Location: Columbia Plateau Conservation Research Center
2024 Annual Report
Objectives
Objective 1: Quantify impact of intercropped legume cover crops with winter wheat to increase soil carbon and reduce herbicide and synthetic nitrogen (N) fertilizer inputs.
Sub-objective 1.A: Identify the best performing legume cover crops for intercropping with winter wheat that reduces herbicide and synthetic N while improving precipitation use efficiency in intermediate rainfall zones.
Subobjective 1.B: Examine whether legume cover crop intercropped with winter wheat can increase soil organic carbon (SOC), reduce herbicide and synthetic N fertilizer inputs, and reduce CO2 and CH4 emissions.
Objective 2: Measure deep root-zone water dynamics in dryland cropping systems to optimize water storage with tillage, crop residue, cover crop, and weed management.
Objective 3: Examine the use of biostimulants and biochar (such as thermal carbonized manure) as amendments in dryland wheat production systems in order to improve soil and plant health, profitability, and resilience to extreme weather and climate change.
Sub-objective 3.A: Establish whether the addition of biostimulants to soils can enhance plant growth and soil properties to reduce drought stress under semi-arid dryland wheat production conditions.
Sub-objective 3.B: Determine whether the addition of thermal carbonized manure to soils can increase soil pH in the N fertilizer application zone and enhance plant nutrient uptake under semiarid dryland wheat production systems.
Approach
1.A. Establish intercropped wheat with 4-legumes. Determine grain yields and wheat, legume, and weed biomasses. Apply herbicides while control subplots are covered to count weeds per species. Collect soil samples at the start of the experiment and after the 4th growing season. Determine total, organic and inorganic C, and N; and extractable P, NO3-N, and NH4-N. Collect soil samples for in-season N fertilization and determine dissolved and labile C and N at the time of N fertilization and at harvest. Monitor soil temperature and water. Collect CO2, N2O, and CH4 samples for two years. Perform life cycle analysis (LCA) from greenhouse gas (GHG) emissions from (1) diesel combustion at each stage of crop production, delivery of seed, fertilizers, pesticides, and (2) direct field emission of GHG.
1.B. Measurements are made in 1) wheat-fallow under reduced tillage, 2) no-till annual winter wheat, and 3) no-till wheat–wheat–sorghum/sudangrass. Half of the plots are planted and managed using herbicide. The other plots are intercropped with a legume. Monitor solar radiation with Albedometers. Collect soil samples and determine total and labile C and N as in 1.A. Soil temperature, water and GHG will be monitored, and the LCA will be performed as in 1.A.
2. Install soil water sensors below tillage depth in controlled experiments on post-harvest weed control, alternative crops, cover crops, and in farmer’s fields of selected management practices. Install sensors in 5-cm boreholes to monitor the root zone and below the root zone to detect upward and downward water movement. A minimum of 24 profiles under commercial farm practices in different locations are monitored for the soil and yield response to precipitation events, weed growth, and cropping patterns. Soil water storage, water extraction by the crop, and yield are principal measurements. The data is posted online in real-time.
3.A. Plots of no-till continuous wheat-wheat with 3-N fertilizer rates (0, 50, 100 kg N/ha) will be used. Apply biostimulants to 4 subplots within the N main plots at a rate of 3.7 L/ha at the 4th leaf growth stage. Grain, biomass yields, and harvest index are determined. Shoots and roots are sampled at V6 & maturity and stored (- 80°C) until analyzed. The samples are extracted and analyzed for up to 18 endogenous plant hormones, 8-carbohydrate and 11 phenol monomers. Carbohydrate monomers are hydrolyzed by H2SO4, separated by anion chromatography, and detected by pulsed amperometry. Phenol monomers are extracted by CuO oxidation and NaOH hydrolysis and detected by GC. Amino acid monomers are extracted, separated by anion chromatography and detected by pulsed amperometry.
3.B. Poultry litter will be pyrolyzed and compared with conifer wood and wheat straw biochars and replicated plots will be treated with each of the 3 biochars and incorporated by rotary tillage. Soil cores will be collected before and after application of the biochar. Total soil N, S, and C, extractable NO3 and NH4, micro- and macronutrients, soil pH, and EC are determined. Winter wheat will be seeded by hand for 3 yrs. Micro- and macronutrients in the wheat grain and straw will be determined at harvest.
Progress Report
This report documents progress for project 2074-11120-005-000D, “Nutrient Cycling and Precipitation Use Efficiency for Increasing Productivity and Resilience in Dryland Agroecosystems,” which started in October 2021.
In support of Sub-objective 1.A, weed infestation was evaluated by counting weed species in ½ x 1 m2 frames in each of the intercropped treatments, and second season wheat and residue yields were determined. Daily weather, soil water, and temperature data collections will continue until the next growing season. This work supports the development of fundamental knowledge of and practices for soil-based management that contribute to greater agricultural productivity, reduced reliance on inputs, resilience to disturbances, and provide ecosystem services.
For Sub-objective 1.B, samples of dissolved and labile carbon and nitrogen in the top 15 cm (approximately 6”) soil were determined and 164 greenhouse gases (carbon dioxide, nitrous oxide, and methane) samples were collected from wheat and wheat-pea intercropped plots and analyzed weekly during the winter wheat growing season (October to July). Monthly collection from August to September will continue, including surface soil temperature and soil moisture measurements. This work contributes to quantifying driving factors in soil carbon cycling, including organic matter dynamics, carbon sequestration, and carbon dioxide, nitrous oxide, and methane emissions.
In support of Objective 2, soil water samples have been collected in a winter pea phenology study to compare water use by winter pea versus winter wheat, as well as comparing several new winter pea varieties. The cover crop trial has now been established and periodic soil samples are being used to measure water use by the different cover crops compared to summer fallow, and to monitor soil water loss and redistribution after cover crop termination. Installation of gopher-proof cable is under way at the first electronic soil water sensor profile site, and farmer agreements are being prepared to install two new sites. This research contributes to developing cropping systems that promote resilience to climate change.
Under Sub-objective 3.A, crop yields were collected from the 12 plots and biostimulants were applied. Samples (shoots and roots) were taken from the middle four rows of each plot at the V6 during the growing season, and immediately placed in a deep freezer (-80 degrees C) until analyzed. Samples (shoots and roots) were taken from the middle four rows of each plot, leaving two rows on either side as border rows. This research contributes to advancing our understanding of innovative, nontraditional soil amendment research, including biostimulants, to develop cropping systems that enhance agroecosystems and promote resilience to climate change.
In support of Sub-objective 3.B, ARS researchers analyzed soil samples for pH, nutrient, carbon and nitrogen. Wheat and residue yields were determined. This contributes to advancing our understanding of nontraditional soil amendment that improves soil pH and plant nutrient availability which enhance agroecosystems productivity.
Accomplishments
1. Timing of soil organic carbon measurements affects conclusions. Soil organic carbon measurements are necessary for assessing soil health and potential carbon credits in carbon trading schemes. Despite decades of measurement experience, very little research has been invested in exploring the variation in soil carbon estimates over relatively short time frames, for example, weeks or months. ARS scientists in Pendleton, Oregon, collected and analyzed data on soil samples repeated monthly over three years at five sites and 12 farm fields. The results showed that temporal variation was as large as many treatment effects, such as tillage, residue management, or cropping system. To assess soil organic carbon accurately, soil scientists need to develop protocols which recognize and deal with temporal variability.
2. Pea cover-crop increased soil organic carbon and influenced soil prokaryotes. Winter-wheat – fallow rotation is a common practice in the inland Pacific Northwest which reduces soil organic carbon (SOC) and has negative ecological consequences. ARS scientists in Pendleton and Corvallis, Oregon, collected soil samples from Pendleton long-term pea cover crop field experiment with five nitrogen fertilizer rates at two depths for bacterial diversity and function and soil chemical properties characterized. Microbial biomass and enzyme activity were greater in the wheat-pea cover crop compared to wheat-fallow, but fertilization did not influence these properties. Replacing fallow with pea cover crop decreased bacterial diversity and influenced soil properties, which in turn exerted influence on the microbial community, suggesting that above and belowground biodiversity is indirectly coupled in these cropping systems.
3. Evaluation of Rothamsted Carbon (ROTH-C) model for predicting soil organic carbon stocks. Assessing soil organic carbon (SOC) plays a significant role in water retention, nutrient cycling, soil health, sustainable agricultural production, and food security. An ARS researcher in Pendleton, Oregon, along with collaborators at Haramaya University and University of Nebraska, used the Roth-C model and long-term climate, soil, and land management inputs to assess the current and future SOC stocks at the Anjeni watershed. The results indicated that grassland had highest current and projected SOC compared to cultivated land and plantation forest. Furthermore, grassland of gentle slope gradient had higher SOC compared to the middle and high elevation section of the watershed. Overall, the model projected an increase in SOC that could improve water retention, and reduces greenhouse gas emissions, which in turn could enhance agricultural productivity, food security, and sustainable development.
4. Assessment of the Enviornmental Policy Environmental Climate (EPIC) model in simulating soil water, and nitrogen dynamics. A suitable nitrogen (N) application rate (NAR) and ideal planting period could improve rice productivity, soil moisture utilization, and reduce N losses. An ARS researcher in Pendleton, Oregon, along with collaborators at Prince of Songkla University, assessed the performance of the EPIC model to simulate upland rice productivity, soil water, and N dynamics under NAR and planting windows. The NAR and planting windows impacted rice responses, and the model was able to simulate grain yield, aboveground biomass, and harvest index for all planting windows. Evapotranspiration was slightly underestimated for all N application rates at all planting windows. Planting window was the major factor impacting N and water losses as compared to the N application rate. An adjustment in the planting window would be necessary for improved upland rice productivity, enhanced N and soil water utilization to reduce N and soil water losses.
Review Publications
Wuest, S.B. 2023. Soil carbon increase from crop roots and amendments still present twelve years later. Soil Science Society of America Journal. 87(6):1498-1502. https://doi.org/10.1002/saj2.20597.
Geremew, B., Tadesse, T., Bedadi, B., Gollany, H.T., Tesfaye, K., Aschalew, A., Tilaye, A., Abera, W. 2024. Evaluation of RothC model for predicting soil organic carbon stock in north-west Ethiopia. Environmental Challenges. 15. Article 100909. https://doi.org/10.1016/j.envc.2024.100909.
Domnariu, H., Reardon, C.L., Manning, V., Gollany, H.T., Trippe, K.M. 2024. Legume cover cropping and nitrogen fertilization influence soil prokaryotes and increase carbon content in dryland wheat systems. Agriculture, Ecosystems and Environment. 367. Article 108959. https://doi.org/10.1016/j.agee.2024.108959.
Hussain, T., Gollany, H.T., Mulla, D., Ben, Z., Tahir, M., Tahir Ata-Ul-Karim, S., Liu, K., Maqbool, S., Hussain, N., Duangpan, S. 2023. Assessment and application of EPIC in simulating upland rice productivity, soil water, and nitrogen dynamics under different nitrogen applications and planting windows. Agronomy. 13(9). Article 2379. https://doi.org/10.3390/agronomy13092379.
Wuest, S.B., Durfee, N.M. 2024. Temporal variability is a major source of uncertainty in soil carbon measurements. Soil Science Society of America Journal. 88(3):830-845. https://doi.org/10.1002/saj2.20660.
Barroso, J., Wuest, S.B., Oreja, F. 2024. Weed competition below ground: A three-year study. Científica: Revista de Ciências Agrárias. 47(1):292-296. https://doi.org/10.19084/rca.35039.
Oreja, F.H., Genna, N.G., Gonzalez-Andujar, J.L., Wuest, S.B., Barroso, J. 2023. A hydrothermal model to predict Russian thistle (Salsola tragus) seedling emergence in the dryland of the Pacific Northwest (USA). Weed Science. 72(1):108-112. https://doi.org/10.1017/wsc.2023.67.