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Herein, we studied the effect of UV-C (shortwave ultraviolet) irradiation on the quality and inhibition of the browning of fresh-cut Chinese yam (Dioscorea opposita). The irradiation of 0, 4, 8, 12, and 24 kJ m-2 were applied to fresh-cut Chinese yam, and quality characteristics were evaluated during 16 days of storage at 4°C. The results indicated that UV-C treatment (8 KJ m-2) effectively decreased the browning degree, polyphenol oxidase (PPO) and peroxidase (POD) activities, and total bacteria count (TBC). However, the phenylalanine ammonia lyase (PAL) activity, PAL gene expression, respiration rate, and total phenol content increased. The UV-C treatment of 8 kJ m-2 resulted in a lower degree of membrane damage, as evidenced by the lower soluble quinone accumulation and browning index (BI), and retained the soluble solid content and hardness during storage. Increasing irradiation intensity would enhance cell damage while did not reduce browning. The results also showed that UV-C treatment alone had great potential to inhibit the browning of fresh-cut vegetables.

AbstractThe coal mine production industry is a complex sociotechnical system with interactive relationships among several risk factors. Currently, causation analysis of gas explosion accidents is mainly focused on the aspects of human error and equipment fault, while neglecting the interactive relationships among risk factors. A new method is proposed through risk coupling. First, the meaning ofrisk coupling of a gas explosionis defined, and types of risk coupling are classified. Next, the coupled relationship and coupled effects among risk factors are explored through combining the interpretative structural modeling (ISM) and the NK model. Twenty‐eight representative risk factors and 16 coupled types of risk factors are obtained through analysis of 332 gas explosion accidents in coal mines in China. Through the application of the combined ISM–NK model, an eight‐level hierarchical model of risk coupling of a gas explosion accident is established, and the coupled degrees of different types of risk coupling are assessed. The hierarchical model reveals that two of the 28 risk factors, such as state policies, laws, and regulations, are the root risk factors for gas explosions; nine of the 28 risk factors, such as flame from blasting, electric spark, and local gas accumulation, are direct causes of gas explosions; whereas 17 of the risk factors, such as three‐violation actions, ventilation system, and safety management, are indirect ones. A quantitative analysis of the NK model shows that the probability of gas explosion increases with the increasing number of risk factors. Compared with subjective risk factors, objective risk factors have a higher probability of causing gas explosion because of risk coupling.