首页|近红外光谱快速检测大豆原油含磷量

近红外光谱快速检测大豆原油含磷量

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
  • 维普
针对现有含磷量检测方法无法通过实时监测指导调控精炼过程中酸碱的添加量问题,提出一种基于近红外光谱分析的大豆原油含磷量的快速检测方法.对比分析发现标准正态变换法对大豆原油样本含磷量光谱数据的去除噪声效果最优.采用组合区间偏最小二乘法优选出磷脂的最佳特征吸收波段,选用学习效率0.005、训练次数108,建立了大豆原油含磷量的BP神经网络预测模型.模型校正集的决定系数(R2)为0.979 7、均方根误差(root mean square error,RMSE)为0.859 3、相对标准偏差(relative standard deviation,RSD)为 1.89％;预测集的R2为0.978 5、RMSE为0.963 8、RSD为2.15％.以上结果说明近红外光谱技术能够实现大豆原油中含磷量的快速、精准、无损检测,为后续精炼工段及调控提供切实可行的方法.
Fast Quantification of Phosphorus in Crude Soybean Oil by Near-Infrared Spectroscopy
The existing methods for the determination of phosphorus content are unable to regulate the addition of acid and base in the refining process of crude soybean oil through real-time monitoring.Therefore,a novel rapid method for determining the phosphorus content of crude soybean oil based on near-infrared spectroscopy was proposed in this study.It was found that standard normal variate transformation was more effective than two other spectral preprocessing methods evaluated for denoising the spectral data indicative of the phosphorus content in soybean crude oil.The characteristic absorption band of phosphorus was optimized by synergy interval partial least squares(SiPLS).A back propagation(BP)neural network prediction model of the phosphorus content in crude soybean oil was established with learning efficiency of 0.005 and 108 training cycles.The determination coefficient(R2),root mean square error(RMSE)and relative standard deviation(RSD)for the correction set were 0.979 7,0.859 3 and 1.89％,respectively.The R2,RMSE and RSD for the validation set were 0.978 5,0.963 8 and 2.15％,respectively.The above results showed that NIR spectroscopy can achieve rapid,accurate and non-destructive detection of the phosphorus content in,and provide a feasible method for the refining of crude soybean oil.

near-infrared spectroscopycrude soybean oilphosphorus contentsynergy interval partial least squaresback propagation neural network prediction

王雪、张海荣、吴丹丹、王伟宁、王立琦、罗淑年、于殿宇

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哈尔滨商业大学,黑龙江哈尔滨 150028

九三食品股份有限公司,黑龙江哈尔滨 150060

东北农业大学食品学院,黑龙江哈尔滨 150030

近红外光谱 大豆原油 含磷量 区间偏最小二乘法 BP神经网络

国家重点研发计划重点专项(十四五)黑龙江省教育厅学科协同创新成果项目

2021YFD2100302-01LJGXCG2023-031

2023

10.7506/spkx1002-6630-20230822-158

食品科学
北京食品科学研究院

食品科学

CSTPCDCSCD北大核心
影响因子：1.327
ISSN：1002-6630
年,卷(期)：2023.44(24)
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