Assessing soybean leaf area and leaf biomass by spectral measurements

Red and photographic infrared spectral radiances were correlated with soybean total leaf area index, green leaf area index, chlorotic leaf area index, green leaf biomass, chlorotic leaf biomass, and total biomass. The most significant correlations were found to exist between the IR/red radiance ratio data and green leaf area index and/or green leaf biomass (r squared equals 0.85 and 0.86, respectively). These findings demonstrate that remote sensing data can supply information basic to soybean canopy growth, development, and status by nondestructive determination of the green leaf area or green leaf biomass

Extracting scene feature vectors through modeling, volume 3

The remote estimation of the leaf area index of winter wheat at Finney County, Kansas was studied. The procedure developed consists of three activities: (1) field measurements; (2) model simulations; and (3) response classifications. The first activity is designed to identify model input parameters and develop a model evaluation data set. A stochastic plant canopy reflectance model is employed to simulate reflectance in the LANDSAT bands as a function of leaf area index for two phenological stages. An atmospheric model is used to translate these surface reflectances into simulated satellite radiance. A divergence classifier determines the relative similarity between model derived spectral responses and those of areas with unknown leaf area index. The unknown areas are assigned the index associated with the closest model response. This research demonstrated that the SRVC canopy reflectance model is appropriate for wheat scenes and that broad categories of leaf area index can be inferred from the procedure developed

Sensitivity analysis of leaf wetness duration within a potato canopy

A description and analysis is given of a wetness duration experiment, carried out in a potato field in the centre of the Netherlands in September 2005. The observations are used to design and evaluate a within-canopy dew model which provides the leaf wetness distribution within the canopy caused by dew processes and by precipitation. This withincanopy dew model consists of three layers (bottom, centre, top) each with equal contribution to the leaf area index. The model results compared favourably with experimental evidence. The sensitivity of the dew and precipitation interception on the amount of free water and the duration of the leaf wetness was analysed by varying the leaf area index and some important weather variables. The findings suggest that the leaf area index affects the amount of free water, but is barely sensitive to leaf wetness duration. Wind speed has hardly any effect on the amount of free water collection as well as on leaf wetness duration. The net radiation, however, appears to be sensitive to the amount of collected free water as well as the leaf wetness duratio

Wheat Productivity Estimates Using LANDSAT Data

The author has identified the following significant results. The biological leaf area index data show that there can be large variations in field vegetative condition from point to point. This is especially true in flood-irrigated fields, in which plant density (and development) varies drastically between rows that are in channels vs. those that are in raised areas. Considerable care must be used in interpreting the significance of isolated leaf area index measurements made from a single wheat row

Determining density of maize canopy. 2: Airborne multispectral scanner data

Multispectral scanner data were collected in two flights over a light colored soil background cover plot at an altitude of 305 m. Energy in eleven reflective wavelength band from 0.45 to 2.6 microns was recorded. Four growth stages of maize (Zea mays L.) gave a wide range of canopy densities for each flight date. Leaf area index measurements were taken from the twelve subplots and were used as a measure of canopy density. Ratio techniques were used to relate uncalibrated scanner response to leaf area index. The ratios of scanner data values for the 0.72 to 0.92 micron wavelength band over the 0.61 to 0.70 micron wavelength band were calculated for each plot. The ratios related very well to leaf area index for a given flight date. The results indicated that spectral data from maize canopies could be of value in determining canopy density

Relating the radar backscattering coefficient to leaf-area index

The relationship between the radar backscattering coefficient of a vegetation canopy, sigma(0) sub can, and the canopy's leaf area index (LAI) is examined. The relationship is established through the development of a model for corn and sorghum and another for wheat. Both models are extensions of the cloud model of Attema and Ulaby (1978). Analysis of experimental data measured at 8.6, 13.0, 17.0, and 35.6 GHz indicates that most of the temporal variations of sigma(0) sub can can be accounted for through variations in green LAI alone, if the latter is greater than 0.5

COVER Project and Earth resources research transition

Results of research in the remote sensing of natural boreal forest vegetation (the COVER project) are summarized. The study objectives were to establish a baseline forest test site; develop transforms of LANDSAT MSS and TM data for forest composition, biomass, leaf area index, and net primary productivity; and perform tasks required for testing hypotheses regarding observed spectral responses to changes in leaf area index in aspen. In addition, the transfer and documentation of data collected in the COVER project (removed from the Johnson Space Center following the discontinuation of Earth resources research at that facility) is described

Correlation and Path Analysis between Sorghum Yield to Growth and Yield Characters

Mutual association between characters of two sorghum varieties (ICSV III and SAMSORG 14) was determined using correlation coefficient of two years experiment. The percent contribution of growth and yield components to yield was also determined with path coefficient analysis. In both years and the average over the years, a positive and highly significant correlation was observed between sorghum yield and plant height, leaf area index and total dry matter. Likewise, sorghum yield also had a positive and highly significant interaction with panicle weight and 1000- grain weight. The highest individual contribution was made by leaf area index, followed by plant height. Total dry matter, panicle length and weight also contributed positively to the final yield. The highest combined percent contribution to yield resulted from plant height via leaf area index.  This was followed by contribution from plant height via panicle weight, panicle length via leaf area index respectively. In improving sorghum yield emphasis on breeding should be on its height, leaf area index and panicle length. Keywords: Sorghum, correlation, growth, regression and yield

Relationship between Flag Leaf Characteristics and Main Yield Components in Oat (Avena sativa L.)

The objective of this study was to investigate relationships between leaf area index, leaf chlorophyll concentration, yield components and grain yield in oat (Avena sativa L.). Ten oat varieties were analyzed in field conditions regarding those traits. Flag leaf chlorophyll concentration range between 451.51 and 747.79 units of μmol of chlorophyll per m2. Also, leaf area index range between 13.68 to 32.84 cm2. Significant correlation indices were highlighted between yield components and leaf area index, yield/yield components and chlorophyll concentration of flag leaf

Simulating Photosynthesis, Respiration and Dry Matter Production in Annual Crops

Crop simulation model, mathematical exhibition of physiological different process of crop growth and development and its response to environmental factors. Then the aim of  this study is to provide a computer model for simulating photosynthetic, respiration and dry matter production in annuls crop. In this model daily gross canopy photosynthetic rate is a fraction of the maximum photosynthetic rate of a fully developed canopy at light saturation. For calculation of that, leaf area index based on the relative length of the four different crop development stage is calculated. Leaf area index, minimum and maximum daily temperature and daily radiation as model inputs were considered. After calculating gross photosynthetic rate, growth and maintenance respiration waste minus its and daily dry matter is calculated based on conversion efficiency coefficient. Sunflower data is used for testing of model. Regression of simulated over observed dry matter yield and leaf area index showed a good correspondence between predicted and observed dry matter yield and leaf area index. R2  for both  dry matter yield and leaf area index were more than 0.95 suggesting that the model was successful in growth and yield crop