In this study, three Lactiplantibacillus plantarum, namely 3-14-LJ, M22, and MB1, with high acetate esterase activity, acid, salt, and high-temperature tolerance were selected from 708 strains isolated from fermented food. Then, L. plantarum strains MB1, M22, and 3-14-LJ were inoculated at 107 CFU/mL in the model and 107 CFU/g in actual Suanzhayu systems, and the effects during fermentation on the physicochemical properties, amino acid, and volatile substance were investigated. The results showed that the inoculated group had a faster pH decrease, lower protein content, higher TCA-soluble peptides, and total amino acid contents than the control group in both systems (p < 0.05). Inoculation was also found to increase the production of volatile compounds, particularly esters, improve the sour taste, and decrease the bitterness of the product (p < 0.05). L. plantarum M22 was more effective than the other two strains in stimulating the production of isoamyl acetate, ethyl hexanoate, and ethyl octanoate. However, differences were discovered between the strains as well as between the model and the actual systems. Overall, the isolated strains, particularly L. plantarum M22, have good fermentation characteristics and have the potential to become excellent Suanzhayu fermenters in the future.
With the continuous improvement for the safety of stone installation, the quality detection of its machined surface is also improving. But its surface crack was always a difficult problem in detection. In recent years, with the rapid development of image processing technology a new method to solve this problem can be realized. In this paper, CCD camera was used to detect the surface crack and roughness of stone slabs. The research about image correction and image enhancement was carried, so as to eliminate noise and protect the crack edge in the greatest extent. The improved threshold segmentation algorithm was used to segment image of linear fracture filtering. Mathematical morphology was applied to refinement of single pixel of crack in order to gain crack size. The CCD camera and micro lens are assembled as image sensors to enlarge the surface of stone and take a sample by many taking pictures. The surface profile of the tested stone slab is obtained by reconstruction method, and the surface roughness of stone slab is finally obtained by analysis and calculation. Through this research, a fast detection technology was realized, which solves the problems of low processing efficiency and high cost in production. The result shows certain theoretical value and practical application significance.
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