基于近红外光谱法的藜麦脂肪含量快速检测  

Rapid Detection on Quinoa Fat Based on Near Infrared Spectroscopy

作　　者：曹晓宁[1,2,3] 田翔[1,2,3] 赵小娟[1,2,3] 王君杰[1,2,3] 刘思辰[1,2,3] 穆志新[1,2,3] 陈凌[1,2,3] 王海岗[1,2,3] 陆平[4] 陶梅[4] 秦慧彬[1,2,3] 乔治军[1,2,3] 

机构地区：[1]山西省农业科学院农作物品种资源研究所,太原030031 [2]农业部黄土高原作物基因资源与种质创制重点实验室,太原030031 [3]杂粮种质资源发掘与遗传改良山西省重点实验室,太原030031 [4]中国农业科学院作物科学研究所,北京100081

出　　处：《湖北农业科学》2016年第18期4796-4798,共3页Hubei Agricultural Sciences

基　　金：山西省农作物种质资源收集与整理项目(2016zzcx-17);农业部作物种质资源保护与利用专项(2015NWB030-07);科技部;财政部国家科技基础条件平台课题(NICGR2015-026);山西省种业专项(2016zyzx41)

摘　　要：为了探索一种快速测定完整藜麦（Chenopodium quinoa Willd）子粒脂肪含量的方法,采集100个藜麦样品的近红外光谱,运用近红外光谱法建立数学模型并进行预测。结果表明,在10 000~4 000 cm-1波长范围内,运用一阶导数＋矢量归一化光谱方法进行预处理,结合化学方法所得数据建立藜麦粗脂肪近红外光谱定量模型,校正和预测效果最佳,所得的粗脂肪近红外定量模型的交叉验证决定系数（R2cv）为0.939 3,外部验证决定系数（R2val）为0.9235。建立的脂肪近红外光谱模型,可以用于藜麦脂肪含量的快速检测。To explore a rapid determination method of fat content in grains of quinoa, collecting the near infrared spectra of100 quinoa samples,the predicted models for quantitative analysis of protein contents in the grains was built using near infrared transmittance spectroscopy（NITS）. Consequently,in the wavelength range of 10 000 ~4 000 cm-1,via first derivative ＋vector normalization preprocessing and combining with the data from chemical methods,we set up near infrared quantitative model of quinoa crude fat,meanwhile,calibration and prediction effect are best,and then the cross validation decision coefficient（R2cv）and external validation decision coefficient（R2val） of fat by near infrared quantitative model were 0.939 3 and0.923 5. In the end,the model of NITS about complete grains quinoa fat can be available for fast detecting quinoa fat content.

关 键 词：藜麦(Chenopodium QUINOA Willd) 脂肪 近红外光谱 快速检测 

分 类 号：O657.33[理学—分析化学]