The physico-chemical parameters including pH and viscosity, and the fluorescence signal induced by fluorescent compounds presenting in yogurts such as riboflavin and porphyrin were measured during one week’s storage at room temperature when five brands of yogurt samples were exposed to ambient air. The fluorescence spectra of yogurt showed four evident emission peaks, 525 nm, 633 nm, 661 nm, and 672 nm. To quantitatively investigate the quality of yogurt during deteriorating, a calculating method of the average rate of change (ARC) was proposed to study the relative change of fluorescence intensity in the spectral range of 600 to 750 nm associated with porphyrin and chlorin compounds. During the storage, the time evolution of two ARC, pH value, and viscosity were regular. Moreover, the ARC showed a good linear relationship with pH value and viscosity of yogurt. Further, multiple linear regression (MLR) models using two ARC as independent variables were developed to verify the dependence of fluorescence signal with pH value and viscosity, which showed a good linear relationship with an R-square of more than 85% for each class of yogurt. The results demonstrate that fluorescence spectra have a great potential to predict the quality of yogurt.

The large depth of images for microscopic measurement can be achieved by using focus stacking techniques with a small depth of field of objective lens. It is implemented by fusing the image sequences of short depth images. However, the non-linear movement of the objective imaging system or the measured object caused by the moving stage straightness error brings the misalignment of the image sequences, such as transversal translation, rotation, and tilting. All of these interferences, as well as the image brightness variation must be corrected by image registration before fusing the image sequences. In this paper, a fast-automatic registration method based on the scale invariant feature transform (SIFT) is proposed. It is achieved by firstly segmenting the focal regions of the image sequences through fast edge detection. Then the image features are extracted within the small segmented focal areas. It greatly reduces the computational cost of feature extraction and the following steps of image correction, and alignment. In the process, the random sampling consistency (RANSAC) algorithm is also used to remove the mistake features. The Laplacian pyramid method is adopted for the large depth of image fusion. The experimental results show that the proposed method is more efficient than the traditional SIFT algorithm. Its registration efficiency is improved by about 60%. This method facilitates the high-precision and real-time imaging of a monocular three-dimensional focus stacking.

Stabilizing orthogonal phase bias is highly required in Mach-Zehnder interferometer (MZI) to achieve sufficiently high sensitivity and long-term stability. To this end, we demonstrated a stabilized MZI using dual-wavelength feedback and a geometric phase shifter (GPS). The two beams at the wavelengths of 632.8 nm and 532 nm, respectively, propagate almost in the common path in the MZI, so that the beams have the same sensitivity to ambient disturbance. The beam at 632.8 nm is used to sense the displacement, and the other one at 532 nm is used for feedback and orthogonal phase bias stabilization. The phase shift error of the two separate wavelengths can be compensated by a GPS consisting of a rotating half waveplate sandwiched between two static quarter waveplates. The results of the proof-of-concept experiment showed that the phase shift error between 632.8 nm and 532 nm was reduced to within (-0.08π, 0.09π) by the GPS, and can be further reduced by two orders of magnitude if more appropriate wavelengths or waveplates were selected. The stabilized MZI showed a displacement resolution of 5 nm, and was proved to be effective in suppressing the low-frequency noise less than 10 Hz.