Tyrosine crystals occasionally appeared on the broad bean paste surface, which will cause economic losses. This study aimed to eliminate the tyrosine crystals in broad bean paste through decreasing the activities of proteolytic enzymes produced by Aspergillus oryzae and process optimization. Broad bean pastes containing no more than 6.16 mg/g dry material tyrosine showed low possibility to form tyrosine crystals. Using tyrosine as substrate, the A. oryzae 3.042 was adaptively evolved and the tyrosine content in the broad bean paste fermented by the evolved A. oryzae was reduced from 6.49 mg/g dry material to 6.14 mg/g dry material (p < 0.05). When the production process was optimized, the tyrosine content in broad bean paste was further reduced to 5.67 mg/g dry material (p < 0.05). In this condition, no tyrosine crystals were formed in broad bean paste after the 12‐month storage while the product quality was not influenced. Practical applications Tyrosine crystals were one of the most important factors which negatively influence the quality of traditionally fermented food, including broad bean paste, soybean paste, and sausages. The appearance of tyrosine crystals in these foods will cause economic losses to manufacturers. This study tried to eliminate the appearance of tyrosine crystals through decreasing the activities of proteolytic enzymes produced by Aspergillus oryzae 3.042 and fermentation process optimization. The adoption of modified A. oryzae and optimized fermentation process successfully guaranteed the elimination of tyrosine crystals formation in the production and storage period of broad bean paste. This will not only benefit the broad bean paste manufacturers but also provide guidance for other fermented food producers to deal with tyrosine crystals problem.

At present, the segmentation method for the heart is one of the most difficult problems and a hot topic in medical imaging segmentation and image analysis. In order to achieve high-precision recognition of heart and blood vessel image, a single target auxiliary blood vessel image recognition algorithm, based on Markov Random Field (MRF) and ash fusion residual network information, is proposed in this paper. The corresponding features are extracted by the residual network depth, and the heart and blood vessels are segmented with high precision through MRF gray information to assist blood vessel image recognition. Thus, an algorithm combining Markov Random Field and Grayscale Information can complete such auxiliary recognition for single target ship image. The paper will also discuss auxiliary recognition techniques for identifying images of the heart and blood vessels. Added to that, it presents current medical image algorithms with a particular emphasis on cardiac image algorithms. Through a series of analysis, better algorithms are proposed. Thus, the research contents of a single target present the vascular image recognition algorithm. Therefore, a blood vessel image recognition algorithm is proposed for the research content of a single target. A series of validation experiments are conducted on the DRIVE and star datasets. The experimental results show that the method proposed in this paper has high segmentation accuracy, can achieve high-precision segmentation, and can achieve high-precision single target blood vessel image recognition. By observing and analyzing two-dimensional cardiac images, such as diabetic arterioles, hemorrhages, hard exudates, and so on, the difficulty of diagnosing cardiovascular disease characteristics can be reduced, and the diagnosis and treatment can be facilitated.

White spots are commonly found in bean-based fermented food, which will significantly lower the product quality. This study aimed to analyze the composition of white spots and further reveal the source and influencing factors of white spots in bean-based fermented food using soybean paste as study model. The results showed that white spots were mainly composed of 40.96% free tyrosine and 37.94% tyrosine in combination form. During soybean paste fermentation, tyrosine was found to be produced by the actions of proteolytic enzymes secreted by Aspergillus oryzae 3.042 instead of the microbial metabolism and the excessive accumulation of tyrosine in soybean paste led to the formation of white spots. Among all influencing factors, high temperature treatment favored the formation of white spots. The existence of soy peptone and phenylalanine would postpone the precipitation of tyrosine while promoting the aggregation of the tyrosine precipitation. Field emission scanning electron microscope analysis showed that tyrosine would accumulate around the soybean protein particles and treatment at 120°C would disrupt the structure of tyrosine-protein complex. Based on the above results, we proposed that treatment of soybean paste at temperature lower than 80°C was the current practically applicable method to control the formation of white spots in soybean paste.

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