Germination and storage of apple seeds

Apple seeds will not germinate immediately after the fruit has become mature enough for picking. It is necessary for the seed to pass thru a stage of after-ripening. The freshly extracted apple seed contains about 85 percent moisture. At room temperature approximately one-half of the moisture is lost during the first five days. Soaking the seed prior to planting does not increase germination. Ninety-one percent of apple seeds prevented from drying out when they were extracted from the fruit germinated. The best temperature for storage was found to be a temperature between 10 and 30 C. Seeds which had air dried germinated poorly in all cases. Apple seeds which had been air dried and kept for a year did not germinate. Apple seeds may be planted any time after Nov. 1. Where seeds are to be shipped long distances, special precaution must be made to keep the seeds from deteriorating. The seed coat is not a factor in causing delayed germination

The economic impact of chronic fatigue syndrome

BACKGROUND: Chronic fatigue syndrome (CFS) is a chronic incapacitating illness that affects between 400,000 and 800,000 Americans. Despite the disabling nature of this illness, scant research has addressed the economic impact of CFS either on those affected or on the national economy. METHODS: We used microsimulation methods to analyze data from a surveillance study of CFS in Wichita, Kansas, and derive estimates of productivity losses due to CFS. RESULTS: We estimated a 37% decline in household productivity and a 54% reduction in labor force productivity among people with CFS. The annual total value of lost productivity in the United States was $9.1 billion, which represents about$20,000 per person with CFS or approximately one-half of the household and labor force productivity of the average person with this syndrome. CONCLUSION: Lost productivity due to CFS was substantial both on an individual basis and relative to national estimates for other major illnesses. CFS resulted in a national productivity loss comparable to such losses from diseases of the digestive, immune and nervous systems, and from skin disorders. The extent of the burden indicates that continued research to determine the cause and potential therapies for CFS could provide substantial benefit both for individual patients and for the nation

Student Housing: Trends, Preferences And Needs

To attract and retain students, universities are confronted with increased demand to provide housing options that meet the new expectations of the millennial generation.  Recent trends and housing preferences are examined.  The results of surveys detailing some of these new demands and how universities are attempting to address these demands are discussed.  Additionally, universities are under pressure to efficiently use their limited resources and, as government support for higher education declines, public universities are seeking other sources of funding for major projects. Suggestions are made for unique partnering and financing options.&nbsp

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

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,

Adoption of Conservation-Tillage Practices in Cotton Production

Replaced with revised version of paper 10/23/07.conservation tillage, cotton, genetically modified seed, herbicide-resistant cotton, stacked-gene cotton, simultaneous logit model, single-equation logit model, technology adoption, Crop Production/Industries,

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

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

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 Agriculture Technology Adoption for Cotton Production

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,