Learning algorithms for identification of whisky using portable Raman spectroscopy.

Reliable identification of high-value products such as whisky is vital due to rising issues of brand substitution and quality control in the industry. We have developed a novel framework that can perform whisky analysis directly from raw spectral data with no human intervention by integrating machine learning models with a portable Raman device. We demonstrate that machine learning models can achieve over 99% accuracy in brand or product identification across twenty-eight commercial samples.

Investigation of refractive index dynamics during embryo development using off-axis digital holographic microscopy.

Embryo quality is a crucial factor affecting live birth outcomes. However, an accurate diagnostic for embryo quality remains elusive in the fertilization clinic. Determining physical parameters of the embryo may offer key information for this purpose.