Metabolic state-driven monitoring and control of abnormal pigment formation in sodium gluconate fermentation by Aspergillus niger

Abnormal pigment formation during late-stage fungal fermentation poses a significant challenge to industrial product quality. This study established an integrated framework to understand and control pigmentation in Aspergillus niger sodium gluconate fermentation. First, a metabolism-oriented scale-down strategy, simulating industrial glucose consumption trajectories, confirmed that metabolic rate deterioration drives pigment accumulation. Crucially, a rate-driven soft sensing strategy was developed by integrating online Raman spectroscopy, which provided real-time kinetic inputs to significantly enhance pigment prediction accuracy. Guided by this monitoring framework, inorganic salt composition was optimized to stabilize metabolic activity, effectively suppressing pigment formation. Crucially, fermentation validation confirmed that the strategy effectively suppressed abnormal pigmentation, even under existing imperfect oxygen supply conditions. This work presented a transferable engineering paradigm that combines metabolic characterization, intelligent spectral monitoring, and rational nutritional intervention, offering a robust solution for quality control in large-scale fungal fermentations.