenny Nelson, PhD
Application Scientist
Agilent Technologies, Inc.

Jenny Nelson received her Ph.D. in Analytical Chemistry from the University of Cincinnati in 2007, and her MBA from Saint Mary’s College of California in 2011. Currently, Jenny is an Application Scientist for the Life Science and Chemical Analysis team at Agilent Technologies, joining in 2012 (with a step away in 2019). Jenny is also an Adjunct Professor in the Department of Viticulture and Enology at the University of California, Davis, since 2013. Jenny has been very active with AOAC and ASTM over the past eight years, serving on expert review panels, chairing committees, and volunteering to develop new methods needed by the industry. Jenny has extensive experience in operating and method development for Inductively Coupled Plasma Mass Spectroscopy (ICP-MS), Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), Microwave Plasma Atomic Emission Spectroscopy (MP-AES). Jenny has broad knowledge and experience in different speciation analysis for many sample matrices using GC-ICPMS and LC-ICPMS. As well as vast experience with sp-ICP-MS for many applications.

 

Greg Gilleland
Application Scientist
Agilent Technologies, Inc.

Greg began his spectroscopy career in 1987 in Colorado, working at a series of environmental labs. After 14 years working in the world of commercial environmental labs, he moved on to a spectroscopy instrument manufacturer where he performed service and sales functions over the course of 11 years. He has been with Agilent Technologies, Inc., since 2012 in the role of Application Scientist for ICP-OES, MP-AES and AA products.

 

Mark Kelinske
Application Scientist
Agilent Technologies, Inc.

Mark Kelinske is an Applications Chemist with Agilent Technologies, specializing in advanced ICP-MS and ICP-MS/MS techniques. He received his undergraduate and graduate degrees from Texas A&M University in College Station, TX. Prior to Agilent, Mark was a senior research scientist and research group manager with Southern Research Institute in Birmingham, AL, where he focused on low-level analytical chemistry, method development, and research program management.

 

Chris Conklin
Atomic Spectroscopy Product Specialist
Agilent Technologies, Inc.

With a degree from the University of Wisconsin – Eau Claire, Chris worked in, and lead, a quality control lab testing fine chemicals ranging from reagent grade to high purity. Over the course of 12 years in that role, Chris has run a variety of atomic elemental instruments and techniques including AA, ICP-OES, and ICP-MS. As a result, he has seen most of the periodic table in its elemental form and overcome the associated interferences. In 2018, Chris brought that knowledge and experience to his current role with Agilent as the Product Specialist for Atomic Spectroscopy supporting AA, MP-AES, and ICP-OES for the Eastern US.

 

Register and watch on demand >

 

Fingerprinting Honey to Ensure Purity

How pure is that honey in your jar?

Although there’s a rising demand for honey, the honey bee population is also under threat. Another not-so-sweet issue is the number of products labelled as honey on retail shelves that don’t meet the criteria to be classified as pure honey.

The term “adulterated honey” means any honey to which has been added honeydew, glucose, dextrose, molasses, sugar, sugar syrup, inverted sugar, or any other similar product or products other than the nectar of floral exudations of plants gathered and stored in the comb by honey bees.

Food fraud is a significant concern for consumers and producers, with research indicating that fraud accounts for up to 25% of all globally reported food safety incidents. The growing demand for food authenticity means consumers regularly pay a premium for organic and sustainably produced goods like honey. Fraudsters have been flooding markets with adulterated, low-quality, or mislabeled foodstuffs, damaging the livelihoods of legitimate businesses and potentially risking consumer health.

 

Increasing demand

Consumers have become quite specific in their demand for honey, focusing on unifloral honey or monofloral honey obtained predominantly from bees that feed on a single species of plant flowers. This results in a unique colour, flavour, and fragrance exclusive to each type of unifloral honey. As consumers are willing to pay more for these products, protections must ensure that they purchase what they expect.

According to data from the Food and Agriculture Organization of the United Nations, China, Mexico, Russia, Turkey, and the United States are among the major honey-producing countries accounting for approximately 55 per cent of world production. The most common form of adulteration involves extending or diluting honey with other less expensive sweeteners. Commonly identified extenders are corn, cane, and beet syrups.

 

Testing for authenticity to mitigate honey fraud

Global e-commerce is placing honey sales outside regulatory oversight more frequently—a trend expected to continue. This, combined with increased fraudulent activities, makes tackling the problem critical. This is why it is important to identify these substances quickly, efficiently, and consistently. The food industry requires analytical instruments and testing techniques to consistently and rapidly analyze food and identify trace chemicals.

Analytical testing is essential for assessing food authenticity, which is important to protect consumers’ health, the brand, and producers’ income. Testing is a necessary part of an overall strategy to mitigate fraud risk, and methods for authenticity testing are rapidly evolving, with innovative technologies now available for developing robust food testing techniques.


Agilent 1290 Infinity II LC System

For example, it has been demonstrated in recent years that coupling high-performance liquid chromatography with quadrupole time-of-flight (LC/Q-TOF), such as the Agilent 1290 Infinity II LC System with Agilent 6545 LC/Q-TOF, provides a sensitive method to reveal the chemical composition of honey samples. Using this method with a non-targeted approach enables the identification of new types and sources of fraud through the chemical markers in the honey, highlighting which kind of fraudulent activity is occurring. Since this technique evaluates multiple markers in honey to determine authenticity, it is very difficult for fraudsters to cheat by adding one or a few adulterants. This innovative technique is called honey fingerprinting.


Agilent 6545 LC/Q-TOF

 

Determining honey’s unique chemical composition

Honey fingerprinting is the practice of using a suitable technique to record as much information as possible on the chemical composition of a particular honey sample. In the same way, a human fingerprint is unique to individuals, this fingerprinting method unlocks and records the unique molecular composition of authentic honey samples. This enables the mapping of food components in an unprecedented fashion that will revolutionize how honey is regulated for quality, safety, and authenticity.

Utilizing a non-targeted workflow begins with identifying other compounds, including pesticides, molecules that indicate freshness, like a compound called HMF (which suggests thermal processing or age if present in high numbers), and phenolic compounds, which are related to the floral origin of honey. The advantage of using LC/Q-TOF for this technique is its efficiency: higher molecular/trace information levels can be obtained from just one sample in less time versus targeted methods focusing on just a few parameters.

 

Standardising honey fingerprinting methods

Although previous work has been done developing case studies for fingerprinting foodstuffs, including honey, the approaches among laboratories have been different regarding sample preparation and instrumental condition. There are also differences in terms of data processing and analysis. As a result, two laboratories analyzing the same sample may obtain slightly different results. Ideally, developing a standardized fingerprinting method that could be used across all LC/MS-based workflows, enabling the same testing technique to be used across multiple laboratories, would be optimal and where future work is aimed.

When addressing the issues of food safety, product quality, and authenticity, each may be governed by separate sets of regulations. For example, looking at the residues of contaminants in honey, such as pesticides, there may be differences globally. Countries may have their own restrictions for the maximum limit for specific compounds. Contaminants are a part of the picture when considering fingerprinting for honey, but permitted levels may vary between countries.

Additionally, as samples come from the field to the lab for testing, there is potential interest in reversing this and bringing the lab out into the field instead. This interesting but not yet recognised capability would enable regulators and the global food industry to respond more quickly to honey contamination and food fraud.

 

Taking a global approach to ensure honey purity

As the food supply chain becomes increasingly globalized, raising the opportunity for food fraud, experts predict that testing, such as those described above, will become more accessible, increasingly automated, and easier to perform. Fingerprinting methods—in which the entire molecular profile of food can be obtained—will be a feature of future fraud prevention and identification systems.

A positive step forward is the focus on building a library of authentic honey samples and making it an accessible, open database so that honey fingerprinting information is available across multiple stakeholders in the global supply chain. With increased knowledge, more scientists will be able to adopt techniques such as LC/Q-TOF and could also use this testing for other types of food—for example, maple syrup.

The ultimate goal is for food testing laboratories to confidently measure contaminants that threaten the global food chain and tackle food fraud head-on to ensure that consumers can access authentic and safe honey.

(This article has been modified from its original appearance on the Agilent website)

Food and Cannabis Elemental Analysis Part 3: Elemental Analysis, Putting it All Together – Agilent 7850 ICP-OMS with MassHunter 5.1 Live Demo & Agilent 5900 ICP-OES with ICP Expert Live Demo

This will be a three week Food and Cannabis elemental analysis workshop. We will cover a lot of great information during these three weeks.

Part 3: We will put it all together, with running samples live in the lab.  We will also share additional tips and tricks on obtaining excellent analytical results in these difficult matrices.

 

Speakers

Jenny Nelson, PhD, Application Scientist, Agilent Technologies, Inc.

Jenny Nelson received her Ph.D. in Analytical Chemistry from the University of Cincinnati in 2007, and her MBA from Saint Mary’s College of California in 2011. Currently, Jenny is an Application Scientist for the Life Science and Chemical Analysis team at Agilent Technologies, joining in 2012 (with a step away in 2019). Jenny is also an Adjunct Professor in the Department of Viticulture and Enology at the University of California, Davis, since 2013. Jenny has been very active with AOAC and ASTM over the past eight years, serving on expert review panels, chairing committees, and volunteering to develop new methods needed by the industry. Jenny has extensive experience in operating and method development for Inductively Coupled Plasma Mass Spectroscopy (ICP-MS), Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), Microwave Plasma Atomic Emission Spectroscopy (MP-AES). Jenny has broad knowledge and experience in different speciation analysis for many sample matrices using GC-ICPMS and LC-ICPMS. As well as vast experience with sp-ICP-MS for many applications.

Greg Gilleland, Application Scientist, Agilent Technologies, Inc.

Greg began his spectroscopy career in 1987 in Colorado, working at a series of environmental labs. After 14 years working in the world of commercial environmental labs, he moved on to a spectroscopy instrument manufacturer where he performed service and sales functions over the course of 11 years. He has been with Agilent Technologies, Inc., since 2012 in the role of Application Scientist for ICP-OES, MP-AES and AA products.

Mark Kelinske, Application Scientist, Agilent Technologies, Inc.

Mark Kelinske is an Applications Chemist with Agilent Technologies, specializing in advanced ICP-MS and ICP-MS/MS techniques. He received his undergraduate and graduate degrees from Texas A&M University in College Station, TX. Prior to Agilent, Mark was a senior research scientist and research group manager with Southern Research Institute in Birmingham, AL, where he focused on low-level analytical chemistry, method development, and research program management.

Chris Conklin, Atomic Spectroscopy Product Specialist, Agilent Technologies, Inc.

With a degree from the University of Wisconsin – Eau Claire, Chris worked in, and lead, a quality control lab testing fine chemicals ranging from reagent grade to high purity. Over the course of 12 years in that role, Chris has run a variety of atomic elemental instruments and techniques including AA, ICP-OES, and ICP-MS. As a result, he has seen most of the periodic table in its elemental form and overcome the associated interferences. In 2018, Chris brought that knowledge and experience to his current role with Agilent as the Product Specialist for Atomic Spectroscopy supporting AA, MP-AES, and ICP-OES for the Eastern US.

 

Register Here >

 

Food and Cannabis Elemental Analysis Part 1: Elemental Workflows in the Food and Cannabis Lab

This will be a three week Food and Cannabis elemental analysis workshop. We will cover a lot of great information during these three weeks.

Part 1: We will cover the entire Agilent elemental portfolio. Each of the different instruments’ strengths and how they meet the challenges that food and cannabis labs have.

 

Speakers

Jenny Nelson, PhD, Application Scientist, Agilent Technologies, Inc.

Jenny Nelson received her Ph.D. in Analytical Chemistry from the University of Cincinnati in 2007, and her MBA from Saint Mary’s College of California in 2011. Currently, Jenny is an Application Scientist for the Life Science and Chemical Analysis team at Agilent Technologies, joining in 2012 (with a step away in 2019). Jenny is also an Adjunct Professor in the Department of Viticulture and Enology at the University of California, Davis, since 2013. Jenny has been very active with AOAC and ASTM over the past eight years, serving on expert review panels, chairing committees, and volunteering to develop new methods needed by the industry. Jenny has extensive experience in operating and method development for Inductively Coupled Plasma Mass Spectroscopy (ICP-MS), Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), Microwave Plasma Atomic Emission Spectroscopy (MP-AES). Jenny has broad knowledge and experience in different speciation analysis for many sample matrices using GC-ICPMS and LC-ICPMS. As well as vast experience with sp-ICP-MS for many applications.

Greg Gilleland, Application Scientist, Agilent Technologies, Inc.

Greg began his spectroscopy career in 1987 in Colorado, working at a series of environmental labs. After 14 years working in the world of commercial environmental labs, he moved on to a spectroscopy instrument manufacturer where he performed service and sales functions over the course of 11 years. He has been with Agilent Technologies, Inc., since 2012 in the role of Application Scientist for ICP-OES, MP-AES and AA products.

Mark Kelinske, Application Scientist, Agilent Technologies, Inc.

Mark Kelinske is an Applications Chemist with Agilent Technologies, specializing in advanced ICP-MS and ICP-MS/MS techniques. He received his undergraduate and graduate degrees from Texas A&M University in College Station, TX. Prior to Agilent, Mark was a senior research scientist and research group manager with Southern Research Institute in Birmingham, AL, where he focused on low-level analytical chemistry, method development, and research program management.

Chris Conklin, Atomic Spectroscopy Product Specialist, Agilent Technologies, Inc.

With a degree from the University of Wisconsin – Eau Claire, Chris worked in, and lead, a quality control lab testing fine chemicals ranging from reagent grade to high purity. Over the course of 12 years in that role, Chris has run a variety of atomic elemental instruments and techniques including AA, ICP-OES, and ICP-MS. As a result, he has seen most of the periodic table in its elemental form and overcome the associated interferences. In 2018, Chris brought that knowledge and experience to his current role with Agilent as the Product Specialist for Atomic Spectroscopy supporting AA, MP-AES, and ICP-OES for the Eastern US.

 

Register Here >