Identifying and Distinguishing Between Nitrogen and Water Stress.

There is a need to develop more efficient soil fertility and nutrient management strategies in order to maximize wheat grain yields and increase grain protein levels. Growing concerns associated with water shortage and climate change emphasize the importance of nutrient management research, specifically targeting water-related challenges pertinent to semi-arid southwest region. Cereal producers are under continuous pressure to increase yields and maintain profitability, while addressing high fertilizer costs and environmental constraints. Crop production, especially in the southern Idaho, is highly dependent on irrigation due to low rainfall. Furthermore, crop production in irrigated areas continues to be more water-constrained. Water and nitrogen fertilizer are both essential inputs to ensure successful plant growth and achieve optimal crop yield. Thus, accurate and timely information regarding both water and nitrogen status obtained with remote sensors can be of tremendous help for irrigation and fertilization decision making. The crop physiological parameters such as leaf nitrogen content, chlorophyll, and canopy temperature as influenced by the different abiotic stressors can be measured by utilizing the remote sensing methodology at the canopy level. Although wheat growth and yield responses to nitrogen fertilizer and water management have received extensive attention, to date, only limited reports exist on identifying the empirical relationships between plant nitrogen and water status with hyperspectral reflectance. This project's key objective is: To Develop effective system for nitrogen and water management in wheat. Specifically: 1) To evaluate the effects of nitrogen rates and irrigation treatments on wheat plant growth and yield; 2) To develop methods to predict yield and grain protein content in varying nitrogen and water environments, and to determine the minimum nitrogen and water required to maintain wheat grain yield and quality; and 3) To develop models predicting yield loss due to nitrogen stress and yield loss due to water stress. Hard red spring wheat was planted at two experimental locations in south-west Idaho: at Parma Research & Extension Center and in a cooperating grower’s field, near Parma, in April 2015. The experiments were laid out in a split-plot design with 4 replicates. Each individual plot size was 10 x 40 foot (two 14-row passes with the small plot research cereal seeder). Irrigation treatments (3 irrigation levels) were the main plots, and treatments of nitrogen fertilization (4 nitrogen fertilization levels) were randomized within each main plot. The water was applied every 7 days utilizing the subsurface drip irrigation system with flow meters that allow us to precisely measure the amount of applied water. Dripper line was placed at 8 inch depth and spaced 28 inches apart. Three irrigation treatments of 50, 75, and 100 % of measured evapotranspiration were randomly assigned. Irrigation with the subsurface system was scheduled based on the estimated crop water use model by AgriMet. Crop physiological parameters were evaluated throughout the growing season at 4 growth stages: Zadoks scale 14 (four leaves unfolded seedling), 30 (main shoot with four tillers), 45 (flag leaf sheath opening), 59 (head completely emerged), and 80 (late milk and early dough): plant height was measured with a measuring ruler, crop reflectance was measured with SVC HR-768i Field Portable Spectroradiometer and GreenSeeker 505, chlorophyll content was estimated with SPAD, leaf area index was measured with  AccuPAR LP-80, canopy temperature was measured with Infrared Thermometer (IRT); furthermore, soil moisture was measured with ML3 Delta-T soil moisture sensor. Wheat will be harvested at maturity. The by-plot grain samples will be collected and dried in a forced-air oven at 140 °F. Test weight of the dried grain will be determined and sent to a laboratory to be analyzed for protein content. The influence of the nitrogen rates and irrigation treatments on grain yield and quality (test weight and grain protein) will be accessed using statistical procedure ANOVA at the 95% significance level. The correlation analysis will be performed between canopy spectral reflectance, leaf area index, and leaf temperature with grain yield, grain protein, yield loss due to nitrogen, and yield loss due to water stress. The relationship will be used to develop a model that will enable us to predict yield and grain protein content in varying nitrogen and water environments, and to determine the minimum nitrogen and water required to maintain wheat grain yield and quality. The experiment will be repeated for three growing seasons at two experimental locations. Grower recommendations for nitrogen and irrigation water use will be developed based on this project’s findings.