摘要
以71份薯叶和170份薯块根样品为材料,应用近红外光谱技术(NIRS)和偏最小二阶乘法(PLS),建立甘薯蛋白质含量近红外反射光谱分析数学模型,并对模型预测结果的准确性进行了评价。结果显示,甘薯叶和块根的蛋白质含量的近红外光谱预测模型校正决定系数(R2cal)分别为0.996和0.993,校正均方差(RMSEE)分别为0.255和0.126,内部交叉验证决定系数(R2cv)分别为0.984和0.986,均方差(RMSECV)分别为0.448和0.178。模型对样品NIR的预测值与其相应的化学值有较好的相关性,此模型可用来预测甘薯蛋白含量。在甘薯优质育种和品质分析中具有广泛的应用价值。
Predicted mathematic models for analysis of protein contents in 71 samples of leaves and 170 samples of roots from sweetpotato were established, with the technique of near infrared reflectance spectroscopy （NIRS） and partial least square （PLS） method, the protein contents of leaves and storage roots were determined by Kjeldahl methods. The veracity of models was estimated by the determination coefficients （R^2cal） and the root mean square errors of Calibration （RMSEE）, the determination coefficients（R^2cv） and the root mean square errors of Cross validation（RMSECV）. The results showed the R^2cal of NIR models of sweetpotato protein contents for leaves and roots were 0.996 and 0.993, the RMSEE were 0.255 and 0.126, respectively, the R^2cv of NIR models were 0.984 and 0.986, the RMSECV were 0.448 and 0.178, respectively. From the above results, the better relativities of the data for protein content from NIR method and chemical mensuration are concluded. The quantitative analysis data for protein content from NIR method can be accepted almostly, it can be widely used in the breeding and quality analysis of sweetpotato.
出处
《中国食品学报》
EI
CAS
CSCD
2008年第4期169-173,共5页
Journal of Chinese Institute Of Food Science and Technology
基金
国家科技支撑计划
江苏省高技术研究计划(BG2006309)
