An appearance quality classification method for Auricularia auricula based on deep learning.

The intelligent appearance quality classification method for Auricularia auricula is of great significance to promote this industry. This paper proposes an appearance quality classification method for Auricularia auricula based on the improved Faster Region-based Convolutional Neural Networks (improved Faster RCNN) framework. The original Faster RCNN is improved by establishing a multiscale feature fusion detection model to improve the accuracy and real-time performance of the model.

Co-production of Biohydrogen and Biomethane from Chicken Manure and Food Waste in a Two-Stage Anaerobic Fermentation Process.

Batch experiments were performed to evaluate the biohydrogen and biomethane production by co-digestion of chicken manure and food waste in a two-stage mesophilic fermentation process. Results showed that no hydrogen was produced in the first stage of sole chicken manure fermentation, while methane yield was 247.3 mL·g-VS.

Effects of maize straw treated with various levels of CaO and moisture on composition, structure, and digestion by in vitro gas production.

Objective: The objective of this study was to explore the effects of maize straw treated with calcium oxide (CaO) and various moisture, on the composition and molecular structure of the fiber, and gas production by fermentation in an in vitro rumen environment.

Methods: The experiment used 4×3 Factorial treatment. Maize straws were treated with 4 concentrations of CaO (0%, 3%, 5%, and 7% of dry straw weight) and 3 moisture contents (40%, 50%, and 60%).

[Progress in Application of Two-Dimensional Correlation Spectroscopy for Detection of Food Quality].

In recent years, the food safety and quality has always been a serious issue. Therefore, it is urgent to develop a rapid and widely available method to determine the quality of food. Due to high spectral resolution, good spectral selectivity and good ability of spectrogram analysis, the technology of two-dimensional (2D) correlation spectroscopy is an effective method for solving three major problems encountered by the conventional one-dimensional (1D) spectrum: low selectivity of the spectra, difficulty in extracting the information of the spectral feature and difficulty in spectrogram analysis.

[Discrimination of adulterated milk based on Euclidian distances between two-dimensional infrared correlation spectra].

Based on Euclidian distances between synchronous two-dimensional infrared correlation spectra, in terms of the average Euclidian distances between unknown samples and "extreme samples", and average intra- and inter-Euclidian distances of samples in the calibration set, a new method for the discrimination of adulterated milk was proposed. Sixteen pure milk samples were collected and 16 adulterated milk samples with urea (0.01-0.