林产化学与工业
林產化學與工業
림산화학여공업
CHEMISTRY AND INDUSTRY OF FOREST PRODUCTS
2014年
5期
91-96
,共6页
刁松锋%邵文豪%栾启福%董汝湘%姜景民
刁鬆鋒%邵文豪%欒啟福%董汝湘%薑景民
조송봉%소문호%란계복%동여상%강경민
无患子%近红外光谱%果皮%皂苷含量%偏最小二乘法
無患子%近紅外光譜%果皮%皂苷含量%偏最小二乘法
무환자%근홍외광보%과피%조감함량%편최소이승법
Sapindus mukorossi Gaertn.%near infrared spectroscopy%pericarp%saponin concent%PLS
为建立无患子( Sapindus mukorossi Gaertn.)果皮皂苷含量的快速检测模型,结合高效液相色谱法( HPLC),对采自浙江省天台县145份无患子果皮的皂苷含量进行检测。并依据近红外吸收光谱与HPLC测定数据的相关性,建立2个果皮皂苷含量估测模型,并对模型的准确性进行预测和评价。结果表明:A组(完整果皮)和B组(粉末状果皮)光谱数据分别基于“SNV+1 st derivative”和“MSC+1 st derivative”预处理法并利用PLS构建的光谱模型表现最佳,模型可靠性最强,预测精度最高,其中B组光谱数据建立的模型预测效果明显优于A组。基于A组和B组建立的模型与HPLC法的测量结果相关系数分别为0.654和0.993,预测标准偏差分别为0.982和0.294。以B组样品建立的模型基本可以代替HPLC法使用,而以A组样品建立的模型可用于测定精度要求不高、比较珍贵或样品量较少的样品。
為建立無患子( Sapindus mukorossi Gaertn.)果皮皂苷含量的快速檢測模型,結閤高效液相色譜法( HPLC),對採自浙江省天檯縣145份無患子果皮的皂苷含量進行檢測。併依據近紅外吸收光譜與HPLC測定數據的相關性,建立2箇果皮皂苷含量估測模型,併對模型的準確性進行預測和評價。結果錶明:A組(完整果皮)和B組(粉末狀果皮)光譜數據分彆基于“SNV+1 st derivative”和“MSC+1 st derivative”預處理法併利用PLS構建的光譜模型錶現最佳,模型可靠性最彊,預測精度最高,其中B組光譜數據建立的模型預測效果明顯優于A組。基于A組和B組建立的模型與HPLC法的測量結果相關繫數分彆為0.654和0.993,預測標準偏差分彆為0.982和0.294。以B組樣品建立的模型基本可以代替HPLC法使用,而以A組樣品建立的模型可用于測定精度要求不高、比較珍貴或樣品量較少的樣品。
위건립무환자( Sapindus mukorossi Gaertn.)과피조감함량적쾌속검측모형,결합고효액상색보법( HPLC),대채자절강성천태현145빈무환자과피적조감함량진행검측。병의거근홍외흡수광보여HPLC측정수거적상관성,건립2개과피조감함량고측모형,병대모형적준학성진행예측화평개。결과표명:A조(완정과피)화B조(분말상과피)광보수거분별기우“SNV+1 st derivative”화“MSC+1 st derivative”예처리법병이용PLS구건적광보모형표현최가,모형가고성최강,예측정도최고,기중B조광보수거건립적모형예측효과명현우우A조。기우A조화B조건립적모형여HPLC법적측량결과상관계수분별위0.654화0.993,예측표준편차분별위0.982화0.294。이B조양품건립적모형기본가이대체HPLC법사용,이이A조양품건립적모형가용우측정정도요구불고、비교진귀혹양품량교소적양품。
In the paper we aimed to provide a rapid, simple and accurate model for estimating of pericarp saponin concent in Sapindus mukorossi, based on the near infrared reflectance spectroscopy ( NIRs) and high performance liquid chromatography ( HPLC) . And 145 samples were collected from Tiantai County of Zhejiang Province. Based on the analysis data of HPLC and NIRs,two models of saponin concent determination were established, and the accuracy of the models were evaluated. The spectroscopic data of group A ( the whole fruit ) and group B ( the powder pericarp ) were obtained from the pretreatments of"SNV+1 st derivative" and "MSC + 1 st derivative". The results showed that the spectral models based on this data and established by PLS, were the best and the most reliable. They also had prediction precision. The model by group B was better than the model by group A. The models with groups A and B could reach 0. 654 and 0. 993 of the correlation coefficient between the prediction and the HPLC measured values. The standard deviations of prediction were 0. 982 and 0. 294, respectively. Thus, the model with the whole pericarp could be used to measure low quantity and precious samples with the relative low accuracy. The model with powder pericarp was very proper and could directly replace HPLC method.