Multi parameter food adulteration detector

1、 The product is equipped with a multi parameter food adulteration detector, which utilizes neural network detection principles to establish a multi parameter mathematical model. The physical and chemical indicators of the mixed sample are measured using a composite probe, and the percentage of adulteration in the liquid food sample is calculated using the internal formula of the instrument. Composite sensor technology is currently the most advanced detection technology. In the detection of substances composed of complex components, a single sensor can no longer meet the requirements for specific component determination. Composite sensor technology can effectively measure specific components. A neural network-based data analysis model can accurately express the specificity of a specific substance in a complex composition, and thus accurately determine it.

2、 Technical Highlights 1 A neural network-based data analysis model that processes data in real-time and accurately identifies feature points; two No reagent consumables, reducing detection costs and improving detection accuracy; three Open testing project upgrade mode, customer customized testing indicator limits. 3、 Test item 1 Rapid determination of liquid food quality based on standard samples; two Lock in food flavor data for standardized mass production; three Research institutions are used to establish a database of standard liquid sample components