Three rice landraces that have been continuously cultivated in Yuanyang County for hundreds of years by the local Hani people and three modern varieties cultivated in this area for 3-5 years were comparative tested on seven major agronomic characteristics at six different altitudes in the Yuanyang paddy field. The results indicated that agronomic characteristics of the landrace varieties, such as plant height, panicle length and number of effective panicles of landraces had no significant difference at different altitudes, whereas, those agronomic traits fluctuated in the modern varieties. In the Yuanyang terrace area, the Yuanyang landraces showed greater diversity in phenotype and better adaptation compared to the modern varieties.
PCA(Principal Component Analysis)常用于Biolog ECO和DGGE数据分析,但是该方法无法正确区分不同环境微生物的多样性结构,也无法实现微生物标记的发现。为实现该功能,研究采用PCA、PLS-DA(partial least squares-discriiminate analysis)、PLS-EDA(partial least squares-discriiminate enhance analysis)及PLS(partial least squares)、OPLS(orthogonal to partial least squares)方法对Biolog ECO和DGGE数据进行分析。结果表明:DGGE数据通过PLS-EDA分析方法能区分不同环境微生物多样性的结构(PC1=16.8%);采用PLS-DA分析方法,发现两个环境样品中有1个样品重合(PC1=33%);PCA分析方法分离效果最差(PC1=27.1%)。Biolog ECO数据通过PLS-EDA分析方法能区分不同环境微生物多样性的结构(PC1=25.5%);PLS-DA分析方法有4个样品重合(PC1=36.3%);PCA分析方法效果最差(PC1=35.1%)。Biolog ECO和DGGE数据进行PLS和OPLS分析方法筛选后,发现多个潜在的碳源及物种,可作为不同环境条件下微生物标记物。可见,PLS-EDA优于PLS-DA及PCA,是微生物研究的重要方法;PLS和OPLS分析方法中VIP(variable important value)≥1.00的条带和碳源可作为潜在的微生物标记。图7,表1,参24。
