Agriculture and Horticulture
Non Technical Summary
Climate change in Alaska is already happening and the current warming climatic conditions will allow Alaska to become a major food crop production area in USA. This project aimsto develop, evaluate, and select crops that can be grown in Alaska. Those crops include hard red spring wheat, Polish canola, semi dwarf sunflower, feed barley with malting potential, and cover crops suitable for three different regions of Alaska. The relationship between crop growth and climatic variables is also important in understanding directions of crop development and selection. For example, the temperature distribution during the growing season and such distribution impact on growth stages of tested crops. Artificial intelligent algorithms will be used to ascertain such relationships, which will significantly improve our understanding on climate change impact on Alaska's agriculture production and agriculture potential in the future. Also, such workwill lay thefoundation for future cooperation and competitive proposal development with universities in lower 48 states. All research results will bedisseminated to public and professionals which includes the release of crop cultivars and cover crop information to Alaska's farmers and farms in US Pacific Northwest coast area, publications for extension and outreach to growers, and for professional peer reviewed papers, and presentations both for growers and professional conferences.Continuing toevaluate crops such as barley (feed, hull-less, and malting), hard red spring wheat, and oilseeds will provide new information for Alaska producers. This will help Alaska growers to find alternative crops, particularly feed barley potentially to be used as malting barley, and hard red spring wheat for food of Alaskans. This is the focus of Objective 1. The open pollinated Polish canola cultivar experiment will lead to the selection of a new canola cultivar which is suitable for local climatic conditions. As such, local growers will have a reliable seed source as well as a suitable rotational crop for improving yields, disease resistance, weed control and a reliable oilseed supply for local markets. Selection of the dwarf sunflower that matures early for combining will allow Alaska growers to have a niche crop (Objective 2). Objective 3 is to evaluate cover crops and cover crop combinations so that growers in Alaska can use them to increase soil productivity and maintain soil health. Objective 4 is to fill the information the gap of field crop performance information and current and future climate change variables. This will provide outlook for crop production potential in Alaskacurrently and in the future. We will produce outreach products such as presentations, publications, and peer reviewed journal papers to our clients both in Alaska and outside of Alaska. All of these fit USDA-NIFA 2014-2018 Strategic Goals 1, 3 and 4.
Animal Health Component
Research Effort Categories
Goals / Objectives
The objectives of this research are to:1) continue to identity and select malting, hull-less, and feed barley, spring wheat (Ingal crosses with three Canadian varieties, and other Nordic varieties) and rye cultivars that can be grown in Alaska with a reasonable assurance of a successful harvest to supply the local markets, and continue testing and selecting from the original dwarf sunflower so thatit can be an economic crop (i.e. bird feed) in Alaska,2) develop and select an open pollinated Polish canola variety that is suitable for Alaska growing conditions, and continue to select dwarf sunflower,3) develop cover crop seed mixtures so that they can be used for Alaska in different regions for soil quality improvement,4) develop an AI-based crop model so that crop performance can be predicted in the future, and,5) reach out to Alaska growers by publishing results from variety tests and cover crop practices evaluated in Agricultural and Forestry Experiment Station bulletins and other outlets.
Objective 1. Wewill conduct aliterature search for information, and cooperate with breeders in US Western land grant universities to select northern adapted varieties of malting and hull-less barley, spring wheat Nordic varieties and crosses of "Ingal" with CDC Bounty, AC Intrepid, and Roblin along with their parent materials, and rye from northern Canada and US sources both from universities and industries. The tentative crops to be tested are listed in Table 1. We will evaluate these varieties for three to five years at Fairbanks, and Palmer Alaska. New varieties will be added as they become available and older ones obviously not well adapted to the locations will be dropped. Crops will be seeded in small plots 2 m by 9 m (6 feet by 30 feet) with proper seeding rates depending on variety and crop. We will collect daily weather data (precipitation, air and soil temperatures, and potential evaporation) at each location using the established weather stations in the fields. Air and soil temperature will be determined continuously by using HOBO temperature sensors located above the soil surface, at the soil surface and within the root zone, and soil moisture within the root zone will be determined by sampling soils at 0-15 cm at different growth stages and also by placing moisture sensors in the root zone. During the growing season, we will record physiologic growth stage information (time of emergence, heading, maturity), plant height, lodging and disease resistance for each plot. At harvest, we will determine yield and test weights for each plot. Grains of malting barley or feed barley used for malt will be tested for germination and protein content, and will be sent to commercial a laboratory for malting quality analysis. The experiment is a complete randomized block design with three replicates. Data will be statistically analyzed using ANOVA and least significant difference (Fisher) for mean comparison at 5% probability. Statistical analysis will be also conducted for relationships between maturity and yield versus heat units received (i.e. growing degree days), precipitation, etc. We will then be able to use this information along with long term weather records to predict the likelihood of a variety maturing in a given location. This information will be used to make variety recommendations to farmers in each major agricultural regions (i.e. Fairbanks and Delta Junction) of Alaska. The dwarf sunflower selection for agronomic quality (i.e. combine harvesting) is still a few years away from release. We will continue to make selections in Fairbanks to increase genetic uniformity and early maturity so that the head can be dried enough for combining. The selection criteria are early, and uniform in maturity to produce evenly dry heads that can be combined. These selections will be disseminated to selected cooperators with a cultivation protocol for testing in growers' field as a potential agronomic crop. Data collected during the experiments include emergence, plant height, time of flowering and maturity, kernel weight, and yield, at time of release, seed oil content and protein will be analyzed. The experiment will be conducted only at the Fairbanks location.Table 1. Tentative list of crops to be included in the project.No.CropNameSeeding rate(lbs/acre)Seeding time1BarleyOtal90May2BarleyLidal90May3BarleyFinaska90May4BarleyDatal90May5BarleyWooding90May6Hooded barleyWeal90May7Hulless barleySunshine90May8Hulless barleyThual90May9Yellow oatToral90May10Yellow oatCeal90May11Hulless oatBelmont90May12Hard red spring wheatNogal90May13Hard red spring wheatIngal90May14Hard red spring wheatAAC redwater90May15Hard red spring wheatCDC Bounty90May16Hard red spring wheatAC Intrepid90May17Hard red spring wheatRoblin90May18Hard red spring wheatIngal x CDC Bounty90May19Hard red spring wheatIngal x AC Intrepid90May20Hard red spring wheatIngal x Roblin90May21Hard red spring wheatNAMO 4090May22Hard red spring wheatNAMO 4290May23Hard red spring wheatNAMO 4390May24Semi dwarf sunflowerMidnight Sun6.2MayObjective 2. Developing and selecting an open pollinated Polish canola cultivar that is suitable inAlaska, by growing a mixture of different Polish canola cultivars. These cultivars include Colt, Horizon, Reward, Hysin 110, and AC Sunbeam that are short growing season Polish canola varieties and they are GMO free. Seeds will be collected each year during the project time and examined for their quality such as green seed content, oil content, kernel weight, and germination rate. The experiment will be conducted in 6 ft by 30 ft (2 m x 9m) plots in three replicates in Fairbanks and Palmer areas. Since this canola is an open pollinated species, through this experiment, we hope to develop a cultivar that is suitable for local climatic conditions so that Alaska growers can have an economic and reliable canola seed source. Data collected will be statistically analyzed (ANOVA and LSD). We will also continue to select dwarf sunflower so that they can reach maturity for combining. In each year, about 20 plants will be seeded and early matured ones will be selected and processed. Seeds from selected ones will be planted in next year.Objective 3. Cover crop mixtures will be evaluated for their biomass production, and their impact on soil quality. Alaska varies in climatic conditions from coast to interior. Cover crop combinations chosen for evaluation will meet the needs in those various climatic conditions. The combinations of cover crops are 1) red clover + oat, 2) red clover + Italian rye, and 3) red clover + buckwheat. Those combinations will be tested in Palmer and Fairbanks areas. Since the Palmer is close Alaska coast area, the results should be applicable to the coast area. The combinations will be seeded in May in 6 ft by 27 ft plots in three replicates. Soil samples will be taken at each end of growing season for determination of soil properties (e.g. nutrients, organic matter etc.). Data will be statistically analyzed (i.e. ANOVA and LSD for mean comparison).Objective 4. All field results along with the past results will be used for simulation using two totally different types of models, plant physiological based model, and statistical or AI models. Future climate change scenarios (temperature change in next 30 or 50 years during the growing season), and temperature variations during the growing seasons in relationship with different growth stages will be simulated. The results of the two models will also be compared using same dataset. For plant physiological model, DSSAT 4.5 will be used for the simulation. But for statistical model, we will use supervised and unsupervised learning. From those two approaches, a variety of algorithms will be tested such as principal component analysis, k-means, smart vector machine, random forest and neural network for their fitness using root mean square error (RMSE). We will closely cooperate with climate change scientists in the University of Alaska Fairbanks and with universities of lower 48 states with similar interests, and also will work closely with the USDA multi state group on impact of climate change on crops growth in central states. Through this cooperation, we hope to develop new proposals at the regional level.Objective 5. Results from objectives 1 to 4 will be statistically analyzed using ANOVA for treatment effects and LSD for mean comparisons. The results will be summarized and presented in the producers meetings (such as Harvest Wrap-up) annually or field days organized extension specialists. Results will be also presented in the national professional conference such as AGU, and Agronomy Society of America annual conference. Results will be published in extension bulletins, and peer reviewed journals. Annual reports will be also written for USDA-NIFA.