Cordyceps militaris is widely used in China, Korea, and other Asian countries as both a traditional medicinal ingredient and an edible fungus. This study aimed to optimize the growth conditions and fruiting body production of C. militaris by investigating various culture media and physical parameters such as pH, aeration, illumination, temperature, spawn materials, and oat–sawdust-based substrate formulations. After a 7-day incubation period, oats with a pH of 6.0, under sealed and illuminated conditions at 32°C, demonstrated the most effective mycelial growth. Substrates consisting of 70% oat and 30% sawdust had the shortest incubation time of 30.5 days for fruiting body formation. The basidiospores showed a typical germination pattern where the sporidium produced a single germ tube that elongated, and branched to form monokaryotic primary mycelia. In conclusion, using oats as a substrate in the cultivation of C. militaris could reduce production costs and help protect the environment.

We studied the effects of initial pH, different nitrogen sources, and cultivation methods (shake flask and static culture) on biomass production, exopolysaccharides (EPS), and adenosine by Paecilomyces tenuipes. Relatively low pH levels were optimal for mycelial growth and EPS production. Yeast extract was the most effective organic nitrogen source for EPS production, whereas soybean extract was the best for adenosine production. A high C/N ratio was beneficial for adenosine production; however, excessively high C/N ratios reduced adenosine production. Static fermentation significantly increased adenosine production. A Box-Behnken design was used to optimize adenosine production; the optimal conditions for adenosine production by P. tenuipes were pH 7.0, soybean concentration of 3%, and a static culture period of 20 days, with the maximum adenosine production of 141.10 mg/L (predicted value: 128.05 mg/L).

Ethanol production from various agricultural and forest residues has been widely researched, but there is limited information available on the use of mixed hardwood for ethanol production. The main objective of this study is to assess the impact of time on the steam explosion pretreatment of waste wood (mixed hardwood) and to determine the convenience of a delignification step with respect to the susceptibility to enzymatic hydrolysis of the cellulose residue and the recoveries of both cellulose and hemicellulosic sugars. Delignification did enhance enzymatic hydrolysis yields of steam exploded waste wood. For steam explosion pretreatment times of 3 and 5 min, the recovery yield of hemicellulosic-derived sugars decreased. The effective hemicellulose solubilization does not always result in high recoveries of hemicellulose-derived sugars in the liquid fractions due to sugar degradation. In the steam explosion pretreatment times of 3 and 5 min, where hemicellulose solubilization exceeded 95%, but sugar recoveries in the liquid fraction remained below 30%. Cellulose to glucose yield losses were less significant than hemicellulosic-sugar losses, with a maximum loss of 24% at 5 min. Up to 80% of the lignin in the original wood was solubilized, leaving a cellulose-rich residue that led to a concentrated cellulose to glucose yield solution (about 50 g/L after 72 h enzymatic hydrolysis in the best case). The maximum overall process yield, taking into account both sugars present in the liquid from steam explosion pretreatment and cellulose to glucose yield from the steam exploded, delignified and hydrolyzed solid was obtained at the lowest steam explosion pretreatment time assayed.

The objective of this study was to determine the ultrasonication-assisted extraction conditions that maximize the DPPH radical scavenging activity of extracts obtained from the stems of Lespedeza bicolor Turcz through the application of the Response Surface Methodology (RSM). Before delving into the analysis of extraction conditions using the RSM model, we conducted efficiency validation of ultrasonication-assisted extraction and executed single-factor experiments for ethanol concentration, extraction time, and extraction temperature. The data obtained from these single-factor experiments were employed to construct the Box-Behnken Design (BBD). In these results, in the single-factor experiments, it was evident that the parameters for ethanol concentration, extraction time, and extraction temperature exhibited quadratic trends. The single-factor experiments allowed us to discern the trends for each parameter leading to the maximum antioxidant capacity, and this data was subsequently applied to the BBD. Following the completion of initial experiments, a Response Surface Methodology (RSM) model was constructed based on Box-Behnken Design (BBD). According to the predictive model developed in this study, it was anticipated that performing ultrasonic-assisted extraction for 85.0412 minutes at an ethanol concentration of 32.573% and an extraction temperature of 51.5608°C will result in a DPPH radical scavenging activity of 79.7146%. The predictive results were statistically verified through a comparative analysis with actual measurements and ANOVA analysis, confirming the statistical significance of the model. The finding of this study underscore the significance of optimizing extraction conditions in the precise quantification of the antioxidant potential for economic advantages in both experimental and industrial contexts.

Paecilomyces tenuipes (P. tenuipes) is a fungus cultivated artificially by South Korean researchers, utilizing rice bran as its substrate. The increased demand for this fungus has not been met with successful cultivation methods for fruiting body production in natural environments. Therefore, we tested the effect on the growth of P. tenuipes using a Solid media based on pests. In this results, the Solid media based on M.alternatus was effective in increasing the growth of P. tenuipes and the content of cordycepin. Moreover, we confirmed the conditions for manufacturing a Solid media based on M.alternatus for P. tenuipes growth. We suggested that the growth-promoting compounds offers valuable insights for optimizing fungal cultivation conditions, thereby enhancing productivity and contributing to a broader understanding of fungal physiology in varying nutritional environments.

Plants synthesize antioxidant compounds as a defense mechanism against reactive oxygen species. Recently, plant-derived antioxidant compounds have attracted attention due to the increasing consumer awareness in the heath industry. However, traditional methods for measuring the antioxidant activity of these compounds are time-consuming and costly. Therefore, our study constructed a quantitative structure-activity relationship (QSAR) model that can predict antioxidant activity using graph convolutional networks (GCN) from plant structural data. The accuracy (Acc) of the model reached 0.6 and the loss reached 0.03. Although with lower accuracy than previously reported QSAR models, our model showed the possibility of predicting DPPH antioxidant activity in a wide range of plant compounds (phenolics, polyphenols, vitamins, etc.) based on their graph structure.