Growing Sweetcorn in Alaska's Cool Environments

Sweet corn can be grown in Alaska's cool environments by employing clear polyethylene mulch to raise soil temperatures. Rows should be run north and south, spaced about 5 feet apart for 4-foot wide mulch. Weeds can be controlled under clear polyethylene mulch by spraying with atrazine after seeding and before mulching

CES P-143

This report summarizes the vegetable variety evaluations of the Horticulture Department of the University of Alaska, Fairbanks, 1979. Variety trials were conducted at the Agricultural Experiment Station’s research farm. The objective of this research is to select varieties of vegetables that are adapted to this environment. It also identifies types whose adaptability may be improved through development of cultural techniques. The selection effort is directed at finding varieties useful to commercial and home garden growers.Varieties are chosen for inclusion in the variety tests on the basis of their description, their latitude of origin, and the record o f the plant-breeding program for producing kinds that have previously been found adapted. Standard recommended varieties are included for comparison. In the past, the vegetable variety evaluation program has been responsible for a continuous improvement in yields, quality, and dependability for many vegetable crops. Our philosophy is to depend upon the many existing plant-breeding programs instead of investing in an expensive, on-site, plant-breeding program . Progress can be made more rapidly by selection than by breeding.Introduction -- Growing-Season Summary: Table 1: Rainfall by Month During the 1979 Growing S e a s o n; Table 2: Broccoli Variety Trials, Upland, 1979; Table 3: Cabbage Variety Trials, Upland, 1 9 79; Table 4: Carrot Variety Trials, Bottom land, 1979; Table 5: Cauliflower Variety Trials, Upland, 1979; Table 6: Cucumber Variety Trials, Upland, 1979; Table 7: Green Pea Variety Trials, 1979; Table 8: Lettuce Variety Trials, Bottom land, 1979; Table 9: Pepper Variety Trials, Upland, 1979; Table 10: Potato Variety Trials, Bottom land, 1979; T able 11: Pumpkin Variety Trials, Upland, 1979; Table 12: Snapbean Variety Trials, 1979; Table 13: Squash, Summer Variety Trials, Upland, 1979; Table 14: Squash, Winter Variety Trials, Upland, 1979; Table 15: Sweet Corn Variety Trials, Upland, 1979; Table 16: Tomato Variety Trials, Upland, 1979; Table 17: Tomato Variety Trials Without Plastic Mulch, Upland, 1979; Miscellaneous Vegetables Tested; Seed Sources

Cryogenic liquid level measuring probe

Universal probe, which contains a unique frequency discriminator, measures the static and dynamic levels of cryogenic liquids in a hydrogen bubble chamber. The probe allows boiling conditions or other turbulence to be observed throughout all the transition stages

Circular 43

This report summarizes the vegetable variety evaluations of the Horticulture Department of the University of Alaska, Fairbanks, 1982. Variety trials were all conducted at the Agricultural Experiment Station’s research farm at Fairbanks. The objective of this research is to select varieties of vegetables that are adapted to this environment. It also identifies types whose adaptability may be improved through development of improved cultural techniques. The selection effort is directed at finding varieties useful to both the commercial growers and home gardeners.Introduction -- Table 1:Climatic Data for the Fairbanks Growing Season: 1981, 1982, and the Long-Term Average -- Table 2: Broccoli Variety Trials, Upland, 1982 -- Table 3: Brussels Sprouts Variety Trials, Upland, 1982 -- Table 4: Cabbage Variety Trials, Upland, 1982 -- Table 5: Carrot Variety Trials, Bottomland, 1982 -- Table 6: Cauliflower Variety Trials, Upland, 1982 -- Table 7: Celery Variety Trials, Upland, 1982 -- Table 9: Eggplant Variety Trials, Upland, 1982 -- Table 10: Green Pea Variety Trials, Bottomland, 1982 -- Table 11: Crisphead Lettuce Variety Trials, Bottomland, 1982 -- Table 12: Pepper Variety Trials, Upland, 1982 -- Table 13: Potato Variety Trials, Bottomland Peat, 1982 -- Table 14: Pumpkin Variety Trials, Upland, 1982 -- Table 15: Snapbean Variety Trials, Upland, 1982 -- Table 16: Summer Squash Variety Trials, Upland, 1982 -- Table 17: Winter Squash Variety Trials, Upland, 1982 -- Table 18: Sweet Corn Variety Trials, Upland, 1982 -- Table 19: Tomato Variety Trials, Upland, 1982 -- Table 20: Container Tomato Variety Trials, 1982 -- Table 12: Miscellaneous Vegetables Tested -- Seed Source

Circular 35

Revised April 1991 by Grant E.M. Matheke, Patricia J. Wagner, and Patricia S. Holloway; Reprinted by Cooperative Extension Service, University of Alaska Fairbanks, and U.S.D.A. Cooperating. Publication 300C-00235A technique for growing high-yielding, everbearing strawberries with clear polyethylene (plastic) mulch and row covers has been developed at the Agricultural and Forestry Experiment Station at Fairbanks. This technique eliminates the long delay from planting to fruiting that occurs with other culture systems and it has created an interest in commercial production and an increased home-garden effort in Alaska. The production system involves planting nursery plants each season as early as possible through clear polyethylene mulch, using row covers for the early part o f the season. Using this technique, harvest begins about July 15 and extends until freeze-up, com pared to a production season from about July 10 to July 28 for hardy types o f strawberries such as Toklat or Pioneer. This system produces clean fruit, easy to pick and relatively free from fruit rot. The harvest season can be extended in the fall by again using the row covers for frost protection

Arsenic in the Water, Soil Bedrock, and Plants of the Ester Dome Area of Alaska

Concentrations of arsenic as large as 10 ppm (200 times the safe limit for drinking water) occur in the groundwater of a mineralized residential area near Fairbanks. Bedrock of the area contains 750 ppm As, primarily as arsenopyrite and scorodite. The oxygen-poor groundwater is enriched in As(III) and ferrous iron while the surface waters are iron free and contain less than 50 ppb As(V). Arsenic is removed from the water by coprecipitation with ferric hydroxide. Some iron-rich stream sediments contain as much as 1,400 ppm arsenic. The distribution of arsenic in the groundwater is controlled by the distribution of arsenic in the bedrock. The arsenic content of the B soil horizon over mineralized veins is about 150 ppm, while that over barren rock is 30 ppm. The vegetation over the veins is not significantly enriched in arsenic. Lettuce, radishes and tomatoes grown with arsenic-rich water (5 ppm) contain 16, 8 and 1 ppm As, respectively; these amounts are significantly greater than plants not treated with arsenic. Preliminary studies by state and federal health agencies show no detrimental effects on the health of persons drinking these arsenic-rich waters.The work upon which this publication is based was supported in part by funds provided by the Office of Water Research and Technology (Project B-037-ALAS, Agreement No. 14-34-0001-8056), U.S. Department of the Interior, Washington, D.C., as authorized by the Water Research and Development Act of 1978

Audio Caption: Listen and Tell

Increasing amount of research has shed light on machine perception of audio events, most of which concerns detection and classification tasks. However, human-like perception of audio scenes involves not only detecting and classifying audio sounds, but also summarizing the relationship between different audio events. Comparable research such as image caption has been conducted, yet the audio field is still quite barren. This paper introduces a manually-annotated dataset for audio caption. The purpose is to automatically generate natural sentences for audio scene description and to bridge the gap between machine perception of audio and image. The whole dataset is labelled in Mandarin and we also include translated English annotations. A baseline encoder-decoder model is provided for both English and Mandarin. Similar BLEU scores are derived for both languages: our model can generate understandable and data-related captions based on the dataset.Comment: accepted by ICASSP201