Characterization of time-series fluorescence properties of bean sprouts during storage using excitation emission matrix and fluorescence imaging.

Soybean (Glycine max (L.) Merr.) and mung bean (Vigna radiata L.) are popular varieties of bean sprouts, which are used in various Asian cuisines. The freshness of bean sprouts reduces at fast rate during storage. Hence, determining index of monitoring the state of sprouts is required to prevent unnecessary food loss, which is also linked to economical loss. The aim of this study is to reveal fluorescence characteristic of bean sprouts and investigate its potentiality for tracking the freshness state of bean sprouts. The fluorescence spectroscopy and imaging were used. For fresh bean sprouts, the Excitation-Emission Matrix (EEM) showed two fluorescence regions: Excitation (Ex) 270-300 nm with Emission (Em) 300-400 nm and Ex 300-350 nm with Em 400-450 nm, which are suspected to be amino acids and vitamins, respectively. When browning process started, the new fluorescence region occurred at Ex 400-450 nm with Em 450-550 nm. Consistent with EEM, under 365 nm, bean sprouts initially had blue fluorescence emission, and later changed to green when they start spoiling. However, due to higher emission, 420 nm-excitation wavelength was preferable for detecting browning part. With these basic fluorescence information, further application on inspecting both physical change and chemical change of bean sprouts can be easily established.

Mobile-device-based two-dimensional measurement for estimating the embryo and endosperm areas of brown rice.

The rice kernel inside a hull is composed of the embryo and endosperm. The embryo or germ of the rice seed will grow and become the shoot and the root parts of a seedling, while the endosperm is an important nutrient source for the embryo in the early stages. Hence, the health of seedlings depends particularly on the sizes of the embryo and endosperm. In this work, we propose and experimentally demonstrate how the embryo and endosperm areas of brown rice can simply be determined. Our key idea is based on the utilization of a smart mobile device equipped with our specifically designed lens module arranged in a simple cross-polarization imaging configuration for acquiring a rice grain image upon the illumination of a white light source and then spatially analyzing the sizes of embryo and endosperm areas. The prototype shows promising results in identifying the sizes of the embryo and endosperm within 2 s per seed with a measurement error of <9% compared with the use of off-the-shelf image editing software. In addition, the prototype is in a small package of 20×32.5×6.5cm3 with 4 kg weight, thus showing high potential to perform in the real scenario.

Temperature-compensated infrared-based low-cost mobile platform module for mass human temperature screening.

As fast human temperature screening is needed in large public areas, this paper proposes a low-cost mobile platform module that combines the advantages of analyzing visible and thermal images. In particular, the key idea relies on face detection in the visible image. Then the coordinates of all faces detected are mapped on to the thermal image to determine their corresponding temperatures. Internal temperature compensation and external reference temperature also are employed to reduce the unwanted temperature fluctuation inside the module and in the surrounding environment. Our mobile platform module, called $\unicode{x00B5} {\rm Therm}$, uses a FLIR ONE camera as our visible and thermal imaging cameras. It can simultaneously determine the temperatures of nine people at a speed of 8 frames/second. A field test operation was performed for four days with 1,170 people, with very promising results of 100% sensitivity, 92.6% specificity, and 92.7% accuracy.