Varietal Difference in Leaf Nitrogen Content and Leaf Area and Their Effects to Ripening Rate During Mature Period of japonica Rice

Employing the pot experiment of the complete random block design with 6 replications,four varieties of japonica rice (Fujisaka 5,Honenwase,Akitakomachi and Taichung 65) were used to study the varietal differences in leaf nitrogen content(LNC) and leaf area during mature period,their relation and effects to the ripening rate.The results showed that(1) thee were varietal differences in LNC at the heading stage and the LNC decrease rate during the matue period,the high LNC at the heading stage was related to the rapid LNC decrease.(2) There were two phases of the leaf area changing process during the mature period,first was the stable,and second was the decreased phase.There was varietal difference in the critical time of phase 1 and phase 2.The hign leaf area in the phase 1 was in relation to the rapid leaf area decrease in the phase 2.It was not found that there was relation between the leaf quality and quantity.(3)It wa unfavorable to the ripening rate for the high leaf area at the heading stage and the rapid decrease of the leaf area during the mature period.(4)It was put forward that the super high yield rice variety should possess the not very high leaf area and high LNC at the heading stage,slow senescence in the leaf area during the mature period.

Direct measurement of the three-dimensional distribution of leaf area density and light conditions in a mature oak stand by the cube method

Although the distributions of foliage and light play major roles in various forest functions,accurate,nondestructive measurement of these distributions is difficult due to the complexity of the canopy structure.To evaluate the foliage and light distributions directly and nondestructively in a mature oak stand,we used the cube method by dividing the forest canopy into small cubes(50 cm per side)and directly measured leaf area density(LAD,the total one-sided leaf area per unit volume,i.e.,cube)and relative irradiance(RI)within each cube.The distribution of LAD and of RI was highly heterogeneous,even at the same canopy height.This heterogeneity reflected the presence of foliage clusters associated with multiple forking branches.The relationship between cumulative LAD at the canopy surface and average RI followed the Beer-Lambert law.The mean light extinction coefficient(K)was 0.32.However,K was overestimated by more than double(0.80)when calculated based on the classical method using RI at the forest floor.This overestimation was caused by the lower RI due to light absorption by nonleaf plant parts below the canopy.Our findings on the complex foliage and light distributions in canopy layers should help improve the accuracy of RI and K measurements and thus more accurate predictions of environmental responses and forest functions.

Litter production and leaf nutrient concentration and remobilization in response to climate seasonality in the central Amazon

Litterfall is the largest source of nutrients to for-est soils of tropical rainforests.However,variability in lit-terfall production,nutrient remobilization,and changes in leaf nutrient concentration with climate seasonality remain largely unknown for the central Amazon.This study meas-ured litterfall production,leaf nutrient remobilization,and leaf area index on a forest plateau in the central Amazon.Litterfall was measured at monthly intervals during 2014,while nitrogen,phosphorus,potassium,calcium and mag-nesium concentrations of leaf litter and canopy leaves were measured in the dry and rainy seasons,and remobilization rates determined.Leaf area index was also recorded in the dry and rainy seasons.Monthly litterfall varied from 33.2(in the rainy season)to 87.6 g m^(-2) in the dry season,while leaf area index increased slightly in the rainy season.Climatic seasonality had no effect on concentrations of nitrogen,calcium,and magnesium,whereas phosphorous and potassium responded to rainfall seasonality oppositely.While phosphorous increased,potassium decreased during the dry season.Over seasons,nitrogen,potassium,and phosphorous decreased in leaf litter;calcium increased in leaf litter,while magnesium remained unaffected with leaf aging.Regardless,the five nutrients had similar remobilization rates over the year.The absence of climate seasonality on nutrient remobilization suggests that the current length of the dry season does not alter nutrient remobilization rates but this may change as dry periods become more prolonged in the future due to climate change.

Single leaf area estimation models based on leaf weight of eucalyptus in southern China

Leaf area is an important parameter for modeling tree growth and physiological processes of trees. The single young and mature leaf area estimation models of eucalyptus were developed based on leaf fresh weight. In total, leaf area and leaf weight were measured from 455 fresh leaves of 25 trees of eucalyptus in southern China. The majority of the data （80%） were used for model calibration, and the remaining data （20%） were used for model validation. The linear, compound and power models were tested. Based on goodness of fit, prediction ability and residual performance, we found that linear and power models could best describe the relationship between leaf area and weight for young leaf and mature leaf, respectively. The study provides a simple and reliable method for estimating single-leaf area, which has a good potential in the functional- structural model of eucalyptus.

Quantity of plant leaf area on three major public squares in Kunming City, China

Regressive formulae to calculate the quantity of plant leaf area for 13 species of ornamental plants were set up based on investigation data of 30 species on 3 major public squares (Dongfeng square, Shengli square and Guandu square) in Kun-ming City, China, which were applied to calculate quantities of plant leaf area of these 13 species. The quantities of plant leaf area for the other 17 ornamental plant species on these squares were directly measured, and the total quantity of plant leaf area of each studied square was obtained individually. The results showed that the quantity of plant leaf area on Shengli square with ornamental plants structure composed of arbor tree species, shrub tree species and turf grass was highest among the three squares. It is believed that the design model of multi-storied vertical structure and proper tending of plant community could not only increase the quantity of plant leaf area, but also play an important role in generating ecological and landscaping benefits. Some corresponding suggestions were put forward on the basis of comprehensive analyses on the plant leaf area quantity of the three representative squares in Kunming urban area.

Quantitative Relationship between Leaf Area Index and Canopy Reflectance Spectra of Rice under Different Nitrogen Levels

Monitoring rice growth by spectral remote sensing technology can provide scientific basis for the high yield and efficient production of rice. Field experiments with different nitrogen application amounts using Tianyouhuazhan rice as test sam- ples were set up to study the relationship between rice leaf area index （LAI） and canopy reflectance spectral. The results showed that： the LAI increased with the amount of applied nitrogen; the canopy reflectance spectral showed significant re- sponse characteristics to groups with different nitrogen application levels; the corre- lation coefficient of LAI and canopy spectral reflectance reached the maximum at 720 nm red edge region. The mathematical model was constructed to predict the LAI according to the canopy reflectance spectra of rice.

Leaf Area Calculation Model of E.urophylla and E.grandis×E.urophylla

[Objective] The aim was to build an optimal leaf area measurement model of E. urophylla and E. grandis×E.urophylla. [Method] The correlation between leaf area and leaf＇s eigenvalue of E. urophylla and E. grandis×E.urophylla were studied. [Result] There was certain difference in leaf characteristics values between the 2 species. The leaf areas of E. urophylla and E. grandis×E.urophylla both had significant correlation with leaf length,leaf width,leaf perimeter,leaf length × leaf width,the ratio of leaf length to leaf width,shape factor,etc.,so the factors could be constructed into a regression model with leaf area. Among them,the best 2 models for leaf area calculation which were built by leaf length × leaf width of E. urophylla and E. grandis×E.urophylla both had relatively high accuracy and practical applications. [Conclusion] The research provides a simple and effective leaf area measurement method for studies on the 2 tree species.

Study on the Correlation Between Leaf Area and Drought Resistance in Different Alfalfa Varieties

[Objective] This study was to reveal the correlation between leaf area and drought resistance in different varieties of alfalfa.[Method] Using various alfalfa varieties as experimental materials,the drought resistance of leaves of drought-stressed alfalfa plants was assessed by measuring the content of free proline for analyzing its correlation with leaf area.[Result] Under drought condition,the drought resistance of alfalfa is directly related to leaf area in a positive correlation.[Conclusion] Leaf area could be used as an institutional assistant index to reflect the resistance of different alfalfa varieties.

Effects of Different Irrigation Times and Nitrogen Fertilizer Application on Leaf Area Index and Grain Yield of ‘Yujiao 5'

To provide ＂more reasonable, more saving and more efficient＂ water and fertilizer application proposals, taking ‘Yujiao 5＇ as the experimental material, the effects of different irrigation times and nitrogen application treatments on the leaf area index and yield of wheat were studied using three-factor split plot method. The results showed that irrigation times, nitrogen application rate and the ratio of basa to topdressed nitrogen respectively had significant effects on the leaf area index, the yield and component factors of wheat. Under the treatment of W1（irrigation before sowing）, the leaf area index showed a positive linear correlation with nitrogen application rate; under the treatments of W2（irrigation before sowing and at jointing stage） and W3（irrigation before sowing, at jointing stage and at grain filling stages）,the leaf area index showed a positive linear correlation with nitrogen application rate at the jointing stage, booting stage and heading stage; 20 d after heading, the leaf area index showed a quadric curve relationship with nitrogen application rate at these stages, and the LAI of N3R2 was the highest. Under different irrigation times,the yield, ear number and kernels per ear showed quadric curve relationship with nitrogen application rate, 1 000-seed weight showed the trend of linear decrease with the increase of nitrogen application rate. Under the treatment combination of irrigation before sowing, at jointing stage and at grain filling stage, nitrogen application rate at 240 kg/hm^2 and the ratio of basal to topdressed nitrogen of 5：5, the grain yield（8 609.60 kg/hm^2）, ear number（688.2×104/hm^2） and kernel number per ear（37.9 grains） reached the highest value at W3N3R2, and the grain yield of W3N3R2 increased by 144.8% compared to the W1N0. In conclusion, in Eastern Henan where the rainfall is insufficient at the late growth stage of wheat, the irrigation-saving space in wheat production is relatively small, but the nitrogen-saving space is relatively large.

Comparative analysis of GF-1,HJ-1,and Landsat-8 data for estimating the leaf area index of winter wheat

Using simultaneously collected remote sensing data and field measurements, this study firstly assessed the consistency and applicability of China high-resolution earth observation system satellite 1 （GF-1） wide field of view （WFV） camera, environment and disaster monitoring and forecasting satellite （H J-l） charge coupled device （CCD）, and Landsat-8 opera- tional land imager （OLI） data for estimating the leaf area index （LAI） of winter wheat via reflectance and vegetation indices （VIs）. The accuracies of these LAI estimates were then assessed through comparison with an empirical model and the PROSAIL radiative transfer model. The effects of radiation calibration, spectral response functions, and spatial resolution on discrepancies in the LAI estimates between the different sensors were also analyzed. The results yielded the following observations： （1） The correlation between reflectance from different sensors is relative good, with the adjusted coefficients of determination （R2） between 0.375 to 0.818. The differences in reflectance are ranging from 0.002 to 0.054. The correlation between VIs from different sensors is high with the R2 between 0.729 and 0.933. The differences in the VIs are ranging from 0.07 to 0.156. These results show the three sensors＇ images can all be used for cross calibration of the reflectance and VIs. （2） The four VIs from the three sensors are all demonstrated to be highly correlated with LAI （R2 between 0.703 and 0.849）. The linear models associated with the 2-band enhanced vegetation index （EVI2）, which feature the highest R2 （higher than 0.746） and the lowest root mean square errors （RMSE） （less than 0.21）, were selected to estimate the winter wheat LAI. The accuracy of the estimated LAI from Landsat-8 was the highest, with the relative errors （RE） of 2.18% and an RMSE of 0.13, while the H J-1 was the lowest, with the RE of 2.43% and the RMSE of 0.15. （3） The inversion errors in the different sensors＇ LAI estimates using the PROSAIL model are small. The accuracy of the GF-1 is the highest with the RE of 3.44%, and the RMSE of 0.22, whereas that of the H J-1 is the lowest with the RE of 4.95%, and the RMSE of 0.26. （4） The effects of the spectral response function and radiation calibration for the different sensors are small and can be ignored, but the effects of spatial resolution are significant and must be taken into consideration in practical applications.

New Vegetation Index and Its Application in Estimating Leaf Area Index of Rice

Leaf area index （LAI） is an important characteristic of land surface vegetation system, and is also a key parameter for the models of global water balancing and carbon circulation. By using the reflectance values of Landsat-5 blue, green and red channels simulated from rice reflectance spectrum, the sensitivities of the bands to LAI were analyzed, and the response and capability to estimate LAI of various NDVIs （normalized difference vegetation indices）, which were established by substituting the red band of general NDVI with all possible combinations of red, green and blue bands, were assessed. Finally, the conclusion was tested by rice data at different conditions. The sensitivities of red, green and blue bands to LAI were different under various conditions. When LAI was less than 3, red and blue bands were more sensitive to LAI. Though green band in the circumstances was less sensitive to LAI than red and blue bands, it was sensitive to LAI in a wider range. When the vegetation indices were constituted by all kinds of combinations of red, green and blue bands, the premise for making the sensitivity of these vegetation indices to LAI be meaningful was that the value of one of the combinations was greater than 0.024, i.e. visible reflectance （VIS）〉0.024. Otherwise, the vegetation indices would be saturated, resulting in lower estimation accuracy of LAI. Comparison on the capabilities of the vegetation indices derived from all kinds of combinations of red, green and blue bands to LAI estimation showed that GNDVI （Green NDVI） and GBNDVI （Green-Blue NDVI） had the best relations with LAI. The capabilities of GNDVI and GBNDVI to LAI estimation were tested under different circumstances, and the same result was acquired. It suggested that GNDVI and GBNDVI performed better to predict LAI than the conventional NDVI.

Mapping Spatial and Temporal Variations of Leaf Area Index for Winter Wheat in North China

Leaf area index （LAI） is an important parameter in a number of models related to ecosystem functioning, carbon budgets, climate, hydrology, and crop growth simulation. Mapping and monitoring the spatial and temporal variations of LAI are necessary for understanding crop growth and development at regional level. In this study, the relationships between LAI of winter wheat and Landsat TM spectral vegetation indices （SVIs） were analyzed by using the curve estimation procedure in North China Plain. The series of LAI maps retrieved by the best regression model were used to assess the spatial and temporal variations of winter wheat LAI. The results indicated that the general relationships between LAI and SVIs were curvilinear, and that the exponential model gave a better fit than the linear model or other nonlinear models for most SVIs. The best regression model was constructed using an exponential model between surface-reflectance-derived difference vegetation index （DVI） and LAI, with the adjusted R2 （0.82） and the RMSE （0.77）. The TM LAI maps retrieved from DVILAI model showed the significant spatial and temporal variations. The mean TM LAI value （30 m） for winter wheat of the study area increased from 1.29 （March 7, 2004） to 3.43 （April 8, 2004）, with standard deviations of 0.22 and 1.17, respectively. In conclusion, spectral vegetation indices from multi-temporal Landsat TM images can be used to produce fine-resolution LAI maps for winter wheat in North China Plain.

Relationship of 2 100-2 300 nm Spectral Characteristics of Wheat Canopy to Leaf Area Index and Leaf N as Affected by Leaf Water Content

The effects of leaf water status in a wheat canopy on the accuracy of estimating leaf area index (LAI) and N were determined in this study using extracted spectral characteristics in the 2 000-2 300 nm region of the short wave infrared (SWI) band. A newly defined spectral index, relative adsorptive index in the 2000-2300 nm region (RAI2000-2300), which can be calculated by RAI2000-2300 = (R2224 - R2054) (R2224 + R2054)-1 with R being the reflectance at 2224 or 2054 nm, was utilized. This spectral index, RAI2000-2300, was significantly correlated (P < 0.01) with green LAI and leaf N concentration and proved to be potentially valuable for monitoring plant green LAI and leaf N at the field canopy scale. Moreover, plant LAI could be monitored more easily and more successfully than plant leaf N. The study also showed that leaf water had a strong masking effect on the 2 000-2 300 nm spectral characteristics and both the coefficient between RAI2000-2300 and green LAI and that between RAI2000-2300 and leaf N content decreased as leaf water content increased.

Research on Measure Techniques Using CAD-Vector Method for Heteromorphism Leaf Area of Garden Trees

Heteromorphism leaf area of garden trees was measured by CAD-vector method.It was showed that all the coefficients of variation were below 1% when measurement accuracy was relatively high.This method was fit for accuracy area measurement of abnormity leaf,pests and disease leaf,big leaf,small leaf and so on.

Simulation of leaf area index and biomass at landscape scale

The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure was: (1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images; (2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated; (3) the relationship models between LAI and biomass were built and annual branch, stem, root and maximum leaf biomass over the landscape were simulated; (4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained. The simulation was based on spatial analysis module GRID in ArcInfo software. The method is also a kind of scaling method from patch scale to landscape scale. A case study of Changbai Mountain Nature Reserve was dissertated. Analysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.

Optimal waveband identification for estimation of leaf area index of paddy rice

The objectives of the study were to select suitable wavebands for rice leaf area index （LAI） estimation using the data acquired over a whole growing season, and to test the efficiency of the selected wavebands by comparing them with feature positions of rice canopy spectra. In this study, the field experiment in 2002 growing season was conducted at the experimental farm of Zhejiang University, Hangzhou, China. Measurements of hyperspectral reflectance （350-2500 nm） and corresponding LAI were made for a paddy rice canopy throughout the growing season. And three methods were employed to identify the optimal wavebands for paddy rice LAI estimation： correlation coefficient-based method, vegetation index-based method, and stepwise regression method. This research selected 15 wavebands in the region of 350-2500 nm, which appeared to be the optimal wavebands for the paddy rice LAI estimation. Of the selected wavebands, the most frequently occurring wavebands were centered around 554, 675, 723, and 1633 rim. They were followed by 444, 524, 576, 594, 804, 849, 974, 1074, 1219, 1510, and 2194 rim. Most of them made physical sense and had their counterparts in spectral known feature positions, which indicates the promising potential of the 15 selected wavebands for the retrieval of paddy rice LAI.

Assimilation of temporal-spatial leaf area index into the CERES-Wheat model with ensemble Kalman filter and uncertainty assessment for improving winter wheat yield estimation

To accurately estimate winter wheat yields and analyze the uncertainty in crop model data assimilations, winter wheat yield estimates were obtained by assimilating measured or remotely sensed leaf area index （LAI） values. The performances of the calibrated crop environment resource synthesis for wheat （CERES-Wheat） model for two different assimilation scenarios were compared by employing ensemble Kalman filter （EnKF）-based strategies. The uncertainty factors of the crop model data assimilation was analyzed by considering the observation errors, assimilation stages and temporal-spatial scales. Overalll the results indicated a better yield estimate performance when the EnKF-based strategy was used to comprehen- sively consider several factors in the initial conditions and observations. When using this strategy, an adjusted coefficients of determination （R2） of 0.84, a root mean square error （RMSE） of 323 kg ha-1, and a relative errors （RE） of 4.15% were obtained at the field plot scale and an R2 of 0.81, an RMSE of 362 kg ha-1, and an RE of 4.52% were obtained at the pixel scale of 30 mx30 m. With increasing observation errors, the accuracy of the yield estimates obviously decreased, but an acceptable estimate was observed when the observation errors were within 20%. Winter wheat yield estimates could be improved significantly by assimilating observations from the middle to the end of the crop growing seasons. With decreasing assimilation frequency and pixel resolution, the accuracy of the crop yield estimates decreased; however, the computation time decreased. It is important to consider reasonable temporal-spatial scales and assimilation stages to obtain tradeoffs between accuracy and computation time, especially in operational systems used for regional crop yield estimates.

Leaf area index retrieval based on canopy reflectance and vegetation index in eastern China

The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of TM3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.

Comprehensive Study on the Influence of Evapotranspiration and Albedo on Surface Temperature Related to Changes in the Leaf Area Index

Many studies have investigated the influence of evapotranspiration and albedo and emphasize their separate effects but ignore their interactive influences by changing vegetation status in large amplitudes. This paper focuses on the comprehensive influence of evapotranspiration and albedo on surface temperature by changing the leaf area index （LAD between 30^-90~N. Two LAI datasets with seasonally different amplitudes of vegetation change between 30^-90~N were used in the simulations. Seasonal differences between the results of the simulations are compared, and the major findings are as follows. （1） The interactive effects of evapotranspiration and albedo on surface temperature were different over different regions during three seasons [March-April-May （MAM）, June-July-August （JJA）, and September-October-November （SON）], i.e., they were always the same over the southeastern United States during these three seasons but were opposite over most regions between 30°-90°N during JJA. （2） Either evapotranspiration or albedo tended to be dominant over different areas and during different seasons. For example, evapotranspiration dominated almost all regions between 30^-90~N during JJA, whereas albedo played a dominant role over northwestern Eurasia during MAM and over central Eurasia during SON. （3） The response of evapotranspiration and albedo to an increase in LAI with different ranges showed different paces and signals. With relatively small amplitudes of increased LAI, the rate of the relative increase in evapotranspiration was quick, and positive changes happened in albedo. But both relative changes in evapotranspiration and albedo tended to be gentle, and the ratio of negative changes of albedo increased with relatively large increased amplitudes of LAI.

A NEW QUANTITATIVE WAY FOR DETERMINING LEAF AREA INDEX AND NET PRIMARY PRODUCTIVITY IN REGIONAL SCALE

An inversion of bidirectional reflection distribution fiJnedon (BRDF) wastested using NK Model and NOAA AVHRR datu. The test involVed sensitiveanalysis, optimum inversion selecting, ground simulated expenment, calibrahngmeasuremed with satellite and computer image processmg. Results of comparisonwith NDVI indicatal that inversion of BRDF will have brigh developing prospect inthe next decade.