Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms

Agricultural crop classification models using two or more spectral regions (visible through microwave) are considered in an effort to estimate biomass at Guymon, Oklahoma Dalhart, Texas. Both grounds truth and aerial data were used. Results indicate that inclusion of C, L, and P band active microwave data, from look angles greater than 35 deg from nadir, with visible and infrared data improve crop discrimination and biomass estimates compared to results using only visible and infrared data. The microwave frequencies were sensitive to different biomass levels. The K and C band were sensitive to differences at low biomass levels, while P band was sensitive to differences at high biomass levels. Two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass. It is implied that inclusion of active microwave sensors with visible and infrared sensors on future satellites could aid in crop discrimination and biomass estimation

Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms, volume 2

Agricultural crop classification models using two or more spectral regions (visible through microwave) were developed and tested and biomass was estimated by including microwave with visible and infrared data. The study was conducted at Guymon, Oklahoma and Dalhart, Texas utilizing aircraft multispectral data and ground truth soil moisture and biomass information. Results indicate that inclusion of C, L, and P band active microwave data from look angles greater than 35 deg from nadir with visible and infrared data improved crop discrimination and biomass estimates compared to results using only visible and infrared data. The active microwave frequencies were sensitive to different biomass levels. In addition, two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass

A mathematical characterization of vegetation effect on microwave remote sensing from the Earth

In passive microwave remote sensing of the earth, a theoretical model that utilizes the radiative transfer equations was developed to account for the volume scattering effects of the vegetation canopy. Vegetation canopies such as alfalfa, sorghum, and corn are simulated by a layer of ellipsoidal scatterers and cylindrical structures. The ellipsoidal scatterers represent the leaves of vegetation and are randomly positioned and oriented. The orientation of ellipsoids is characterized by a probability density function of Eulerian angles of rotation. The cylindrical structures represent the stalks of vegetation and their radii are assumed to be much smaller than their lengths. The underlying soil is represented by a half-space medium with a homogeneous permittivity and uniform temperature profile. The radiative transfer quations are solved by a numerical method using a Gaussian quadrature formula to compute both the vertical and horizontal polarized brightness temperature as a function of observation angle. The theory was applied to the interpretation of experimental data obtained from sorghum covered fields near College Station, Texas

The 1981 Argentina ground data collection

Over 600 fields in the corn, soybean and wheat growing regions of the Argentine pampa were categorized by crop or cover type and ancillary data including crop calendars, historical crop production statistics and certain cropping practices were also gathered. A summary of the field work undertaken is included along with a country overview, a chronology of field trip planning and field work events, and the field work inventory of selected sample segments. LANDSAT images were annotated and used as the field work base and several hundred ground and aerial photographs were taken. These items along with segment descriptions are presented. Meetings were held with officials of the State Secretariat of Agriculture (SEAG) and the National Commission on Space Investigations (CNIE), and their support to the program are described

Flowering Development Stage in Sorghum Estimated from Optical Polarization Data

We tested the hypothesis that we can estimate the flowering developmentstage of sorghum from measurements of the polarization of the light scattered by asorghum canopy. Such information is critically important in agricultural productionforecasting. If such information were available for each sorghum field in a region, itcould be interleaved with timely weather data and used in crop production models toobtain improved estimates of sorghum grain production for the region

Strong succession in arbuscular mycorrhizal fungal communities.

The ecology of fungi lags behind that of plants and animals because most fungi are microscopic and hidden in their substrates. Here, we address the basic ecological process of fungal succession in nature using the microscopic, arbuscular mycorrhizal fungi (AMF) that form essential mutualisms with 70-90% of plants. We find a signal for temporal change in AMF community similarity that is 40-fold stronger than seen in the most recent studies, likely due to weekly samplings of roots, rhizosphere and soil throughout the 17 weeks from seedling to fruit maturity and the use of the fungal DNA barcode to recognize species in a simple, agricultural environment. We demonstrate the patterns of nestedness and turnover and the microbial equivalents of the processes of immigration and extinction, that is, appearance and disappearance. We also provide the first evidence that AMF species co-exist rather than simply co-occur by demonstrating negative, density-dependent population growth for multiple species. Our study shows the advantages of using fungi to test basic ecological hypotheses (e.g., nestedness v. turnover, immigration v. extinction, and coexistence theory) over periods as short as one season

Morphological Variation in the Wild-Weedy Complex of Sorghum bicolor In Situ in Western Kenya: Preliminary Evidence of Crop-to-Wild Gene Flow?

Crop wild relatives are important components of agroecosystems and have over the years been exploited in breeding programs as sources of genes for novel traits. Information on the extent and patterns of variability is important in formulating effective conservation and utilization strategies for existing crop wild relative populations. We conducted surveys and collections of wild and weedy accessions of Sorghum bicolor (L.) Moench in Lambwe Valley in western Kenya in order to investigate occurrence, distribution, and morphological variability in the wild-weedy complex of S. bicolor under local agroecological conditions. We also attempted to understand the role, if any, of crop-to-wild gene flow in structuring variability within and among populations. The morphological data presented here showed wide variability within wild-weedy sorghum populations with respect to habitats and morphotypes. True wild sorghum populations in national parks and the sugarcane belt were clearly distinguishable from the putative hybrids or intermediate forms found in sorghum fields, in sorghum field margins, and, to some extent, by the roadside near sorghum fields. The existence of these intermediate forms is empirical evidence of introgression between cultivated sorghum and its wild-weedy relatives. Extensive introgression, especially within in situ conservation areas and/or in areas of high diversity, would lead to genetic erosion and possible depletion of these important wild sorghum genetic resources

Algae in Agricultural Fields from St. Francis County, Arkansas

On August 9th, 2007, two agriculture fields (rice and sorghum fields) were sampled for freshwater algae in St. Francis County. The purpose of this study was to document the algal species in the rice and sorghum fields and compare the similarities of species composition. There were a total of 53 species identified. Overall, diatoms and cyanobacteria were equally dominant with both represented by 21 species (39.6% of the total) and 11 green algal species (20.8%) were present. The sorghum field was dominated by Chlorogloeopsis fritschii and Chroococcus limneticus, while Anabeana cylindrica was abundant in the rice field