摘要
为研究温度对黄酒品质近红外光谱分析模型的影响,分别在5、10、15、20、25、30、35℃7个温度条件下采集黄酒样品的可见-近红外光谱,采用偏最小二乘法建立各温度下黄酒酒精度和总糖含量定量分析模型。结果表明:温度对样品光谱存在影响,主成分分析表明不同温度下的样品有明显聚类趋势。模型精度受温度影响较大,但并无随温度变化的一致趋势。建立的混合温度模型预测相对误差较小,有实际应用潜力。
In order to evaluate the influence of temperature on near-infrared spectroscopy(NIRS) analysis models of Chinese rice wine quality, NIR spectra of rice wine samples were collected at 5, 10, 15, 20, 25, 30 and 35 ℃, respectively. Calibration models for the quantification of alcohol and total sugar contents in rice wine were developed by partial least square(PLS) algorithm. The results indicated that the spectra of samples were affected by temperature. An obvious clustering tendency was detected by principal component analysis(PCA) between samples at different temperatures. The prediction ability of the calibration models was also influenced by temperature, but showing no consistent trend with temperature. The performance of the multi-temperature calibration models was suitable for practical application with low relative error values. These results provided a theoretical basis for rapid detection of rice wine quality as well as temperature correction by NIR spectroscopy.
出处
《食品科学》
EI
CAS
CSCD
北大核心
2014年第23期25-28,共4页
Food Science
基金
国家自然科学基金国家杰出青年科学基金项目(30825027)
关键词
温度
近红外光谱
偏最小二乘法
黄酒
品质
temperature
near infrared spectroscopy(NIRS)
partial least square
Chinese rice wine
quality
