基于长时间序列的遥感数据和气象数据,通过相关分析、趋势分析等方法,详尽分析了呼伦贝尔地区植被覆盖状况变化及其与气候的关系,得出以下主要结论:(1)20世纪80、90年代,呼伦贝尔以湿润气候区为主;进入21世纪后,气候呈现明显的暖干化趋势,尤其是大兴安岭林区北部、中部及东南部及呼伦贝尔草原的西南部地区湿润度指数呈显著减小趋势,半干旱和半湿润气候区在空间分布上占据了主要地位;(2)呼伦贝尔地区总体上表现出较高植被覆盖区面积减小、较低植被覆盖区面积增大的变化趋势,尤其是21世纪最初的十年,呼伦贝尔草原区的植被退化状况不容忽视,呼伦贝尔草原区中东部部分地区植被覆盖呈下降趋势;(3)呼伦贝尔草原西部、大兴安岭东南部农区部分地区的植被覆盖状况与湿润度指数呈正相关关系,而大兴安岭林区的中北部地区二者则呈负相关关系.

目的：建立芩双颗粒中甘草酸铵含量的测定方法.方法：采用ZORBAX SB-Aq色谱柱(4.6 mm×250mm，5μm)，流动相为乙腈（B）-0.1%磷酸水溶液（A）梯度洗脱，检测波长为237nm，流速为1.0mL·min-1，柱温为30℃.结果：甘草酸铵在0.240～1.440μg(r=0.9996)范围内线性关系良好.精密度、重现性、稳定性的RSD均小于2%，甘草酸铵的平均加样回收率分别为95.10%.结论：所采用方法可靠、准确、重现性好，可用于该制剂的含量测定及质量控制.

[Objective]The research aimed to develop a new method for the detection of flavonoid compounds of Scutellaria baicalensis Georgi by near infrared reflectance spectroscopy(NIRS).[Method]Firstly,through the principal component analysis(PCA) of spectroscopic curves of 4 kinds of Scutellaria baicalensis Georgi,the clustering of baicalin and wogonoside content of Scutellaria baicalensis Georgi was processed.Based on the PCA results,the first eight principal components were applied as artificial neural network(ANN) input nods,and 2 predictive indexes were applied as output nods,a testing model of near infrared reflectance spectroscopy with 8(input nods)-13(hidden layer nods)-2(output nods) was set up.[Result]The average relative error of NIRS model of baicalin and wogonoside content were 3.87% and 5.15%.The predicted value nearly was equal to HPLC value.The NIRS model had good predictability to analyze Scutellaria baicalensis Georgi quality.[Conclusion]NIRS model can be used on detecting Scutellaria baicalensis Georgi quality and quality controlling of Scutellaria baicalensis Georgi production processing.

[Objective] The aim was to put forward a new method for the detection of indigotin and indirubin contents in compound indigowoad root granule by using near infrared reflectance spectroscopy (NIRS).[Method]Firstly,through the principal component analysis method (PCA) to analyze spectroscopic curves of 6 kinds of compound indigowoad root granule which were obtained by spectrometer,then,combined with artificial neural network technology,the model was established to determine.The clustering of indigotin and indirubin content of indigowoad root granule was processed.Based on the PCA results,the first seven principal components were applied as ANN-BP input nods,and the 2 predictive indexes were applied as output nods,a testing model of artificial neural network(ANN-BP) with 7(input nods)-7(hidden layer nods)-2(output nods) was set up.[Result]The average relative error of NIRS model of indigotin and indirubin content were 4.14 % and 4.72%.The predicted value nearly was equal to HPLC value.The NIRS model had good predictability to analyze compound indigowoad root granule quality.[Conclusion]This NIRS model can be used on detecting compound indigowoad root granule quality and quality controlling of compound indigowoad root granule production processing.

A new method for discriminating the quality of schisandra chinensis based on near infrared spectroscopy and artificial neural network is proposed.The spectral curves of 90 schisandra chinensis samples from three different sources are obtained by using a near infrared spectrometer.The principal component analysis(PCA) method is used to make cluster analysis of the spectral data and to establish the analysis models of schizandrin A,schizandrin B and schsantherin A.The PCA result shows that the first five principal components have their cumulative reliability of 98.75%.The clustering is good.On the basis of the PCA result,an ANN model with 18 input nods,10 hidden layer nods and 3 output nods is established by using 18 absorption peaks of the first five principal components as input nods and taking 3 specifications as output nods.The ANN model predicts that the average relative error for 3 specifications of schizandrin A,schizandrin B and schsantherin A are 4.07%,2.65%,6.15%respectively.This is in good agreement with the prediction of HPLC.This model has an excellent prediction capability and can be used for quality checking and quality control of schisandra chinensis in a mass production process.

[Objective] The purpose was to provide theoretical basis for exploitation and use of Alfalfa.[Method] The compositions and contents of amino acids in the neck,leaf and seed of Alfalfa were analyzed with amino acid auto analyzer.[Result]The results indicated that the contents of amino acids of Alfalfa are abundant.The differences of contents of amino acids between different varieties and different parts of Alfalfa were large.The percentages on the dry weight of amino acids in the leaf,neck and seed of Alfalfa were 30.43%,24.44% and 18.31%.The analyzed results of essential amino acid and non-essential amino acid indicated that Alfalfa leaf had higher nutritional values.[Conclusion] The Alfalfa has the higher nutritional value and the development use value.

[Objective]The purpose aimed to realize nutrition value of Alfalfa leaves.[Method] Ten kinds of microelements(Na,K,Ca,Mg,Fe,Zn,Cu,Mn,Cr and Co) in leaves at seedling stage of Gongnong 1,Zhongmu 1,American Phabulous and American GoldenEmpress Alfalfa were detected and analysed by flame atomic absorption spectrometry(FAAS).[Result]The results indicated that the precision and recovery for different elements within the limits of working curves were good,the range of recovery(n=5) was 95%-105% and the RSD was lower than 5%.There were abundant nutritional elements for people in Alfalfa leaves.In the leaves of four Alfalfa,the content sequence of different microelements was found to be CaKZnMgNaFeMnCoCuCr.The content sequence of Na,Mg,Fe and Zn was Gongnong 1Zhongmu 1American PhabulousAmerican GoldenEmpress,the content sequence of Ca,Cu,Mn and Co was American GoldenEmpressGongnong 1American PhabulousZhongmu 1,the content sequence of K and Cr was Gongnong 1 American GoldenEmpress American PhabulousZhongmu 1.[Conclusion]The results of this study will provide useful evidence for effective exploitation of Alfalfa leaves.