姚延娟, 范闻捷, 刘 强, 李 丽, 陶 欣, 辛晓洲, 柳钦火. 玉米全生长期叶面积指数收获测量法的改进[J]. 农业工程学报, 2010, 26(8): 189-194.
    引用本文: 姚延娟, 范闻捷, 刘 强, 李 丽, 陶 欣, 辛晓洲, 柳钦火. 玉米全生长期叶面积指数收获测量法的改进[J]. 农业工程学报, 2010, 26(8): 189-194.
    Improved harvesting method for corn LAI measurement in corn whole growth stages[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(8): 189-194.
    Citation: Improved harvesting method for corn LAI measurement in corn whole growth stages[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(8): 189-194.

    玉米全生长期叶面积指数收获测量法的改进

    Improved harvesting method for corn LAI measurement in corn whole growth stages

    • 摘要: 农作物全生长期冠层表现不同的结构,常规的叶面积指数测量仪器不能适用于全生长期的叶面积指数测量,提出改进的收获测量法可进行玉米全生长期叶面积指数的测量,并且测量结果也具有可比性,该法在减少常规直接测量法工作量的同时也减少了对玉米的破坏。通过对比不同生长期单株样本叶面积计算的两种方法,得出二元二次回归法比常规的形状因子法计算精度高的结论。同时,分析不同生长期玉米秆所占总面积比例的规律,得出进行叶面积指数的准确测量,玉米秆的表面积必须进行准确考虑。该研究可为同类作物叶面积指数测量提供参考,可以有效推动叶面积指数的准确快速测量及遥感反演的验证工作。

       

      Abstract: Considering different canopy structures for the whole crop growth stages, it is not suitable to use traditional instrument to measure crop LAI for some growth stages, such as crop early growth stages with very sparse canopy structure. In order to obtain comparable and coherent LAI, the authors proposed the new method for corn LAI measurement, namely improved harvesting method (IHM). The IHM can reduce the measurement workload and the corn damage. Through the single corn total area comparison based on the two computing methods, namely the regression method and the shape factor method, it is shown that the regression method is better than shape factor method. Furthermore, based on the analysis of the ratio of stalk area to total area for the whole growth stages, the authors draw the conclusion that the stalk area must be considered for accurate LAI measurement. This work can provide some references for similar research and can accumulate the priori knowledge. The research of this paper will improve the study of LAI inversion and validation for remote sensing data.

       

    /

    返回文章
    返回