Increase shelf life of peanuts with AOTF NIR technology
How to increase shelf life of peanuts with AOTF NIR technology
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Comparison between Raman, MIR and NIR spectroscopy
Comparison between Raman, MIR and NIR spectroscopy
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Determining moisture content in breadcrumbs with AOTF NIR technology

Determine moisture content in breadcrumbs with AOTF NIR technology

Determine moisture content in breadcrumbs with AOTF NIR technology

Precise measurements of moisture content in foodstuff has great economic relevance for food manufacturers. Moisture influences not only taste and texture of food, but weight, appearance and shelf life of food. Measuring and controlling moisture content in food with high accuracy ensures optimal balance between product quality, safety and profitability, in addition to respecting national and international standard for commercial food products. Here we describe how to determine moisture content in breadcrumbs with AOTF NIR technology.

There are many available methods out there to measure water in food. A fairly comprehensive list can be found in the book Food Analysis edited by S. Nielsen. Near-infrared (NIR) analysis is one of these methods, that has the advantage of being non-destructive and non-contact, with proven applications in the laboratory, at-line, and on-line situations.
For water, NIR bands 1400–1450 nm and 1920–1950 nm can be used to determine the moisture content of a food after proper calibration work. NIR is extremely useful to determine moisture content in bulk food, such as grains, wheat, baby formula, and breadcrumbs. The reason is that near-infrared light interaction range is within a 2-3 mm depth in solids, and therefore foodstuff that is already in powder or granular form is very well suited for NIR.

Determination of moisture content in breadcrumbs was recently done by Brimrose for one of their customers using an AOTF-NIR Luminar 5030 spectrometer. They provided 60 samples of breadcrumbs (from three different types of bread), from which they chose eight validation samples. Here’s the NIR spectra from these samples (note the prominent water peaks at 1420 nm and 1950 nm.
The data was used to build a calibration model using Regression Analysis. Once the model was built, the validation samples were tested, and the moisture values predicted by NIR analysis were compared to the known value to assess the accuracy of the technique.

SampleReference moisture valuePredicted moisture valueRelative error (%)
19.559.752.1
28.058.424.6
38.758.982.6
410.0010.474.7
56.106.343.9
67.227.240.3
78.008.040.5
86.706.903.0
On the eight validation samples, the prediciton error was well within the acceptable accuracy range for the food manufacturer.

Would you like to test our NIR spectrometer for your food analysis applications? Feel free to give us a buzz!

Instruments & Data Tools

Instruments and Data Tools
Instruments and Data Tools
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