2012 Annual Report
1a.Objectives (from AD-416):
The goal of this research project is to identify cultural practices and technologies that improve economic viability and environmental sustainability of inland PNW dryland wheat production systems. The specific objectives are fourfold and include:
Objective 1: Develop cropping practices for improving crop water use in dryland production systems and landscapes across PNW agroecological zones. (Pullman all of Obj 1)
Sub-objective 1A: Optimize crop establishment practices and crop water use for improving the performance of winter canola.
Sub-objective 1B: Improve stand establishment methods for spring canola to minimize weed competition and increase crop water use.
Sub-objective 1C: Contrast fall-planted facultative wheat and spring-planted wheat for abilities to suppress weeds and increase yield, profitability, and crop water use.
Sub-objective 1D: Determine effects of Russian thistle on crop water use, and production costs and quality of forage spring triticale.
Objective 2: Evaluate cropping system diversification strategies (forage and biofuels) for increasing agronomic performance of agricultural landscapes across PNW agroecological zones.
Sub-objective 2A: Determine productivity and profitability of integrating alternative forage and biofuel crops into wheat-based production systems. (Pullman)
Sub-objective 2B: Determine production potential of perennial biofuel and forage crops incorporated as riparian buffers in agricultural landscapes. (Pendleton)
Objective 3: Assess how new optical light reflectance spectrometers (advanced technology) can be used to increase cropping system performance in agricultural landscapes. (Pendleton – all of Obj 3)
Sub-objective 3A: Apply information from on-combine yield monitors and optical sensors into site-specific nitrogen (N) application thereby improving grain quality and yield, and N use efficiency of cereal crops.
Sub-objective 3B: Assess the quantity and quality of wheat residue at site-specific field locations across farm fields.
Sub-objective 3C: Measure and map determinants of grain quality value (i.e. test weight, protein concentration, and foreign weed material), and apply this information into grain segregation on a combine harvester.
Objective 4: Synthesize available crop and cropping systems research across PNW agro-ecological zones to assess biophysical production factors influencing cropping system performance and ecosystem services.
Sub-objective 4A: Compile and summarize existing databases of dryland crops and cropping systems to calibrate and corroborate process-oriented models. (Pendleton)
Sub-objective 4B: Utilize existing datasets and process-oriented models to spatially evaluate the suitability of past, present, and future cropping system strategies. (Pullman). Replaces 5356-13210-002-00D (10/08).
NP216 Cross-location project associated with Pullman, WA, 5348-22610-002-00D (Young).
1b.Approach (from AD-416):
Field experiments will assess the production potential of perennial bioenergy and forage crops in lower, middle, and upper slope positions. Biomass will be harvested at each slope position. Soil/air temperature and rainfall will be measured daily. Soil samples will be analyzed for water content and soil organic matter. A water gradient experiment will study the effect of the water-by-N interaction on grain protein and yield of spring wheat. A second experiment will compare economic returns from precision vs. conventional uniform N placement. Precision N placement uses yield and protein values from the water gradient study to compute the total N required for a following crop. Previous year’s plots of the water gradient study will be replanted. N fertilizer will be applied to half of plots based on N factors computed from previous protein/yield measurements (precision N placement), and to remaining plots based on single uniform N rate (uniform N placement). Uniform and precision N placement will be compared in terms of uniformity in grain protein. Dollar returns will be determined using a partial budget analysis of market quotes and production costs. Grain yield and N supply will be computed for each plot and averaged to arrive at N use efficiency for each N placement strategy. The bulk tank of a combine will be divided into two bins. An optical sensor will sense grain protein and control a mechanism that diverts grain into a bin for ordinary grain or one for high quality grain. Site-specific measurements of grain protein and yield will be used to determine the dollar value of grain. Partial budget analysis will be conducted to compare the profitability of wheat production with and without grain segregation. The water gradient study will provide a wide range in values for yield, grain protein, plant height, and straw yield. Linear regression will be used to develop straw yield prediction equations that include terms for yield, protein, and plant height. Models will be evaluated by comparing predictions against actual measurements obtained from fields. On-combine measurements of grain yield, protein, and straw yield will be obtained using a yield monitor, optical grain quality sensor, and crop height sensor. Maps of straw yield will be used with current price quotes to estimate the net value of straw. Dollar returns will be contrasted with contract payments that would be received under conservation programs if straw is retained. Amount of carbon to maintain soil organic C at current levels will be estimated using the C sequestration model CQESTR. From this, the amount of straw that may be removed while maintaining soil quality will be assessed. Long-term studies will be examined to assess their value for calibration and corroboration of various simulation models (CQESTR, C-Farm, CropSyst, and RZWQM2). For RZWQM2, relevant soil, weather, and plant growth parameters will be calibrated from available data that have measured values of phenology, biomass, and leaf area at different stages, and yield. Modeling will extend study results for a more diverse set of weather conditions and soil types across the region.
Progress was made on all three objectives and their subobjectives, all of which fall under National Program 216, Component 1, Agronomic Crop Production Systems; Component 2, Integrated Whole Farm Production Systems; and Component 4, Integrated Technology and Information to Increase Customer Problem Solving Capability. Under Objective 2B, we have completed two years of monitoring perennial biofuel and forage crops for growth and development, and are currently making progress as planned for completion of the third and final year of data collection. Through agreement with collaborators at Oregon State University, we were able to conduct biochemical analysis of plant materials collected from our plots, and a journal manuscript has been submitted for peer review. Under objective 3A, we made significant progress in determining the economic feasibility of spatially variable nitrogen application in dryland wheat production systems. Progress was made toward determining the effects of applied nitrogen and water on grain protein and yield for wheat grown in lower rainfall areas of the Pacific Northwest (PNW). In addition, significant progress was made in molecular technique development and optimization for Pendleton soil. The analyses completed for the first year samples have enhanced our knowledge of the effect of fertilizer use on the microbial N cycle with respect to nitrification and fixation. Under objective 3B, we made significant progress determining the economic feasibility of segregating wheat by protein concentration on a combine harvester during harvest. Progress was made developing web-based software to calculate the best cutoff value to segregate grain into a bin of common quality grain or a bin of high quality grain. Progress was made showing that premiums occur under certain supply and demand conditions that make grain segregation profitable. Under objective 3C, we made significant progress in assessing the accuracy and feasibility of light detection and ranging (LiDAR) measurements of crop height for predicting the straw yield of wheat at site-specific field locations and applying this information into determining where excess straw is available beyond soil conservation needs. For objective 4A, progress was made toward calibrating the process oriented model RZWQM2 for predicting winter wheat yield of conventional tillage and zero tillage systems in the intermediate rainfall zone of the PNW.
Adapting LiDAR to mapping straw yield from a combine harvester. Scientists in Pendleton, Oregon adapted a technology to measure crop height and aboveground biomass of wheat using an inexpensive LiDAR instrument mounted to a combine harvester. Based on field results, LiDAR measurements of crop height can determine straw productivity with about 85% accuracy. Maps of straw yield can be derived from LiDAR when it is coupled to a GPS receiver. Maps of harvestable straw can be computed by subtracting the amount of straw required to maintain soil carbon from a map of total straw. These findings are important in soil conservation programs where accurate information is needed on how much straw is available for commercial use and soil protection.
GPS-guided drill operation captures runoff on steep slopes. Contour farming has long been recommended as a means of retaining water on hill slopes and preventing soil erosion. A novel method was developed and validated by scientists in Pendleton, Oregon to guide a tractor and its seed drill along the elevation contour lines on a hill slope. Results demonstrated that seeding precisely in one pass on the elevation contour of an upper shoulder slope can effectively capture and hold the runoff from a 100 year 24 hour storm event. Using terrain map information and GPS-based autosteering systems, contour seeding promises to improve soil and water conservation in many tillage systems. The method can be implemented using commercially available mapping software and autosteering equipment designed for tractors and drills.
In-line NIRS technology for in-stream measurement of canola seed oil concentration. Natural variation in the seed oil concentration of oilseed crops sent to a crushing plant can impair the recovery of oil from the seed. Scientists in Pendleton, Oregon, demonstrated that the in-line NIRS technology can determine seed oil concentration in a grain stream to within an error of 0.73%. This result is sufficiently promising to suggest that in-line NIRS could be used to evaluate the performance of the extraction process in a crushing plant so that the expeller can be adjusted to maximize oil extraction and minimize residual oil levels in the finished meal. Ability of crushing plants to monitor extraction efficiency would also enhance profitability and help ensure maximum efficiency of the harvested acres of oilseed crops.
Franzen, D., Long, D.S., Sims, A., Lamb, J., Casey, F., Staricka, J., Halvorson, M., Hofman, V. 2011. Evaluation of methods to determine residual soil nitrate zones across the northern Great Plains of the USA. Precision Agriculture. 12:594-606.
Juneja, A., Kumar, D., Williams, J.D., Wysocki, D.J., Murthy, G.S. 2011. Potential for ethanol production from conservation reserve program lands in Oregon. Journal of Renewable and Sustainable Energy. 3(6). Available http://jrse.aip.org/
Long, D.S., McCallum, J.D., Young, F.L., Lenssen, A. 2012. In-stream measurement of canola (Brassica napus L.) seed oil concentration using in-line near infrared reflectance spectroscopy. Journal of Near Infrared Spectroscopy. 20(3):387-395.
Williams, J.D., Long, D.S., Wuest, S.B. 2012. Capture of Plateau Runoff by GPS Guided Seed Drill Operation. Journal of Soil and Water Conservation. 66(6):355-361.
Weerakoon, D.M., Reardon, C.L., Paulitz, T.C., Izzo, A., Mazzola, M. 2012. Long-term suppression of Pythium abappressorium induced by Brassica juncea seed meal amendment is biologically mediated. Soil Biology and Biochemistry. 51:44-52.
Mazzola, M., Reardon, C.L., Brown, J. 2012. Initial Pythium species composition and Brassicaceae seed meal type influence extent of Pythium-induced plant growth suppression in soil. Soil Biology and Biochemistry. 48:20-27.
Williams, J.D., Hartman, H.M., Spencer, L.M., Loiland, J.O. 2011. Plant community development in a dryland CREP in Northeastern Oregon. American Journal of Plant Sciences. 2(6):744-752.