Growth-pH Coupling Mechanism and Prediction Model for <italic style="font-style: italic">Synechococcus</italic> in Sodium Bicarbonate Culture System

XU Yuntong; YU Guiyuan; FENG Min; CAO Wen; WEI Wenwen; GUO Liejin

doi:10.7652/xjtuxb202609019

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Growth-pH Coupling Mechanism and Prediction Model for Synechococcus in Sodium Bicarbonate Culture System

更新时间：2026-09-04

- Growth-pH Coupling Mechanism and Prediction Model for Synechococcus in Sodium Bicarbonate Culture System
- Journal of Xi'an Jiaotong University Vol. 60, Issue 9, Pages: 197-207(2026)
- 作者机构：
  
  西安交通大学动力工程多相流国家重点实验室，710049，西安
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202609019
  CLC： TK6;Q949.22
- Received：01 December 2025，
  
  Online First：24 June 2026，
  
  Published：10 September 2026
- 稿件说明：
移动端阅览
XU Yuntong, YU Guiyuan, FENG Min, et al. Growth-pH Coupling Mechanism and Prediction Model for Synechococcus in Sodium Bicarbonate Culture System[J]. Journal of Xi'an Jiaotong University,2026,60 (9):197-207. https://doi.org/10.7652/xjtuxb202609019.
DOI：

XU Yuntong, YU Guiyuan, FENG Min, et al. Growth-pH Coupling Mechanism and Prediction Model for Synechococcus in Sodium Bicarbonate Culture System[J]. Journal of Xi'an Jiaotong University,2026,60 (9):197-207. https://doi.org/10.7652/xjtuxb202609019. DOI：

摘要

针对聚球藻培养过程中pH波动引发生长受限、生长状态难以实时精准预测的问题，提出了基于在线pH信号的多因子耦合生长预测模型。设置不同初始接种浓度（以730 nm波长下的光密度OD

730

表示，记为

（无量纲），其取值范围为0.1～1.3）、光照强度（14～181μmol·m

-2

·s

-1

）和碳酸氢钠物质的量浓度（25～125 mmol/L），监测聚球藻的生物量与pH动态变化数据；在无机碳形态转换机理分析基础上，采用Logistic模型定量表征生物量与pH的响应关系，并进一步构建多因子耦合生长预测模型。研究结果表明，生物量积累与培养液pH上升高度同步，生长限制主要由pH升高促使

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向

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转化，导致可利用无机碳不足引起；Logistic模型在15组条件下拟合优度

均大于0.98，拐点pH为9.5～9.8，且与碳源可利用性转折节点高度吻合；生长预测模型在两组独立实验中预测拟合优度

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分别为0.9879、0.8858，平均绝对误差

分别为0.0439、0.1181。营养代谢试验证实无机碳消耗与硝态氮消耗呈显著正相关；脂质的质量分数（以细胞干质量为基准）为13.0%～18.7%，脂肪酸以棕榈酸和棕榈油酸为主要组分，二者合计占总脂肪酸的75%～85%。经多目标优化得到最优培养条件为：光照强度为97μmol·m

-2

·s

-1

、初始接种浓度为0.1～0.4、碳酸氢钠物质的量浓度为25～50 mmol/L。该模型可依托现场pH在线监测，实现聚球藻培养过程精准预判与精细化调控。

Abstract

To address the growth limitation caused by pH fluctuations during

Synechococcus

cultivation and the difficulty in accurate real-time prediction

a multifactor-coupled growth prediction model based on online pH signals is proposed.Experiments are conducted at different initial inoculation concentrations（expressed as optical density at 730 nm

703

denoted by

ranging from 0.1 to 1.3）

light intensities（14—181 μmol·m

-2

·s

-1

）

and sodium bicarbonate concentrations（25—125 mmol/L）to obtain dynamic biomass and pH data.Based on an analysis of inorganic carbon speciation

a logistic model is used to quantify the biomass-pH relationship

and a multifactor-coupled growth prediction model is further established.It is shown that biomass accumulation is highly synchronized with the increase in culture-medium pH

and that growth limitation is mainly caused by the pH-driven conversion of

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resulting in insufficient available inorganic carbon.

values above 0.98 are obtained by the Logistic model under all 15 conditions

with inflection-point pH values of 9.5—9.8

which closely correspond to the transition points of carbon-source availability.In two independent experiments

predicted determination coefficients

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values of 0.9879 and 0.8858 and mean absolute error

of 0.0439 and 0.1181 are obtained by the growth prediction model

respectively.A significant positive correlation between inorganic carbon consumption and nitrate-nitrogen consumption is confirmed by nutrient metabolism experiments.The dry cell mass-based lipid mass fraction ranges from 13.0% to 18.7%

and palmitic acid and palmitoleic acid are the main fatty acids

together accounting for 75%—85% of th

e total fatty acids.The optimal culture conditions are determined through multi-objective optimization as a light intensity of 97 μmol·m

-2

·s

-1

an initial inoculation concentration of 0.1—0.4

and a sodium bicarbonate concentration of 25—50 mmol/L.Accurate prediction and refined regulation of

Synechococcus

cultivation can be achieved using the model based on online pH monitoring.

关键词

Keywords

references

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Growth-pH Coupling Mechanism and Prediction Model for Synechococcus in Sodium Bicarbonate Culture System

DOI：10.7652/xjtuxb202609019

摘要

Abstract

关键词

Keywords

references