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Shimadzu Corporation
Shimadzu Corporation
Shimadzu Corporation has remained committed to commercializing cutting-edge technology and providing it to customers in a wide array of industries for more than 140 years. Our brand statement, "Excellence in Science"​, reflects our desire and attitude to diligently respond to customers'​ requirements by offering superior, world-class analytical and measuring instruments, medical imaging systems, aircraft equipment and industrial machinery for the advancement of human health, the safety and security of society, and industrial processes.
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LC/MS
Sample prep
LC/MS/MS
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Faster, Smarter Analysis For FAMEs And Pesticides

RECORD | Already taken place We, 20.8.2025
Explore how Shimadzu’s AOC-6000 Plus and Peakintelligence AI streamline GCMS and LCMS food workflows—boosting speed, throughput, and efficiency in FAME and pesticide analysis.
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Shimadzu: Faster, Smarter Analysis For FAMEs And Pesticides
Shimadzu: Faster, Smarter Analysis For FAMEs And Pesticides

Food testing laboratories are under constant pressure to boost productivity, speed up turnaround times, and manage ever-growing sample volumes. However, conventional methods are often too time-consuming and labor-intensive, creating bottlenecks that may hinder progress.

Looking for a more efficient way forward? In this latest session of Digital Classrooms, discover how Shimadzu’s innovative solutions are transforming food analysis. Learn how AOC-6000 Plus enables automated GCMS workflows for FAME analysis and automated LCMS workflows for pesticide analysis. Plus, explore Peakintelligence software—a world-first AI-assisted algorithm that simplifies chromatography peak detection and accelerates data analysis for a streamlined workflow.

Take the next step towards faster, smarter, and simpler food testing. Register now to unlock your laboratory’s full potential!

Learning Objectives:
  • Discover Shimadzu's latest AI and automation solutions for advanced laboratory workflows
  • Understand how Shimadzu’s AI and automation technologies enhance laboratory throughput and efficiency compared to manual approaches
  • Explore practical applications of these solutions in FAME and pesticide analysis

Presenter: Dr Chia Chee Geng (Senior Application Specialist, Shimadzu (Asia Pacific) Pte Ltd)

Chee Geng attained his Bachelor of Science (Chemistry) and Doctorate (Biochemistry) from the National University of Singapore (NUS). His wide exposure in the various fields of sciences enables him to communicate effectively with a larger group of scientists from different backgrounds. After graduating from NUS, he joined the industry as an Analytical Chemist, involved in projects that deal with small molecules traces analysis in the complex sample matrix, requiring hands-on experience in various kinds of mass spectrometry (Ion Trap, Q-Trap, timsTOF, Triple Quad). He is also experienced in optimizing and designing high throughput sample preparations process for LC and GC analysis via automation, in order to improve efficiency in routine workflow. Dr CCG loves learning the latest advancement in technology in the market, looking forward to sharing what he knows with the interested target audience.

Presenter: Dr Yap Siew Qi (Senior Product Specialist (LCMS), Shimadzu (Asia Pacific) Pte Ltd)

Siew Qi is the Senior Product Specialist at Shimadzu Asia Pacific, specializing in LCMS. She earned her Ph.D. in Chemistry from the National University of Singapore in 2016, where her research focused on Pt (IV) complexes as prodrugs of cisplatin, utilizing various analytical techniques to assess their efficacy in cancer treatment. Since joining Shimadzu in 2017, she has held several roles, including Consumables Technical Specialist, Application Chemist and Product Specialist, where she has contributed to product development and customer engagement. Currently, as a Senior Product Specialist, she leads initiatives to enhance LCMS solutions for clients. With a solid foundation in analytical chemistry and a commitment to innovation, Siew Qi continues to drive advancements in her field.

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