• 生物工程 •

### 出芽短梗霉发酵液中聚苹果酸定量近红外模型的建立与应用

1. （1.天津科技大学生物工程学院，天津 300457；2.天津慧智百川生物工程有限公司，天津 300457；3.天津现代职业技术学院生物工程学院，天津 300350；4.天津市食品绿色制造及安全校企协同创新实验室，天津 300457）
• 出版日期:2020-04-25 发布日期:2020-04-20
• 基金资助:
滨海-中关村知行卓越创新创业实验室建设项目（17YFCZZC00310）； 天津市食品绿色制造及安全校企协同创新实验室建设项目（17PTSYJC00080）； 工业微生物优良菌种选育与发酵技术公共服务平台项目（17PTGCCX00190）

### Construction and Application of a Predictive Model for Determination of Polymalic Acid in the Fermentation Broth of Aureobasidium pullulans by Near-Infrared Spectroscopy

ZHANG Yinghao, XUE Zhaoyang, ZHAO Tingbin, YIN Haisong, QIAO Changsheng,

1. (1. College of Biotechnology, Tianjin University of Science & Technology, Tianjin 300457, China; 2. Tianjin HuizhiBiotrans Biological Engineering Co. Ltd., Tianjin 300457, China;3. School of Bioengineering, Tianjin Modern Vocational Technology College, Tianjin 300350, China;4. Tianjin University-Enterprise Collaboration Innovation Laboratory of Food Green Manufacturing and Safety, Tianjin 300457, China)
• Online:2020-04-25 Published:2020-04-20

Abstract: High performance liquid chromatography (HPLC) was used to measure the polymalic acid concentration in the fermentation broth of Aureobasidium pullulans. Interval partial least square regression (iPLSR) combined with moving window PLSR (MWPLSR) was used to confirm 5 638–6 024 cm-1 as the waveband for modeling. Multiplicative scatter correlation (MSC), standard normal variate (SNV), Savitzky-Golay 55 points smoothing and 1st derivative spectrum were successively operated as spectral pre-processing methods, and then PLSR with the first 5 factors was used to develop a predictive model with the highest accuracy. The root mean square of prediction (RMSEP) and correlation coefficient of prediction (Rp) of the model were 1.553 g/L and 0.970 0 for the internal test set, and 1.378 g/L and 0.992 4 for the external test set, respectively, and a paired t-test at 95% confidence level demonstrated that the maximum deviations between the HPLC values and the model predicted values were calculated as 1.48 and 0.83 g/L, respectively. There was no significant difference among three parallel predictions for one sample. When the model was applied to medium composition optimization and mutant screening, large prediction errors were found with paired t-test. However, the model could reliably predict polymalic acid concentration under the premise that the model calculated values were larger than 3.19 and 1.44 g/L, respectively, indicating the potential application of the near-infrared model in medium composition optimization and strain screening.