Spatial pattern analysis of pre- and post-hurricane forest canopy structure in North Carolina,USA

Existing spatial patterns of a forest are in part a product of its disturbance history. Using laser altimetry and field measures of canopy top height to represent pre- and post-hurricane canopy topography, respectively, we measured changes in spatial patterns of stand structure of a United States southern mixed coniferous-deciduous for est. Autocorrelative and fractal properties were measured in this opportunistic study to quantify changes in canopy architecture along twelve, 190-250 m transects that were subjected to moderate to high levels of wind disturbance. Prior to the hurricane, canopy heights were autocorrelated at scales <40 m with an average fractal dimension of 1.71. After the disturbance, autocorrelation disappeared; the average fractal dimension rose to 1.94. This shift towards spatial randomness illustrates part of the cyclical nature of ecosystem development. It shows how a catastrophic collapse of biomass accumulation corresponds to a decrease in ecosystem organization across a landscape. This revised version was published online in July 2006 with corrections to the Cover Date.     

篱壁式红富士苹果光照分布及结果部位对果实品质的影响

作者对6～7年生篱壁式红富士苹果叶幕光照分布、结果部位对品质的影响进行了研究.结果表明:篱壁形叶幕光照垂直分布和水平分布的日变化相对均衡,树冠内未产生无效光区;品质垂直和水平分布与光照垂直和水平分布呈极显著正相关.中、下层中长果枝果实的果面光洁度分别为92.7%和97.2%,端正果率分别为91.6%和92.5%.     

水稻早衰产生原因及防治技术

根据多年从事基层水稻生产指导工作实践,分析水稻早衰产生的主要原因,并总结其防治技术措施.     

土壤温度对作物根区环境及玉米根冠生长的调控研究进展

土壤温度对作物的生长发育具有很强的调控作用。在全球气候变化背景下,根区土壤温度对玉米生长的影响及其调控机制已成为当前研究的一个热点。结合目前农业生产中土壤低温和高温对玉米造成危害的现状,从土壤温度对作物根区土壤环境以及玉米根系生长、冠层发育与产量形成的影响方面,综述土壤温度对玉米生长发育调控作用的研究进展,介绍改变土壤温度的措施以及对玉米土壤温度研究的发展方向进行展望,为今后的研究提供参考。     

棉花早衰的成因及预防措施

棉花早衰是指由于其自身或外部因素,在有效的生育期内,棉株局部或整体过早终止生命活动而影响棉花产量和品质形成的现象。该文综述了棉花早衰的表现及判断指标,分析了引起棉株发生早衰的因素,并提出了预防棉花早衰的对策措施,为今后开展相关工作提供参考。     

Estimation of litchi (Litchi chinensis Sonn.) leaf nitrogen content at different growth stages using canopy reflectance spectra

The estimation of crop nitrogen status in fresh vegetation leaf using field spectroscopy is challenging due to the weak responses on leaf/canopy reflectance and the overlapping with the absorption features of other compounds. Although the spectral indices were proposed in the literature to predict leaf nitrogen content (LNC), the performance of selected spectral indices to estimate the LNC is often inconsistent. Moreover, the models for nitrogen content estimation changed with the growth stage. The goal of this study was to evaluate the performance of published indices, ratio of data difference index (RDDI) and ratio of data index (RDI) developed by band iterative-optimization algorithm in LNC estimation. The correlation analysis, linear regression and cross validation were used to analyze the relationship between spectral data and LNC and construct the best performed estimation model. The study was conducted by the data of five growing seasons of litchi from the orchards in Guangdong Province of China. Results showed that the relationship between chlorophyll (Chl) related spectral indices and LNC varied with the growth stage. Even in flower bud morphological differentiation stage and autumn shoot maturation stage, there were not significant correlations between the proposed spectral indices and LNC. Besides it is difficult to estimate the LNC by the general model across the growth stages due to the integrated effects of cultivar, biochemical, canopy structure, etc. The band iterative-optimization algorithm can improve the sensitivity of spectral data to LNC to some extent. The optimal RDDI performed better than other indices for the synthetic dataset and the dataset in each growth stage. And the sensitive bands selected in the optimal indices at each growth stage are not consistent, which are not only related to the Chl absorption but also other biochemical components, such as starch, lignin, cellulose, protein, etc. In general, the LNC can be estimated by the optimized CR-based RDDI indices in autumn shoot maturation stage, flower spike stage, fruit maturation stage, and flowering stage with the R² > 0.50 and RMSE < 0.14. Although there were the significant relationship between RDIs and RDDIs in flower bud morphological differentiation stage, the highest R²s of the model developed by RDDIs and RDIs were less than 0.50 in cross validation. This study indicated that the applicability of canopy reflectance to estimate litchi LNC was closely related to the growth stage of litchi. Growth stage-specific models will be preferred for estimating litchi LNC estimation.