Graduate School of Agricultural Sciences, Kindai University, Nara, 631-8505, Japan.
Graduate School of Agricultural Science, Tohoku University, Sendai, 981-8555, Japan.
Sci Rep. 2018 Apr 23;8(1):6387. doi: 10.1038/s41598-018-24369-0.
Monitoring the vertical distribution of leaf area index (LAI) is an effective method for evaluating canopy photosynthesis and biomass productivity. In this study, we proposed a novel method to characterize LAI vertical distribution non-destructively by utilizing LAI-2200 plant canopy analyzer, followed by the application of statistical moment equations. Field experiments were conducted with 5 rice cultivars under 2 fertilizer treatments in 2013 and with 3 rice cultivars under 3 plant density treatments in 2014. LAI readings obtained by a plant canopy analyzer for non-destructive stratified measurements were relatively consistent with LAI estimations using the stratified clipping method for every cultivar and treatment. The parameters calculated using the statistical moment equations numerically showed the changes in LAI vertical distribution with plant growth up to the heading stage. The differences in the parameters also quantified the effect of cultivar, fertilizer, and plant density treatments. These results suggest that the non-destructive stratified measurements and the statistical moments evaluated in this study provide quantitative, reliable information on the dynamics of LAI vertical distribution. The method is expected to be utilized by researchers in various research fields sharing common interests.
监测叶面积指数(LAI)的垂直分布是评估冠层光合作用和生物量生产力的有效方法。本研究提出了一种利用 LAI-2200 植物冠层分析仪对 LAI 垂直分布进行非破坏性特征描述的新方法,然后应用统计矩方程。2013 年在 2 种施肥处理下对 5 个水稻品种进行了田间试验,2014 年在 3 种种植密度处理下对 3 个水稻品种进行了田间试验。利用植物冠层分析仪进行非破坏性分层测量获得的 LAI 读数与每种品种和处理的分层剪除法估算的 LAI 相对一致。使用统计矩方程计算的参数数值上显示了 LAI 垂直分布随植株生长到抽穗期的变化。参数的差异也量化了品种、肥料和种植密度处理的影响。这些结果表明,本研究中的非破坏性分层测量和评估的统计矩提供了 LAI 垂直分布动态的定量、可靠信息。该方法有望被具有共同兴趣的不同研究领域的研究人员所采用。