Described here is the modeling used to improve the mycophenolic acid (MPA) titer from Penicillium brevicompactum using central composite design and a comparatively newer, data-centric approach method k-nearest-neighbor algorithm. The two models for enhancing MPA production using P. brevicompactum were compared with respect to ultrasonic stimulation. During the ultrasonic treatment, we studied different independent factors such as ultrasound power, irradiation duration, treatment frequency and duty cycle to determine their ability to enhance the MPA titer value. The optimized factors such as a treatment time of 10 min (50% duty cycles) with a 12-h interlude at fixed ultrasonic power and frequency (200 W, 40 kHz) were used for ultrasonic treatment of a mycelial culture from the 2nd to 10th day of fermentation. Thus the production of MPA was improved 1.64-fold under the optimized sonication conditions compared with the non-sonicated batch fermentation (non-optimized conditions).

此处描述的是用于使用中心复合设计和相对较新的以数据为中心的方法k-最近邻算法来提高来自短青霉的霉酚酸 (MPA) 滴度的建模。使用P. brevicompactum提高 MPA 产量的两种模式与超声波刺激进行了比较。在超声治疗过程中，我们研究了不同的独立因素，如超声功率、照射持续时间、治疗频率和占空比，以确定它们提高 MPA 滴度值的能力。在固定超声功率和频率（200 W，40 kHz）下，处理时间为 10 分钟（50% 占空比）和 12 小时间隔等优化因素用于从第 2 到第 10 次对菌丝体培养物进行超声处理。发酵日。因此，与非超声分批发酵（非优化条件）相比，优化的超声处理条件下 MPA 的产量提高了 1.64 倍。