Whether built for food safety or product quality testing, food and beverage analytical labs are constantly faced with challenges such as overcoming matrix interference and meeting low detection limits, all while decreasing test turnaround times and cost per test sample.
In this three-part application eBook series, you will learn more about how our chromatography and mass spectrometry solutions from Thermo Fisher Scientific can be utilized to improve analytical testing in three important application areas: food authenticity, veterinary drug residues, and QA/QC product testing.
As globalized food supply chains have introduced increased opportunities for deliberate misrepresentation or adulteration of food products, ensuring that the food and beverage products we consume are authentic and unadulterated through analytical testing has become essential. This eBook introduces a variety of methods for utilizing techniques such as HPAE-PAD, LC-HRAM-MS, and EA-IRMS to quickly identify and quantify the presence of fraudulent substances or adulterants in food samples, ensuring consumer safety and maintaining the integrity of food industries.
Veterinary drugs are administered to livestock for a host of reasons including disease prevention and growth promotion, and their residues can persist in the animal’s tissues and the downstream food supply chain if gone unchecked. This eBook explores several methods that utilize LC-MS/MS and LC-HRAM-MS for tackling specific groups of compounds or high-throughput simultaneous screening of multiple residues, overcoming muscle matrix problems and improving Limits of Quantification (LOQs).
Quality assurance and quality control testing help food and beverage manufacturers identify any deviations from desired specifications and ensure consistent quality throughout the entire supply chain, from raw materials to the final product. This eBook covers several analytical methods that utilize techniques such as ICP-OES and HPLC-CAD to overcome problems arising in traditional QA/QC approaches, such as sample matrix interference or the need for pre-processing (e.g. derivatization), thereby enabling the high-resolution separation of complex samples at greater speed followed by high-sensitivity detection.
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