中国食品学报

卡拉胶碱处理工艺与凝胶品质关联规律及预测模型研究

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刘月梅 ¹ , 蒋鹏 ² , 朱艳冰 ³,² , 洪涛 ³,² , 倪辉 ⁴,³,² , 姜泽东 ³,² , 郑明静 ³,²

中国食品学报 | 基础研究 2026,26(1): 58-68

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中国食品学报 | 基础研究 2026, 26(1): 58-68

卡拉胶碱处理工艺与凝胶品质关联规律及预测模型研究

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刘月梅¹, 蒋鹏², 朱艳冰³,², 洪涛³,², 倪辉⁴,³,², 姜泽东³,², 郑明静³,²

作者信息

^1.福建省绿麒食品胶体有限公司福建漳州 363107

^2.集美大学海洋食品与生物工程学院福建厦门 361021

^3.福建省食品微生物与酶工程重点实验室福建厦门 361021

^4.厦门海洋职业技术学院福建厦门 361102

Study on Correlation Law and Prediction Model of Carrageenan Alkali Treatment Process and Gel Quality

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出版时间: 2026-01-31 doi: 10.16429/j.1009-7848.2026.01.006

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目的:研究碱处理工艺与卡拉胶凝胶品质关联性规律及其预测模型。方法:采用碱提取法从麒麟菜中提取卡拉胶，利用人工神经网络(ANN)模型建立可靠的可测量模型，预测不同碱处理工艺条件下卡拉胶凝胶品质和分子特征结构。结果:人工神经网络模型对总集的拟合度R2 = 0.991高于多元线性模型(MLR)，平均绝对百分比误差(MAPE凝胶强度 = 1.71%，MAPE分子质量 = 18.84%，MAPE硫酸基 = 1.91%，MAPE3，6-内醚半乳糖 = 3.68%)均比MLR模型低。此外，在实际生产中，当碱处理关键工艺参数(温度、时间、质量分数)分别为65 ℃，6 h，10%时，测得卡拉胶的凝胶强度为614.32 g/cm2，而通过构建卡拉胶加工碱处理工艺与其凝胶品质关联性预测模型，预测该卡拉胶的凝胶强度为617.13 g/cm2。由此表明构建的凝胶品质关联性预测模型的预测值与实际生产中测得的结果相近。结论:人工神经网络模型的预测性能优于多元线性模型，ANN模型在预测卡拉胶凝胶特性和分子特征结构方面比MLR模型更准确。本研究为卡拉胶高品质产品的智能化精准制造提供了技术参考，以扩大卡拉胶在生物医药等领域的应用。

关键词

卡拉胶 / 凝胶强度 / 分子特征结构 / 多元线性模型 / 人工神经网络模型

Abstract

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Objective: Correlation between alkali treatment process and carrageenan gel quality and prediction model were studied. Method: Carrageenan was extracted from Eucheuma muricatum by alkali extraction method， and a reliable and measurable model was established to predict the gel properties and molecular characteristic structure of carrageenan under different alkali treatment process conditions using artificial neural network (ANN) model. Results: Artificial neural network model fit the total set with R2 = 0.991 better than the multivariate linear model (MLR)， with mean absolute percentage errors (MAPEgel strength = 1.71%， MAPEmolecule = 18.84%， and MAPEsulphate group = 1.91%， MAPE3，6-endoethergalactose = 3.68%) are lower than the MLR model. In addition， in actual production， when the key process parameters of alkali treatment (temperature， time， and concentration) were 65 ℃， 6 h， and 10%， the gel strength of carrageenan was measured to be 614.32 g/cm2， and the gel strength of carrageenan was predicted to be 617.13 g/cm2 by the constructed prediction model of the correlation between carrageenan processing alkali treatment and its gel quality. The results show that the predicted value of the model is close to that of the actual production. Conclusion: The prediction performance of ANN model is better than that of multivariate linear model， and ANN model is more accurate than MLR model in predicting carrageenan gel properties and molecular characteristic structure. This study provides a technical reference for the intelligent and precise manufacturing of carrageenan high-quality products， so as to expand the application of carrageenan in biomedicine and other fields.

Key words

carrageenan / gel strength / characteristic molecular structure / multiple linear model / artificial neural network model

引用本文

刘月梅, 蒋鹏, 朱艳冰, 洪涛, 倪辉, 姜泽东, 郑明静. 卡拉胶碱处理工艺与凝胶品质关联规律及预测模型研究. 中国食品学报, 2026 , 26 (1) : 58 -68 . DOI: 10.16429/j.1009-7848.2026.01.006

. Study on Correlation Law and Prediction Model of Carrageenan Alkali Treatment Process and Gel Quality[J]. Journal of Chinese Institute of Food Science and Technology, 2026 , 26 (1) : 58 -68 . DOI: 10.16429/j.1009-7848.2026.01.006

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国家自然科学基金面上项目
福建省科技计划项目

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2026年第26卷第1期

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doi: 10.16429/j.1009-7848.2026.01.006

接收时间：2025-02-26
首发时间：2026-05-27
出版时间：2026-01-31

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收稿日期：2025-02-26

基金

国家自然科学基金面上项目

福建省科技计划项目

作者信息

^1.福建省绿麒食品胶体有限公司福建漳州 363107

^2.集美大学海洋食品与生物工程学院福建厦门 361021

^3.福建省食品微生物与酶工程重点实验室福建厦门 361021

^4.厦门海洋职业技术学院福建厦门 361102

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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