QA/QC of flours using the Agilent Cary
Food grains (cereals, legumes and oilseeds) are milled to get flours, which can be employed in the manufacture of an enormous variety of products such as pasta and bakery products. All the raw ingredients in a food product should ideally be authenticated in order to ensure consistent quality standards and to comply with regulatory labeling requirements. Flours are generally received as powders that need to be tested to ensure: firstly that the contents of the containers correspond with the label and shipping ledger; and secondly, that the product received meets the requirements of the formulator as to uniformity and purity (in terms of composition). Typically
an advance sample is made available before bulk shipment and, in this case, it is incumbent upon the formulator to verify that the advance sample is indistinguishable in composition from that of the bulk shipment.
Various types of fl ours (Figure 1) such as chickpea, oat, rice, chestnut (gluten-free), millet (gluten-free), soya, yellow and white corn, organic shelled hemp seed (gluten-free), wheat gluten, whole wheat, breadcrumbs and baking soda were obtained from different suppliers.
The following procedure was used for all data acquisition:
1. A small amount of fl our (without any sample preparation or weighing) was placed on the ATR diamond surface.
2. The samples were pressed against the diamond crystal using the attached pressure clamp. A slip clutch on the clamp prevents overtightening.
3. Spectra were recorded by adding 64 spectra with a resolution of 4 cm-1 (measurement time ~30 seconds).
This figure shows several overlaid infrared spectra for selected flour samples. The infrared bands characteristic of major flour components such as proteins, carbohydrates, lipids and moisture content can be clearly discerned in the spectra. The intuitive
Agilent MicroLab FTIR software provides the means by which sample spectra can be compared to spectra of flour standards already stored in a spectral database of flours. A spectral database (library) can be quickly and easily created on-the-fl y in MicroLab PC. A new sample can then be identified immediately after recording its infrared spectrum.
The Agilent Cary 630 ATR-FTIR analyzer can be configured to report a pass/fail or percentage (%) spectral similarity with regard to a reference sample stored in the spectral database. Moreover, the spectral similarity among the infrared spectra of incoming new materials and previously recorded samples is particularly valuable in tracking batch-to-batch or lot-to lot variability from the same or different vendors.
Excerpt from Agilent Technologies Application Note 5991-0785EN