近红外反射分析法测定水稻可能再转流物质的研究  

Determination of Translocatable Matter of Rice by Near Infrared Reflectance Spectroscopy

作　　者：辛阳[1] 杨重法[1] 罗海伟[1] 姚立明[1] 朱鹏[1] 

机构地区：[1]海南大学农学院,海南海口570228

出　　处：《光谱学与光谱分析》2012年第9期2414-2417,共4页Spectroscopy and Spectral Analysis

基　　金：人事部留学回国择优项目(国人部发[2006]164);教育部留学回国科研基金项目(教外司留[2008]890)资助

摘　　要：为了探讨应用近红外反射分析法测定水稻可能再转流物质的可行性,以种植于海南儋州的7个水稻品种为试验材料,在淀粉酶处理结合中性洗涤纤维法分析的基础上,应用近红外反射分析法建立预测水稻茎叶部和穗部可能再转流物质含量的校正模型。结果表明:采用偏最小二乘法回归(PLS1)建立的校正模型的预测效果较好,光谱预处理对改进校正模型没有显著效果;采用不做预处理+PLS1建立的茎叶部和穗部校正模型都具有较高的预测准确度,校正模型的外部验证结果茎叶部的决定系数为0.991 2、均方根误差为0.008 1,穗部的决定系数为0.961 1、均方根误差为0.022 6。The potential of predicting translocatable matter of rice with near infrared reflectance spectroscopy（NIRS） was studied.Using 7 varieties of rice planted in Danzhou of Hainan province as materials,the method of neutral detergent fiber added amylase with NIRS was examined to establish calibration model of predicting translocatable matter of stem and panicle of rice.The results indicated that partial least square（PLS1） is the best regression statistic method for calibration model;The differences of results of the spectral data pretreatment methods for calibration model were insignificant;Because of the high prediction accuracy,the final calibration model was chosen using ＂no spectral data pretreatment＂＋＂PLS1＂;Determination coefficient of external validation and root mean square errors of prediction of the calibration model of stem and panicle was 0.991 2,0.008 1,0.961 1 and 0.022 6,respectively

关 键 词：水稻 可能再转流物质 近红外反射分析法 中性洗涤纤维法 

分 类 号：O657.3[理学—分析化学]