736 research outputs found

    Variations in primary production and particulate carbon flux through the base of the euphotic zone at the site of the Sediment Trap Intercomparison Experiment (Panama Basin)

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    C primary production data collected during the deployment and recovery cruises of STIE in 1979 showed a simple relationship with light and nutrient concentrations in the euophotic zone. A simple empirical relationship, calibrated using these data, was derived so that weekly averaged observations of fractional cloudiness, sea-surface temperature and mixed layer depth could be used to estimate primary production on a weekly basis for the years 1976–1979. 15N-uptake measurements, which estimate new production, were combined with the 14C data to estimate particulate carbon fluxes from the euphotic zone. Results of calculations showed that production may vary by a factor of three and particulate carbon flux by a factor of ten on a week to week basis with peak values corresponding to times when the mixed layer became enriched in nutrients. Mean euphotic zone production and particulate carbon flux estimated for the STIE deployment cruise were 286 and 138 mg C m–2 d–1, respectively; they were 174 and 59 mg C m–2 d–1 for the recovery cruise. Mean production and flux values were 261 and 122 mg C m–2 d–1, respectively for the duration of STIE. Three high production and particle sedimentation events may have occurred during STIE in September and October 1979. 1979 appeared to be a year of lower than average primary production compared with 1976 and 1977

    B827: Toward a Cooperative Marketing Strategy for Fresh Wild Blueberries

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    Marketing wild blueberries as a fresh product has become an increasingly viable alternative for Maine wild blueberry producers. This bulletin presents the results of research that identified marketing regions with the greatest profit potential for fresh wild blueberries and whether there are packaging or promotional strategies that are likely to be more successful than others within these regions. The authors analyze retail demand for fresh wild blueberries in Maine, Boston, and New York City, as well as describe the results of a survey of wholesale buyers of fresh blueberries in Boston. The conclusions based on the analysis of demand at these two levels of the marketing chain provide some interesting evidence with which to begin to develop a fresh wild blueberry marketing strategy.https://digitalcommons.library.umaine.edu/aes_bulletin/1042/thumbnail.jp

    Changes in Producers’ Perceptions of Within-field Yield Variability Following Adoption of Cotton Yield Monitors

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    Precision Farming, Risk, Yield Monitor, Yield Variability, Yield Perceptions, Spatial Yield Distributions, Within Field Variability, Farm Management, Production Economics, Risk and Uncertainty, Q12, Q16,

    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,
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