生物
菌丝体
分生孢子
植物
原基
园艺
冬虫夏草
接种
光强度
生物化学
基因
光学
物理
作者
Kuanbo Liu,Fen Wang,Guijun Liu,Caihong Dong
标识
DOI:10.1615/intjmedmushrooms.2018029506
摘要
Isaria cicadae (syn. Cordyceps cicadae) is one of the most valued edible and medicinal fungi and has been used in Asia as a substitute for Ophiocordyceps sinensis. Wild I. cicadae is limited and seasonal, and its cultivation is deserved. In this investigation we studied synnema formation by and nucleoside production in cicada flower under different environmental conditions. I. cicadae produced an asexual structure and mitospores instead of meiotic ascospores; this indicates that the term "synnema" is more suitable than "fruiting body" for this species. The optimal temperature was 25°C for growth of I. cicadae mycelia on potato dextrose agar plates but was 20°C for synnema formation on wheat medium. Synnemata can grow well under blue, green, and white light, and the dry weight of samples grown under these 3 light wavelengths is not significantly different. However, neither primordia nor synnemata formed under red light. Blue light promotes conidia production and white light promotes N6-(2-hydroxyethyl)-adenosine (HEA) production. Weak white light at 50 and 150 lux was more suitable for synnema production than strong-intensity light at 850 lux. The growth curve showed that HEA content has the same trend as synnema production over the entire cultivation period. The optimal harvesting time for I. cicadae cultivated on wheat medium is 35 days after inoculation. HEA content in the synnemata cultivated on wheat medium under the optimal conditions was significantly higher than that of the wild species and of synnemata cultivated on pupae, suggesting that synnemata cultivated on wheat medium may have potential as a substitute for wild resources. The results presented herein provide a new strategy for producing superior-quality synnemata of I. cicadae and further elucidate the effects of environmental conditions on metabolite accumulation in fungi.
科研通智能强力驱动
Strongly Powered by AbleSci AI