2,625 research outputs found

    Comparisons among a new soil index and other two- and four-dimensional vegetation indices

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    The 2-D difference vegetation index (DVI) and perpendicular vegetation index (PVI), and the 4-D green vegetation index (GVI) are compared in LANDSAT MSS data from grain sorghum (Sorghum bicolor, L. Moench) fields for the years 1973 to 1977. PVI and DVI were more closely related to LAI than was GVI. A new 2-D soil line index (SLI), the vector distance from the soil line origin to the point of intersection of PVI with the soil line, is defined and compared with the 4-D soil brightness index, SBI. SLI (based on MSS and MSS7) and SL16 (based on MSS 5 and MSS 6) were smaller in magnitude than SBI but contained similar information about the soil background. These findings indicate that vegetation and soil indices calculated from the single visible and reflective infrared band sensor systems, such as the AVHRR of the TIROS-N polar orbiting series of satellites, will be meaningful for synoptic monitoring of renewable vegetation

    Estimating total standing herbaceous biomass production with LANDSAT MSS digital data

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    Rangeland biomass data were correlated with spectral vegetation indices, derived from LANDSAT MSS data. LANDSAT data from five range and three other land use sites in Willacv and Cameron Counties were collected on October 17 and December 10, 1975, and on July 31 and September 23, 1976. The overall linear correlation of total standing herbaceous biomass with the LANDSAT derived perpendicular vegetation index was highly significant (r = 0.90**) for these four dates. The standard error of estimate was 722 kg/ha. Biomass data were recorded for two of these range sites for 8 months (March through October) during the 1976 growing season. Standing green biomass accounted for most of the increase in herbage, starting in June and ending about September and October. These results indicate that satellite data may be useful for the estimation of total standing herbaceous biomass production that could aid range managers in assessing range condition and animal carrying capacities of large and inaccessible range holdings

    Vegetation density as deduced from ERTS-1 MSS response

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    Reflectance from vegetation increases with increasing vegetation density in the 0.75- to 1.35 micron wavelength interval. Therefore, ERTS-1 bands 6 (0.7 to 0.8 micron) and 7 (0.8 to 1.1 micron) contain information that should relate to the probable yield of crops and the animal carrying capacity of rangeland. The results of an experiment designed specifically to test the relations among leaf area index (LAI), plant population, plant cover and plant height, and the ERTS-1 MSS responses for 3 corn, 10 sorghum, and 10 cotton fields are given. Plant population was as useful as LAI for characterizing the sorghum and corn fields, and plant height was as good as LAI for characterizing cotton fields. These findings generally support the utility of ERTS-1 data for explaining variability in green biomass, harvestable forage and other indicators of productivity

    Methods of editing cloud and atmospheric layer affected pixels from satellite data

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    Subvisible cirrus clouds (SCi) were easily distinguished in mid-infrared (MIR) TIROS-N daytime data from south Texas and northeast Mexico. The MIR (3.55-3.93 micrometer) pixel digital count means of the SCi affected areas were more than 3.5 standard deviations on the cold side of the scene means. (These standard deviations were made free of the effects of unusual instrument error by factoring out the Ch 3 MIR noise on the basis of detailed examination of noisy and noise-free pixels). SCi affected areas in the IR Ch 4 (10.5-11.5 micrometer) appeared cooler than the general scene, but were not as prominent as in Ch 3, being less than 2 standard deviations from the scene mean. Ch 3 and 4 standard deviations and coefficients of variation are not reliable indicators, by themselves, of the presence of SCi because land features can have similar statistical properties

    Soil, Water, and Vegetation Conditions in South Texas

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    The author has identified the following significant results. Reflectance differences between the dead leaves of six crops (corn, cotton, sorghum, sugar cane, citrus, and avocado) and the respective bare soils where the dead leaves were lying on the ground were determined from laboratory spectrophotometric measurements over the 0.5- to 2.5 micron wavelength interval. The largest differences were in the near infrared waveband 0.75- to 1.35 microns. Leaf area index was predicted from plant height, percent ground cover, and plant population for irrigated and nonirrigated grain sorghum fields for the 1975 growing season

    Reflectance of vegetation, soil, and water

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    The author has identified the following significant results. Iron deficient and normal grain sorghum plants were sufficiently different spectrally in ERTS-1 band 5 CCT data to detect chlorotic sorghum areas 2.8 acres (1.1 hectares) or larger in size in computer printouts of the MSS data. The ratio of band 5 to band 7 or band 7 minus band 5 relates to vegetation ground cover conditions and helps to select training samples representative of differing vegetation maturity or vigor classes and to estimate ground cover or green vegetation density in the absence of ground information. The four plant parameters; leaf area index, plant population, plant cover, and plant height explained 87 to 93% of the variability in band 6 digital counts and from 59 to 90% of the variation in bands 4 and 5. A ground area 2244 acres in size was classified on a pixel by pixel basis using simultaneously acquired aircraft support and ERTS-1 data. Overall recognition for vegetables, immature crops and mixed shrubs, and bare soil categories was 64.5% for aircraft and 59.6% for spacecraft data, respectively. Overall recognition results on a per field basis were 61.8% for aircraft and 62.8% for ERTS-1 data

    Soil, water, and vegetation conditions in south Texas

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    The author has identified the following significant results. Software development for a computer-aided crop and soil survey system is nearing completion. Computer-aided variety classification accuracies using LANDSAT-1 MSS data for a 600 hectare citrus farm were 83% for Redblush grapefruit and 91% for oranges. These accuracies indicate that there is good potential for computer-aided inventories of grapefruit and orange citrus orchards with LANDSAT-type MSS data. Mean digital values of clouds differed statistically from those for crop, soil, and water entities, and those for cloud shadows were enough lower than sunlit crop and soil to be distinguishable. The standard errors of estimate for the calibration of computer compatible tape coordinate system (pixel and record) to earth coordinate system (longitude and latitude) for 6 LANDSAT scenes ranged from 0.72 to 1.50 pixels and from 0.58 to 1.75 records

    Methods of editing cloud and atmospheric layer affected pixels from satellite data

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    The location and migration of cloud, land and water features were examined in spectral space (reflective VIS vs. emissive IR). Daytime HCMM data showed two distinct types of cloud affected pixels in the south Texas test area. High altitude cirrus and/or cirrostratus and "subvisible cirrus" (SCi) reflected the same or only slightly more than land features. In the emissive band, the digital counts ranged from 1 to over 75 and overlapped land features. Pixels consisting of cumulus clouds, or of mixed cumulus and landscape, clustered in a different area of spectral space than the high altitude cloud pixels. Cumulus affected pixels were more reflective than land and water pixels. In August the high altitude clouds and SCi were more emissive than similar clouds were in July. Four-channel TIROS-N data were examined with the objective of developing a multispectral screening technique for removing SCi contaminated data

    Population Dynamics, Disturbance, and Pattern Evolution: Identifying the Fundamental Scales of Organization in a Model Ecosystem

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    ABSTRACT We used auto‐ and cross‐correlation analysis and Ripley's K ‐function analysis to analyze spatiotemporal pattern evolution in a spatially explicit simulation model of a semiarid shrubland (Karoo, South Africa) and to determine the impact of small‐scale disturbances on system dynamics. Without disturnities bance, local dynamics were driven by a pattern of cyclic succession, where ‘colonizer’ and ‘successor’ species alternately replaced each other. This results in a strong pattern of negative correlation in the temporal distribution of colonizer and successor species. As disturbance rates were increased, the relationship shifted from being negatively correlated in time to being positively correlated—the dynamics became decoupled from the ecologically driven cyclic succession and were increasingly influenced by abiotic factors (e.g., rainfall events). Further analysis of the spatial relationships among colonizer and successor species showed that, without disturbance, periods of attraction and repulsion between colonizer and successor species alternate cyclically at intermediate spatial scales. This was due to the spatial ‘memory’ embedded in the system through the process of cyclic succession. With the addition of disturbance, this pattern breaks down, although there is some indication of increasing ecological organization at broader spatial scales. We suggest that many of the insights that can be gained through spatially explicit models will only be obtained through a direct analysis of the spatial patterns produced

    Methods for expression of recombinant proteins using a Pichia pastoris cell-free system

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    Cell‐free protein synthesis is a powerful tool for engineering biology and has been utilized in many diverse applications, from biosensing and protein prototyping to biomanufacturing and the design of metabolic pathways. By exploiting host cellular machinery decoupled from cellular growth, proteins can be produced in vitro both on demand and rapidly. Eukaryotic cell‐free platforms are often neglected due to perceived complexity and low yields relative to their prokaryotic counterparts, despite providing a number of advantageous properties. The yeast Pichia pastoris (also known as Komagataella phaffii) is a particularly attractive eukaryotic host from which to generate cell‐free extracts, due to its ability to grow to high cell densities with high volumetric productivity, genetic tractability for strain engineering, and ability to perform post‐translational modifications. Here, we describe methods for conducting cell‐free protein synthesis using P. pastoris as the host, from preparing the cell lysates to protocols for both coupled and linked transcription‐translation reactions. By providing these methodologies, we hope to encourage the adoption of the platform by new and experienced users alike
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