72 research outputs found

    Factors Influencing Adoption of Remotely Sensed Imagery for Site-Specific Management in Cotton Production

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    This research evaluated the factors that influenced cotton producers to adopt remote sensing for variable rate application of inputs. Farmers who were younger, more highly educated, had a larger farm operation, and were more technologically savvy were more likely to have adopted remote sensing.Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies,

    A Binary Logit Estimation of Factors Affecting Adoption of GPS Guidance Systems by Cotton Producers

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    Binary logit analysis was used to identify the factors influencing adoption of Global Positioning System (GPS) guidance systems by cotton farmers in 11 Mid-south and Southeastern states. Results indicate that adoption was more likely by those who had already adopted other precision-farming practices and had used computers for farm management. In addition, younger and more affluent farmers were more likely to adopt. Farmers with larger farms and with relatively high yields were also more likely to adopt. Education was not a significant factor in a farmer’s decision to adopt GPS guidance systems.binary logit, cotton, GPS guidance system, marginal effect, precision farming, technology adoption, Agribusiness, Crop Production/Industries, Q2, Q16, Q19, Q20, Q24,

    Adoption and Abandonment of Precision Soil Sampling in Cotton Production

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    Technology adoption in precision agriculture has received considerable attention, while abandonment has received little. Our objective was to identify factors motivating adoption and abandonment of precision soil sampling in cotton. Results indicate younger producers who farmed more cotton area, owned more of their cropland, planted more non-cotton area, used a computer, or used a Personal Digital Assistant (PDA) were more likely to adopt precision soil sampling. Those with more cotton area or who owned livestock were more likely to abandon, while those who used precision soil sampling longer, used a PDA, or used variable-rate fertilizer application were less likely to abandon.Crop Production/Industries,

    Precision Farming by Cotton Producers in Six Southern States: Results from the 2001 Southern Precision Farming Survey

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    Precision Farming by Cotton Producers in Six Southern States: Results from the 2001 Southern Precision Farming Surveycotton, precision farming, survey, Agribusiness, Farm Management, Production Economics, Research and Development/Tech Change/Emerging Technologies,

    Precision Agriculture Technology Adoption for Cotton Production

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    Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the number of specific types of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the influence of spatial yield variability on the number of precision farming technologies adopted, using a Count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a larger number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies were significantly correlated. Finally, farmers using computers for management decisions also adopted a larger number of precision agriculture technologies.precision technologies, Poisson, Negative Binomial, count-data method, GIS, education, cotton, Agricultural and Food Policy, Farm Management, Labor and Human Capital, Land Economics/Use, Productivity Analysis, Resource /Energy Economics and Policy,

    Intensity of Precision Agriculture Technology Adoption by Cotton Producers

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    Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the intensity of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the role of spatial yield variability on the number of precision farming technologies adopted, using a count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a higher number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies used were significantly correlated. Finally, farmers using computers for management decisions also adopted a higher number of precision agriculture technologies.precision technologies, Poisson, negative binomial count data method, GPS, education, cotton, Crop Production/Industries, Farm Management, Production Economics, Research and Development/Tech Change/Emerging Technologies,

    Precision Farming by Cotton Producers in Eleven Southern States: Results from the 2005 Southern Precision Farming Survey

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    Precision Farming by Cotton Producers in Eleven Southern States: Results from the 2005 Southern Precision Farming Surveycotton, precision farming, survey, Agribusiness, Farm Management, Production Economics, Research and Development/Tech Change/Emerging Technologies,

    Multimodal characterization of the late effects of traumatic brain injury: a methodological overview of the Late Effects of Traumatic Brain Injury Project

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    Epidemiological studies suggest that a single moderate-to-severe traumatic brain injury (TBI) is associated with an increased risk of neurodegenerative disease, including Alzheimer’s and Parkinson’s disease (AD and PD). Histopathological studies describe complex neurodegenerative pathologies in individuals exposed to single moderate-to-severe TBI or repetitive mild TBI, including chronic traumatic encephalopathy (CTE). However, the clinicopathological links between TBI and post-traumatic neurodegenerative diseases such as AD, PD, and CTE remain poorly understood. Here we describe the methodology of the Late Effects of TBI (LETBI) study, whose goals are to characterize chronic post-traumatic neuropathology and to identify in vivo biomarkers of post-traumatic neurodegeneration. LETBI participants undergo extensive clinical evaluation using National Institutes of Health TBI Common Data Elements, proteomic and genomic analysis, structural and functional MRI, and prospective consent for brain donation. Selected brain specimens undergo ultra-high resolution ex vivo MRI and histopathological evaluation including whole mount analysis. Co-registration of ex vivo and in vivo MRI data enables identification of ex vivo lesions that were present during life. In vivo signatures of postmortem pathology are then correlated with cognitive and behavioral data to characterize the clinical phenotype(s) associated with pathological brain lesions. We illustrate the study methods and demonstrate proof of concept for this approach by reporting results from the first LETBI participant, who despite the presence of multiple in vivo and ex vivo pathoanatomic lesions had normal cognition and was functionally independent until her mid-80s. The LETBI project represents a multidisciplinary effort to characterize post-traumatic neuropathology and identify in vivo signatures of postmortem pathology in a prospective study

    The North American tree-ring fire-scar network

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    Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree-ring fire-scar network (NAFSN), which contains 2562 sites, >37,000 fire-scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000-m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire-scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under-sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America
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