Helmut Ernstberger, senior scientist inorganic speciation at PerkinElmer, told FoodQualityNews that there was a trend around cutting down the number of analyses.
“In terms of food safety I would think one of the areas we are focussing more on is inorganic analysis where we would like to highlight our possibilities in providing an efficient analysis run for major nutrients and trace elements on one instrument which is the ICP-MS and going away from approaches that utilise two instruments, one for high level analysis and one for low level elements separately," he said at Analytica 2016.
“This particular feature makes use of our existing technologies in interference removal but also our capability to attenuate high level elements selectively by using what is termed, electronic dilution, to get high level elements to a signal intensity which is decreased to a level which is amenable to ICP-MS and allows limited dilution and analysis of the traces at the same time of the higher level elements.”
Label claims and speciation
Ernstberger said label claims analysis and speciation are other areas of interest with legislation becoming element specific such as mercury and arsenic.
“We are expanding in that [speciation] and there is more coming in terms of element speciation for food safety,” he said.
PerkinElmer showcased the Torion T-9 GC/MS: a portable GC/MS instrument for analyses in the field which has applications in food safety at the booth.
The firm had the Perten DA 7250 NIR Analyzer is a diode array based NIR instrument that analyzes samples of grains, flakes, pellet powders, pastes, slurries and liquids in six seconds and can determine moisture, protein, fat, ash, starch and other parameters.
Available factory calibrations cover a variety of products and parameters and are built from a database of hundreds of thousands of samples.
Clarus SQ 8 GC/MS delivers reliable throughput and productivity for applications which require extreme sensitivity such as environmental and food testing, said the firm.
It is designed around Clarifi technology, a GC/MS detector which uses electron technology to provide sensitivity and longer operational lifetime.
“Taking into account recent changes in the legislation which is happening in the EU, we have new legislation on inorganic arsenic in rice so the gold standard for this is still LC-ICP/MS so we are actively working on techniques which are faster than the conventional approaches.
“So they allow benefits for quality assurance by having easier access to faster recalibrations and more quality control standards in there just because the run time for an analytical sample is much shorter than what is typically passing right now.
"We are focussing on methods that are customised towards higher throughput analysis of those type of speciation applications will get more routine as the legislation is picking up.”
Ernstberger said in terms of economic viability for food adulteration it can detect levels way below those typically present in adulterated compounds using either targeted or non-targeted approaches.
“Food fraud could be characterized by techniques which are allowing direct analysis of the sample and in our product line-up we have a sampling deduction system for our mass spectrometer,” he said.
“This allows the measurement of samples in a native state and does away with the sample preparation and you get analysis results real-time, and that is a trend we see as important to serve in the food industry.”
In addition to targeted approaches, there are non-targeted approaches, he said.
“We have our spectrometric techniques so we use IR techniques for solutions where we want to highlight the presence of impurities which are compared against a library model of the unadulterated product so the spice industry for example or common food products like oils, these type of analyses are very helpful to distinguish if the profile deviates from the norm.
“One added attraction of our product line-up is to provide the capability not only to distinguish the spectrum for a model compound from adulterated samples but also to quantify any adulterants which are present in that food material as a result of adulteration.
“For example, in the case of milk and possible adulterants there is a database of about 50 compounds in there which are included in an algorithm to identify how much of said possible adulterant would be contributing to the deviations of the spectrum observed. So it is not just a yes-no answer but also a what type of adulterant compound could be contained in the sample.”
Direct sample analysis is one aspect getting more attractive if you want fast answers without much sample preparation, said Ernstberger.
“Maybe also there is a need for more data fusion scenarios where different techniques provide different aspects of a profile of a particular foods model,” he said.
“So an individual analysis may not provide conclusive answers so you may want to combine from a number of techniques which results in more data and more need for capabilities to process larger types of data sets and we have been looking into that also.”