摘要
根据偏最小二乘法建立番茄总糖含量的定量分析模型,比较原始光谱和平均光谱以及10种光谱预处理方法对近红外光谱无损检测番茄总糖含量的影响。结果表明:平均光谱所建立的偏最小二乘法校正模型明显优于原始光谱所建模型,常数偏移消除最适合番茄总糖近红外光谱的预处理,其在11998.9～7497.9cm-1和4601.3～4256.5cm-1优化光谱区内,所建偏最小二乘法定量分析模型的预测值和实测值的相关系数(R)为0.917,校正标准差(RMSEC)为0.263%,预测标准差(RMSEP)为0.236%。平均光谱和优化的光谱预处理方法可有效提高近红外光谱无损检测番茄总糖含量的准确性。
Based on the precision of quantitative analysis models established by application of partial least squares (PLS), the effects of average and original spectra as well as 10 spectral data preprocessing methods on near infrared spectroscopy (NIRS) nondestructive determination of total sugar (TS) content in tomatoes were analyzed. The results suggested that PLS correction model based on averaged spectrum is obviously superior than that based on original spectrum, and the constant offset elimina- tion (COE) is t...
出处
《食品科学》
EI
CAS
CSCD
北大核心
2009年第6期171-174,共4页
Food Science
基金
湖北省科技攻关项目(2004AA101D07)
关键词
番茄
近红外光谱
偏最小二乘法(PLS)
tomato
near infrared spectroscopy （NIRS）
partial least squares （PLS）
