Adulteration in food items is today’s most severe problem particularly meat and other highly consumed products by the common people. Most consumers are unconscious of the meat products they use. Keeping in mind the consumer’s rights, European and global food regulations have mandated that the origin of food should be guaranteed from farm to fork. Different techniques have been introduced to ensure the quality and authenticity of food based on genomics, proteomics, and metabolomics. The recent advancement in genomic technology plays a significant role in exploiting food technology. In this paper, we aim toward food authentication and adulteration in the assessment of the meat in compliance with labeling regulations and policies through the development of thermocyclers. The thermocycler ensures the precise temperature control and rapid temperature changes to conduct the polymerase chain reaction, PCR. A heating–cooling element, i.e., a Peltier heater is used for heating and cooling the metal block and the temperature sensors are responsible for sensing the metal block temperature. Based on the controller coefficient values, the temperature of the metal block is maintained. Further, the tunable fluorometer and design of DNA probes can be implemented for the detection of admixing targeting mitochondrial/genomic DNA.

Determination of the botanical source of honey samples is important for the determination of its medicinal properties, price, and certification. Monofloral honey samples and some of the common adulterants have been characterized by using Fourier Transform Infrared (FTIR) spectroscopy integrated with ATR sampling. In the region 4000–600 cm−1, spectral data of seven varieties of monofloral honey samples and four adulterant syrups were recorded. The spectral data is preprocessed using Extended Multiplicative Scatter Correction (EMSC) and second-order derivative methods. Dimension reduction of the data set has been achieved by using Principal Component Analysis (PCA). Classification models have been developed to characterize the monofloral honey samples and the adulterants. K-means, K-medians, and State Vector machine (SVM)-based classification models have been developed. Further, these classification models are cross-validated.

Various honey samples and possible adulterants has been characterized using Fourier Transform Infrared (FT-IR) spectroscopy integrated with ATR sampling. Spectral data of twelve varieties of samples including mono-floral honey, multi-floral honey and different variety of adulterants has been collected in Mid-IR region (4000cm -1 -400cm -1 ). Spectral Mid-IR data has been corrected using baseline correction method and preprocessed using 2nd order derivative & Standard Normal Variate (SNV) methods for removal of any additive & multiplicative scattering effects. The principal component analysis (PCA) has been used for dimension reduction in the data set and exploratory data analysis of the honey and its adulterant samples. K-means, K-medians and Fuzzy C Means based classification model has been developed for the classification of pure honey samples and adulterants. Developed model has been cross-validated using external samples.

FBAR (Thin Film Bulk Acoustic Wave Resonator) devices are commonly used as application of RF (Radio Frequency) filters for the cell phones and other communication devices. This paper reports about the measurement of the efficiency of FBAR devices. The efficiency is commonly measured in terms of the EMCC (Electromechanical coupling coefficient) and QF (Quality factor). Since the FBAR devices are designed in many shapes and sizes which depend on their working frequency range. So every shape and size has a different value of QF and EMCC. This paper compares the various shapes in terms of QF, EMCC and spurious modes of L-Band (1-2 GHz) resonator. Once the best shape is selected, the study of different metal electrode materials coupling with piezoelectric layer and the effect of the thickness ratio (t(d)) of electrode layer and the piezoelectric layer is discussed.