This manuscript describes the use of a portable and low cost fluorescence setup to quantify the concentration of ochratoxin A (OTA) in beverage samples using an in-house developed system and different color models. It is reported that OTA is naturally fluorescent, for that reason an ultraviolet light at 365 nm was used to excite the samples and a Complementary Metal Oxide Semiconductor (CMOS) sensor was used to get a photograph of the OTA under excitation conditions, which is controlled by an executable interface designed in MATLAB. For each concentration of OTA, the coordinates with respect to each model color were obtained and plotted to quantify the mycotoxin present in the sample. It was possible to observe that despite the fact no extraction column was employed, the Red, Green, Blue (RGB) model shows a proportional relation to the evaluated concentrations. Despite the fact more analysis and other methods are required to quantify the OTA concentration, the brightness and a,b for the color-opponent dimensions (L*a*b) and Hue, Saturation, Value (HSV) tests provide results whereby it is possible to identify the concentration of OTA in beverage samples such as beer and wine.

In this work, we will analyze the response of a Metal Oxide Gas Sensor (MOGS) array to a flow controlled stimulus generated in a pressure controlled canister produced by a homemade olfactometer to build an E-nose. The built E-nose is capable of chocolate identification between the 26 analyzed chocolate bar samples and four features recognition (chocolate type, extra ingredient, sweetener and expiration date status). The data analysis tools used were Principal Components Analysis (PCA) and Artificial Neural Networks (ANNs). The chocolate identification E-nose average classification rate was of 81.3% with 0.99 accuracy (Acc), 0.86 precision (Prc), 0.84 sensitivity (Sen) and 0.99 specificity (Spe) for test. The chocolate feature recognition E-nose gives a classification rate of 85.36% with 0.96 Acc, 0.86 Prc, 0.85 Sen and 0.96 Spe. In addition, a preliminary sample aging analysis was made. The results prove the pressure controlled generated stimulus is reliable for this type of studies.

The low bandwidth of metal oxide semiconductor (MOX) sensors (<0.1 Hz) is a major hurdle to gas source localization (GSL) in turbulent environments where detection of intermittent odor patches is key. We present a fast-response miniaturized electronic nose (Fast-eNose) composed of four naked MOX sensors and a digital band-pass filter that can boost the bandwidth of the system close to 1 Hz. The device was attached to a fast photo-ionization detector (330 Hz) to quantify the response time during exposure to turbulent gas plumes. The results indicate that the digital filter can improve the response time by at least a factor of 4, bringing new possibilities to mobile robot olfaction.

The aim of this work is to present an ongoing research related to the design of a computer controlled olfactometer, which can be used in olfaction studies and e-noses tests. This design doesn't use mass How controllers instead it implements pressure controllers to regulate the output flow making it a less expensive solution. The designed device is PC controlled, portable and it has: Four ways/channels capable of handling solid and liquid odorant samples, its own clean air source, one clean air channel as odor carrier that allows dilutions, graphical interfaces for individual and cyclic stimulation, 8 supplementary analogic signal recording input ports and 5 digital input/output ports and two modes of operation single odor stimulation or odor mixing. The average top flow obtained was of 0.57 L/min for odor channels and of 2 L/min for the clean air channel. The flow stabilization time of 1.577 s makes the device a potential alternative for olfactometric tests or e-nose characterization.