Entering the composition of many processed foods as a base ingredient, the wheat must be of high and constant quality. The presence of tainted wheat can.

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Entering the composition of many processed foods as a base ingredient, the wheat must be of high and constant quality. The presence of tainted wheat can indeed contaminate large batches of other raw material in storage or even prevail into the finished product if not removed from the process. The evaluation of wheat contamination is commonly carried out by visual assessment and human smelling at reception of raw materials. An instrumental analytical method can significantly simplify and improve usual quality control process. This study describes the analysis of wheat and the detection of off-flavor with an electronic nose. Samples & Analytical Conditions CONCLUSION The HERACLES e-nose has proved to be a very powerful tool to rapidly assess the sensory quality of wheat. The AroChemBase software indicates that the concentration of several alcohols is correlated with the off-odour. These molecules probably originate from microorganism metabolism that is responsible for wheat decay. Chromatography Profile Wheat off flavor assessment with an Electronic Nose Mr. A. Cowell, Mr. J.C. Mifsud, Mr. A. Rashtchian, Mr H. Lechat, Ms F. Ayouni, Ms V. Vabre, Ms M.L. Vicenty, Ms M. Bonnefille Alpha MOS Inc Connelley Drive, Suite 110 – Hanover, MD Eight samples of wheat (table 1) were analyzed with HERACLES electronic nose. (table 2) Each sample has been ground using a coffee grinder for 15 s before analysis on HERACLES electronic nose. Fig 1: Chromatograms of 2 batches of wheat (GA & TE) on the 2 columns of HERACLES HERACLES, Dual Fast Gas Chromatography E-Nose Odor Map The comparison of chromatograms (Fig. 1) obtained with HERACLES e-nose shows significant differences in terms of VOCs concentration between good and bad batches of wheat. Several volatile compounds have been detected at much higher concentration in tainted wheat than in good samples. Fig. 2: Principal Components Analysis of wheat obtained with HERACLES e-nose measurements Using the AroChemBase software and Kovats indices obtained on MXT-5 & MXT columns, indications about chemical composition can be determined. The main volatile compounds are listed in table 3. Most of them correspond to aldehydes and alcohols that are related with fatty acid oxidation and microbial metabolism. Table 3: Extract of possible volatile compounds identified by their Kovats indices in the headspace of wheat *Retention Time - **Retention Index (Kovats Index) HERACLES is coupled to AroChembase software module, which is designed to help characterize, directly from the chromatograms, the chemical compounds involved and their related sensory attributes, based on Kovats Index matching. It consists of a library of chemical compounds with name, formula, CAS number, molecular weight, Kovats retention Index, sensory attributes and related bibliography. This odor map (Fig. 2) obtained by selecting the most significant chemical compounds, shows a clear separation of tainted samples from good samples, according to their volatile compounds composition. Geosmin together with alcohols, aldehydes and alkanes are considered as discriminant compounds explaining the organoleptic differences. 2 columns of different polarities (MXT-5 & MXT-1701, length = 10m, diameter = 180µm, Restek) 2 Flame Ionization Detectors (FID) Integrated pre-concentration trap thermo-regulated by Peltier cooler (0- 260°C) Headspace or liquid analysis Equipment Table 2: HERACLES Electronic Nose Analytical Parameters ParameterValue Sample quantity 5 g  0.01 in a 20mL vial Headspace generation20 min at 90°C Syringe temperature100°C Injected volume 5000  L Injection speed 100  L/s Injector temperature220°C Injector vent30 mL/min Trap temperature60°C Trap pressure60 kPa (2s) kPa/s - 90 kPa Trapping time70 s Trap desorption240°C Columns temperature program 60°C (2s) to 80°C by 1°C/s then to 280°C (0s) by 2°C/s FID temperature280°C Acquisition duration120 s Time between 2 analyses 9 min CodeQualityInfo GAGoodWhole GBGoodWhole GCGoodWhole GDGoodWhole TETaintedGround TFTaintedWhole TGTaintedWhole THTaintedWhole *RT MXT-5 (  0.1s) *RT MXT (  0.1s) **RI MXT-5 (  20) **RI MXT (  20) Possible compoundsSensory attributes methyl propan-1-olAlcoholic, winey methyl butanalGreen, malty methyl butanalGreen, malty Pentanal / 2,3- pentanedione Butter, caramelized methyl butan-1-olAlcoholic, fermented methyl butan-1-olWiney, balsamic PentanolFruity, green HexanalFatty, green ,4-octadieneGlue, warm Hexan-1-olFloral, green β-pineneGreen, turpentine n-decaneAlkane methyl decane Methyl undecanoateBrandy, winey GeosminBeet, earthy Chemical CharacterizationQuality Control Model A quality control model (SQC algorithm) using good samples as the reference has been built (Fig. 3). This model shows that all tainted samples are out of range. Fig. 3: Statistical Quality Control (SQC) Chart model with good samples as reference Table 1: Samples list