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Initial single\u2010adsorbent optimization using RSM achieved high decolorization rates of 92.5% (1.8% resin) and 92.0% (1.4% activated carbon), but suffered from poor pullulan recoveries of only 80.14% and 77.14%, respectively. For the first time, mechanistic analysis revealed that pigment adsorption from complex pullulan fermentation broth (mixed pigment fractions) follows a monolayer Langmuir model for D392 resin and a multilayer Freundlich model for activated carbon, both conforming to pseudo\u2010second\u2010order kinetics, providing a theoretical foundation for synergistic system design. Considering the intrinsic limitation of quadratic response surface models for describing highly nonlinear multi\u2010adsorbent interactions, a BP\u2010ANN network was further introduced, and an independent test subset was applied to objectively compare predictive performance. Leveraging these distinct adsorption properties, sequential adsorption was optimized using RSM and BP\u2010ANN, where the ANN demonstrated superior prediction accuracy. Under ANN\u2010optimized conditions (0.17% resin and 0.88% activated carbon), the hybrid system achieved 92% decolorization and 90.4% recovery, drastically reducing resin consumption by 90.76% and activated carbon by 37.14% compared with single\u2010adsorbent processes. Comprehensive characterization (ultraviolet\u2010visible spectroscopy, Fourier transform infrared spectroscopy, X\u2010ray diffraction, nuclear magnetic resonance, and scanning electron microscopy) confirmed that the native molecular structure and functional properties of pullulan were fully preserved. This work not only breaks the conventional trade\u2010off between decolorization efficiency and pullulan yield but also provides a novel, cost\u2010effective methodological paradigm for polysaccharide purification.<\/jats:p>","DOI":"10.1002\/jssc.70557","type":"journal-article","created":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T06:41:39Z","timestamp":1791960099000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Breaking the Decolorization Recovery Trade\u2010off: Hybrid Adsorbent System Coupled With Response Surface Methodology and Artificial Neural Network for Efficient Pullulan Purification"],"prefix":"10.1002","volume":"49","author":[{"given":"Qingli","family":"Guan","sequence":"first","affiliation":[{"name":"College of Bioengineering Tianjin University of Science and Technology  Tianjin China"},{"name":"Tianjin Engineering Research Center of Microbial Metabolism and Fermentation Process Control College of Biotechnology Tianjin University of Science and Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyue","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Bioengineering Tianjin University of Science and Technology  Tianjin China"},{"name":"Tianjin Engineering Research Center of Microbial Metabolism and Fermentation Process Control College of Biotechnology Tianjin University of Science and Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbin","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Bioengineering Tianjin University of Science and Technology  Tianjin China"},{"name":"Tianjin Engineering Research Center of Microbial Metabolism and Fermentation Process Control College of Biotechnology Tianjin University of Science and Technology  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingbin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Tianjin Huizhi Biotrans Bioengineering Co. 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