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Soybeans: Research Projects

Increasing Yields and Profitability for Mid-Atlantic Double-Crop Soybean

World demand for food, particularly soybean meal and oil, is increasing as the population moves to a higher protein diet. A goal of the United Soybean Board (USB) is to increase soybean production by 36% by 2025. This would require a 15+ bushel/acre increase using currently available land area. Increasing the average annual increase in yield from the current 0.4 bushel/acre/year to greater than 1.5 bu will be a challenge; but the goal is possible with new and innovative technologies and cropping systems, and effective educational/technology transfer programs. Environmental concerns could greatly limit soybean production if runoff and leaching goals are not met. Continuous no-till systems and cover crops address runoff and leaching, respectively, of nutrients and other chemicals. However, cover crops can add expense and lower profitability.

Double-crop soybean following small grain addresses world food demand by growing two crops in one year. It also addresses environmental and profitability concerns by growing a harvestable "cover crop" (wheat or barley). Double-crop soybean tends to yield 10 to 30% less than full-season soybean due to late planting, which results in a shorter growing season. Therefore, there is need to increase yield and profitability of double-crop soybean if overall productivity is to improve. Improving yield potential would not only increase total production, but also encourage more soybean acres if such a system is most profitable. Over half of the soybean acres in the Mid-Atlantic States are double-cropped after small grain. There is a need to coordinate ongoing research that is funded by state soybean boards (QSSB) and develop new multi-state research and extension projects that would benefit the entire region.

The goal of this project is to bring universities and qualified state soybean boards (QSSB) together to develop priorities, coordinate activities, and begin implementation of research that develops innovative practices to increase early-season growth early-season growth and yield of double-crop soybean across multiple environments in the Mid-Atlantic USA. Specific objectives to obtain this goal include:

  1. Conduct a 1-day research workshop that brings researchers and QSSB and/or soybean association members to develop research priorities that will sustainably increase production and profitability of double-crop soybean.
  2. Conduct one additional meeting for researchers to plan and coordinate research activities for the 2015 growing season and a researcher tour of experiments during the summer of 2015.
  3. Recruit and hire a Ph.D. candidate to manage a future project to meet our goal.
  4. Begin field research in 2015 to determine the most effective combination of practices to increase double-crop soybean yields. These master set of experiments will be conducted in all participating states, but inputs may be adjusted to reflect local/regional conditions. An omission plot design will be implemented. Other coordinated small-plot experiments will feed data and information into this objective.

Validation of a Weather-based Advisory for Foliar Fungicide Application in Soybean

Investigator(s): Hillary Mehl and David Holshouser

Foliar fungicides have shown to be effective against leaf and stem diseases and can prevent yield loss when disease pressure is high. However, research has shown that a yield response to foliar fungicide application only occur about one-third of the time. It is not profitable or ecologically responsible to apply fungicides when they are not needed. Unfortunately, fungicides need to be applied before disease increases to yield-robbing levels to be effective (fungicides are preventative, not curative). Therefore, only if environmental conditions (primarily humidity and temperature) are right for disease development will effective fungicide applications be made. Furthermore, timing of fungicide sprays are based on soybean development stage (typically R3 or beginning pod). However, development stage does not always coincide with periods conductive to crop infection by foliar pathogens. Poor timing of fungicide sprays may also contribute to the inconsistent yield responses observed in soybean. Disease pressure, favorability of weather conditions to diseases development, fungicide cost and efficacy, and the market value of soybeans need to be considered to optimize yields and maximize profitability of fungicides. Weather-based advisories have been developed for several crops to assess disease risk and assist growers in making disease management decisions. These advisories can reduce total fungicide inputs and increase the efficacy of fungicides when they are applied, thereby increasing overall profitability of soybean. A weather-based soybean disease advisory was developed by Dr. Phipps, Professor Emeritus of Plant Pathology. Hilary Mehl is continuing to develop the model with small plot experiments. Before the model can be released to soybean farmers, it must be validated by on-farm experiments that compare an untreated control with a R3-stage application and an application based on the advisory. With a series of validation experiments that prove the model’s effectiveness, we will have more confidence that the model is ready to be released to the agricultural community.

Goal: 

Validate the fungicide advisory model with on-farm experiments throughout Virginia

Approach:

Fields will be identified throughout Virginia’s soybean growing regions. Three treatments will be tested: 1) Untreated; 2) R3-stage application of a fungicide; and 3) fungicide application based on the weather-based advisory. Plot size will be the swath width of the farmer’s sprayer and length of the field. Plots will be replicated at least three times. Variety choice and other cultural practices will be the choice of the farmer. Fields will be monitored for disease during the growing season and disease incidence will be confirmed by collecting a representative sample from the field and identifying diseases with a microscope. After the fungicide application, plots will be rated for disease every 7-14 days. At maturity, plots will be harvested by the farmer with his combine and weighed with a weigh wagon. Farmers with yield monitors and field mapping capabilities will be sought out to better correlate disease with soybean yield.

Research Update:  

Seven experiments were conducted in 2014. In all locations, the advisory model forecast that conditions were favorable between the R3 and R6 development stages at all locations. As of Dec. 1, six of the experiments had been harvested. A yield response from the fungicide application occurred in four of those six experiments. There was no significant difference in yield between the R3 and weather advisory treatments. In one of the locations where no response occurred, the model did not advise a fungicide until late in the season, nearly 3 weeks after the R3 application; therefore, we suspected that no response would occur.


Agronomic and Economic Comparisons of Small Grain and Soybean Cropping Systems

Investigator(s):  Phillip Browning, David Holshouser, Wade Thomason and Gordon Groover

    Soybean Rows

Little research has been conducted to directly compare full-season soybean with double-cropped wheat-soybean or barley-soybean systems. In a 1972-75 Kentucky study, full-season soybean planted on May 21 yielded only 0.6 bushels per acre more than soybeans planted on June 6 after barley (Herbek and Bitzer, 1997). The Kentucky research indicated that soybean yields after barley do not significantly differ from full-season soybean; however, it was conducted over 30 years ago in one location with older and lower-yielding wheat and soybean varieties. Therefore, research was initiated in the fall of 2008 to agronomically and economically compare the three cropping systems. In total, we have completed 2 years of study for a total of six experiments. Data from these two years of study was somewhat atypical, whereas 2009 was very wet with good yields and 2010 was very dry with poor yields. Another year of research is needed to verify past results. 

Goal and Objectives:

The goal of this research was to develop new information about the agronomic and economic benefits of a barley-soybean double-cropping system using field experiments and updated enterprise budgets. Three cropping systems were compared: full-season soybean, double-cropped wheat-soybean, and double-cropped barley-soybean. The objectives of this study were to:

  1. Determine soybean yield and compare cropping system profitability of the three cropping systems.
  2. Perform a breakeven sensitivity analysis of the three cropping systems.
  3. Determine the effect of planting date and previous winter crop on soybean yield and yield components.

Results to Date:

Data indicate that soybean double-cropped after barley has the potential to yield equal to or greater than full-season soybean or double-cropped soybean following wheat, but its relative yield is very dependent on growing conditions. Profitability comparisons indicated that the barley-soybean cropping system was generally more profitable than the full-season soybean and double-cropped wheat-soybean systems. This conclusion was supported by the breakeven sensitivity analysis, but remains dependent on prices that have been extremely volatile in recent years. In another study, soybean yields declined with planting date at two of four locations in 2009, a year that late-season rainfall enabled later-planted soybean to yield more than expected. In 2010, soybean yield decline was affected by the delay in planting date at both locations. Winter grain did not affect soybean yield in either year. Yield component data reinforced these results and indicated that the lower seed yield in the later planting dates was due primarily to a decrease in the number of pods.

Plan of Work:

Additional replicated research over two contrasting environments in Suffolk will verify that soybean planted after barley yields similarly to full-season soybean (results from 2009 and 2010). We will integrate planting date using the same experimental design used in 2010, allowing us to better separate the contributions of planting date and residue to the reduced yields common with double-cropping. Experimental design is a randomized complete block design in a strip-plot arrangement with four replications. Horizontal plots are barley, wheat, rye, or fallow. ‘Thoroughbred’ barley was planted in October after corn and early November after cotton at 30 to 35 seeds per square foot. Southern States brand SS 520 wheat was planted during the second through fourth week of November. A high-yielding Roundup-Ready/STS soybean variety will be planted beginning in mid-May and continued through mid-July.  Intensive management will be implemented in all crops to achieve and maintain maximum economic yield. Maximum and minimum temperature, rainfall, pan evaporation, and/or radiation will be measured daily via on-farm weather stations. The effects of small grain-induced soil moisture deficits on soybean will be quantified by measuring soil moisture during the growing season.  Soil moisture will be measured at 12, 24, and 36 inches with a series of electrical resistance blocks placed within each of the four replicated blocks. Barley, wheat and soybean plots will be harvested with a small-plot combine equipped with bucket scales and moisture sensor. All data will be subjected to appropriate statistical analysis. With this research, we will have more confidence to recommend barley-soybean or barley-grain sorghum double-cropping systems in Virginia, Mid-Atlantic, and Southeast soybean producers. 

To evaluate production costs and profitability of each cropping system, annual costs will be estimated and based on the operations and inputs used in each experiment. Input costs will be obtained by using an average of a survey of costs from three Virginia distributors. Costs will be fixed across years and locations so as not to bias the results by region or year. Machinery costs will be obtained in a similar manner. The Virginia Cooperative Extension’s Enterprise Budget System Generator (BUDSYS) will be used to calculate net returns, cost of production ($/bu) for each crop, and income above variable costs at differing yields and prices. In addition, a breakeven sensitivity analysis will be performed and a model developed to allow growers to determine the most profitable cropping system using current or 5-year price trends.


Appropriate Seeding Rates for Double-Crop Soybean Planted After Barley

Investigator(s): David Holshouser

Much research has been conducted to evaluate soybean seeding rates in full-season and double-cropped wheat-soybean systems, but little research exists when soybean are planted after barley. Research was conducted in 2009 and 2010 to address this issue. More is needed, especially on different soil types. In addition, the effect of maturity groups on seeding rate needs to be addressed.

Objective:

Conduct seeding rate experiments for maturity group (MG) IV and V soybean on contrasting soil types.

Plan of Work:

Research will be conducted in as many environments and on as many soil types as time allows. At least two locations with different soil types will be utilized at the Tidewater AREC. Experiments will be conducted at OVT locations if those locations are using barley as a winter crop. Or, the wheat may be terminated early with herbicide and soybean will be planted in early June. Either 7.5- or 15-inch row spacing will be used. At each location, two experiments will be conducted, one using a representative maturity group IV variety and the other using a maturity group V variety. Five or six seeding rates ranging from 50,000 to 300,000 seeds per acre will be used. Stand counts will be taken within 3 weeks after emergence to determine percent emergence. Yield and seed size will be determined. Yield will be regressed on seeding rate and plant population density.


Physiology of Soybean Yield and Variety Advancement in Virginia Cropping Systems

Investigator(s): Maria Balota and David Holshouser

    Mature Soybeans

Over the last 30 years, soybean yields in the U.S. and Virginia have increased by an average of 0.5 and 0.35 bushels per acre per year, respectively (Fig. 1). Virginia soybean variety test results show a similar yield improvement over the last 23 years. When these data are separated by cropping system, the yield improvement of full-season soybean approach an average of 0.6 bushels per acre per year but yield improvements in a double-cropped system are flat (Fig. 2a). A more detailed evaluation of these data indicates that most of the full-season yield increase occurred before 1998 and is relatively flat afterwards (Fig. 2b). More concerning is that double-crop yields have gradually declined until the last 2 years, when late-season rains pushed double-crop yields above full-season yields. There is a need to more fully investigate why these yield trends are occurring. Physiological measurements of old and new varieties should improve our knowledge, allow us to better understand yield as related to variety improvement, and better direct breeding programs in search of greater yields.

Objectives:

  1. Determine the magnitude of change in dryland soybean yield with variety improvement in full-season and double-cropped soybean systems
  2. Determine the physiological mechanisms contributing to yield and variety improvement.

Plan of Work:

The experiment will be arranged as a split- plot with the cropping system (full season vs. double crop) as the main plot, and soybean variety as the subplot. Cultural practices for maximum economic yields will be performed. Data collected will include the following: plant population density, emergence rate, maturity date, lodging, yield, and yield components (seed size, number of seeds per pod, number of pods per plant, plant population density, nodes, reproductive nodes). Other physiological measurements to be collected at V12 (12-leaf stage), R2 (full flower stage), R4 (full pod), R6 (full seed), and R7 (physiological maturity) include: height, leaf area index, dry matter, specific leaf area, chlorophyll content, andcanopy temperature depression. Nitrogen content and 13C discrimination will be determined at R7. In addition, data will be collected on leaf gas exchange rates and the maximum quantum yield of the PS II of the photosynthetic apparatus, measured as the ratio of variable (Fv) vs. maximum (Fm) chlorophyll florescence. Physiological measurements will be related to yield and yield components of varieties. Data will be subjected to analysis of variance (ANOVA) and means will be separated using appropriate statistical analysis. If varieties are found to be significantly different, old versus new soybean varieties will be contrasted with appropriate statistical techniques. If a variety by treatment interaction occurs, the interaction term will be tested for validation of difference in response due to genetic improvement.


Foliar Soybean Disease Incidence, Severity, and Interaction with Agronomic Factors

Investigator(s): David Holshouser and Pat Phipps

Over the past 5 years, much research was conducted evaluating foliar disease in soybean. Fungicide trials have been conducted by Drs. Phipps, Rideout, and Stromberg in Virginia. Plus, other states have contributed to this database. In addition, trials evaluating planting date, maturity group, and stage of application have been conducted. At all experimental locations, weather data was collected. Occasionally, significant yield responses were obtained. Still, predicting such a yield response has proven elusive. To date, no model has been developed to better predict when and where fungicide applications need to be made. Considering the amount of data acquired, it may be time to begin developing such a model.

Objective:

Begin efforts to model foliar soybean disease incidence and severity, and it’s interaction with agronomic factors.

Plan of Work:

Fungicide trials will be implemented at the Tidewater AREC evaluating foliar disease and its control. Additional experiments relating to agronomic factors (row spacing, plant population, variety, etc.) will also be instigated.   


Improved Cover Crop Systems for Virginia

Investigator(s): Wade Thomason and David Holshouser

Winter cover crops have the potential to reduce the impact of agricultural production on the surrounding ecosystem, including the Chesapeake Bay. Cover crops are one of the main tools that will be relied upon in the coming years to help meet water quality goals and acreage will need to expand by over 100,000 acres of cover crop annually to help meet the agreed upon goals. However, the incrementally “easiest” acres, those that lend themselves to cover cropping, are likely already enrolled in the program. Thus, a dramatic increase in acreage is going to require adaptation and innovation of the current cover crop systems so that they offer greater flexibility and greater appeal. 

Goal and Objectives:

Our overall long-term goals are to increase acres of winter cover crops and to achieve sustainable conservation through cover crops. Sustainable conservation means that while credits and subsidies will likely be necessary to facilitate adoption of the practice, it will ultimately be valuable enough to the farmer to continue with no or greatly reduced subsidy. 

  1. Evaluate potential cover crop species that are most adaptable to interseeding into soybean cash crops
  2. Evaluate the time of cover crop interseeding with and without soybean defoliation on the success of interseeding
  3. Evaluate various soil and/or residue management techniques to increase germination and stand of intereseeded cover crops.
  4. Evaluate soybean planting date and maturity group and cover crop seeding method on establishment and growth of cover crops.
  5. Evaluate soybean variety response to rye and oat cover crop planting date.

Plan of Work

Objective 1:

Cover crop species interseeding trials will be conducted at three diverse locations in Virginia. When soybeans reach approximately 25% leaf drop (R6.75 growth stage), rye, barley, spring oats, rye + hairy vetch, rye + tillage radish, or spring oats + tillage radish will be broadcast into the bean canopy. In early winter percent ground cover will be estimated for all species. Experiments will use a randomized complete block design with four replications. Aboveground biomass will be determined from a 0.5 m-2 area. Digital photographs will be taken from each treatment at this time for inclusion in presentations and fact sheets as well as analysis via VegMeasurement software. Total C and N determined by dry combustion. Nitrogen uptake will be determined as the product of dry matter yield and tissue N concentration. Similarly, all aboveground biomass will be hand clipped from a 0.5 m-2 area in each treatment just prior to killing the cover crop. Cover crop dry matter will be determined as well as total C and N. To evaluate species growth rate response to temperature, each entry tested in the previous studies, will also be germinated under controlled environmental conditions in growth chambers on the Virginia Tech campus. Phenological development will be recorded and a “growth curve” developed for each species. This will allow fall and winter growth to be estimated throughout the Commonwealth in response to long-term average temperatures. Recommended planting date ranges can then be developed by species and the most effected species for a cropping system can be targeted based on growth and development.

Objective 2:

At the R6.5 growth stage (full seed; 10 days after R6; 80% of yield made) and R7 (physiological maturity; approximately 2/3 of leaves have fallen; 100% of yield made) of soybeans, rye at a rate of 1.5 bu/ac will be broadcast into the crop canopy. One treatment will be sprayed with paraquat, while one will remain untreated and leaves will senesce naturally. The study will be conducted in a randomized complete block design, with the six treatments listed above and four replications in plots of approximately 400 sq. ft. each.  In early winter, percent ground cover will be estimated for all treatments. Similar to the methods in objective 1, we will measure ground cover, biomass, and take digital photos from each demonstration area. Total C and N will be determined from these samples and uptake calculated.

Objective 3: 

It is apparent that to expand cover cropping systems to greater acreages, alternative seeding practices, such as interseeding into standing soybeans, must be refined and recommendations to improve success be developed. Since most of these late-maturing acres will be soybeans planted double-crop behind small grains, how we manage the small grain stubble could influence the success of this interseeded cover crop. To that end, after small grain harvest and before (or just after) soybean planting, four straw management treatments will be imposed, then soybean planted on the entire area. The four treatments will be: 1) stubble left standing; 2) stubble removed as if baled for hay; 3) stubble rolled down with a cultipacker; and 4) stubble incorporated. At the R7 growth stage of soybeans, rye at a rate of 1.5 bu/ac will be broadcast into the crop canopy. In early winter percent ground cover will be estimated from all plots. Aboveground biomass will be hand clipped from a 0.5 m-2 area in each comparative demonstration at this time and crop samples will be dried to determine dry matter yield. Digital photographs will be taken from each treatment at this time as well. 

Objective 4:  

A MG III, IV, or V soybean will be planted in April, May, and June of 2011. When soybean reaches the R6.5 to R7 stages, the cover crop will be aerially seeded to half of the plots. After harvest, the cover crop will be drilled into the other half of the plot. The experimental design is a split strip-plot with maturity group as main plots and planting date and cover crop seeding method as vertical and horizontal plots within the main plot. Similar methods employed in the previous objectives will be used for evaluating cover crops.

Objective 5:

Rye and oat cover crops will be planted in the fall of 2011 in a randomized complete block design, which will also include a fallow treatment at three different planting dates. In the spring of 2012, cover crops will be killed with herbicide at two or three different planting dates. Biomass will be harvested and weighed from a subsample in each plot. Nutrient utilization/recycling will be calculated based on the biomass data. Several representative soybean varieties will be no-till planted in 7.5- or 15-inch rows. Stand counts, growth measurements, and yield will be taken throughout the season to evaluate the effect of the covers on soybean. Soybean yield will be determined and data will be analyzed with appropriate statistical techniques.

Overall, we will develop a greater understanding of the techniques that increase success of interseeding cover crops into standing soybeans and develop recommendations for this practice. We will also better determine the most appropriate cover crop to use before full-season soybean. Field days will be planned at two or more demonstration sites annually.


Vegetative Growth Response and Yield with Starter Fertilizer and Bradyrhizobia japonicum Inoculation in Double-Cropped Soybean

Investigator(s): Kevin Dillon and David Holshouser

Few attempts have been made to increase early-season growth in late-planted soybean. Soybean depends on a symbiotic relationship with the soil bacteria Bradyrhizobia japonica to provide for its nitrogen (N) needs. Still, several studies have found an increase and dry matter and yield with N applications (Al-Ithawi et al., 1980; Starling et al., 1998; Touchton and Rickerl, 1986; Wood et al., 1993). Others found no or negative responses (Peterson and Varvel, 1989; Welch et al., 1973). Taylor et al. (2005) discovered that 60 to 70 kg ha-1 of N broadcast immediately after planting maximized yield and R1 (beginning flower) dry matter accumulation in late-planted (but not double-cropped) soybean. Nitrogen application did reduce nodule number and mass; therefore care must be taken to not harm this important N-fixing mechanism. With the exception of Taylor et al. (2005), none of the referenced studies were conducted in late-planted studies, and none were conducted soybean planted after a small grain. Furthermore, little research has been conducted that investigated the effect of inoculating seed with Bradyrhizobia japonica bacteria in double-cropped soybean.

Objective:  

Evaluate vegetative growth response and yield with starter fertilizer and Bradyrhizobia japonicum inoculation in double-cropped soybean.

Plan of Work:

Field experiments will be conducted at diverse locations representing contrasting Coastal Plain and Piedmont soil types for three growing seasons. Experimental design will be a randomized complete block in a split-plot arrangement with four replications. Main plots will be a factorial combination of two planting dates (May and late-June) and wheat crop (with and without). Subplots will consist of a factorial arrangement of seed inoculated with and without Bradyrhizobia japonicum and five N rates of 0, 25, 50, 75, and 100 kg N ha-1. Nitrogen will be applied at planting either by dribbling the solution 5 to 10 cm away from the planted row of soybean on the surface or injecting the solution 5 to 7 cm below the soil surface and 5 to 10 cm away from the row. Immediately before planting, soil samples will be collected in each replication of the main plots to determine nitrate N (NO3) concentrations. At the V4, V8, R2, and R5 development stages, height, LAI, and dry matter measurements and tissue samples will be collected. Tissue samples will be analyzed for available nutrients with N being of particular interest. Also at the above soybean development stages, root samples will be taken with an 8-cm diameter core barrel to a depth of 20 cm.  Root samples will be washed and nodule number and dry weight determined. At maturity, seed yield (adjusted to 13% moisture), protein and oil content (dry matter basis), seed weight (g 100 seed-1), and seed quality (visually rated on scale of 1 = good quality to 5 = poor quality) will be determined. Data will be subjected to analysis of variance. To investigate the nature of yield and other measurements on N rate, standard orthogonal polynomial coefficients will be used to test for linear, quadratic, and cubic trends.


Disease Incidence, Yield, and Fungicide Effects on Double-Cropped Soybean Varieties

Investigator(s): Kevin Dillon and David Holshouser 

Documented yield loss caused by foliar pathogens in soybean is rare. However, application of fungicide to soybean has increased yields in some cases, but results have been mixed. Some studies have shown yield increases, but others reported no response. Some researchers have suggested a possible yield benefit due to a physiological effect of the fungicide on plants. Such physiological effects include increased chlorophyll content, leaf greenness, and photosynthetic rates, better water use efficiency, and delayed senescence. Little information is available documenting yield advantages of fungicides for double-cropped soybean, although soybean in this cropping system matures later in the year when disease incidence is usually greater. Furthermore, the effect of disease prevention has not been adequately separated from potential physiological effects.

Objective:

Evaluate the effect of fungicide application on disease incidence and yield of double-cropped soybean varieties.

Plan of Work:

Experiments will be conducted over a period of 3 years at several locations through Virginia on double-cropped soybean. Experimental design will be a randomized complete block with 4 replications. To facilitate planting multiple cultivars and insure more uniform fungicide application, plots will be arranged as a strip-plot. Vertical plots will be cultivars with varying maturities and disease resistance. Horizontal plots will be an untreated control and fungicide treatments at the R3 (beginning pod), R5 (beginning seed), or R3 + R5 soybean development stages. Pyraclostrobin will be the fungicide used and applied at a rate of 113 g ha-1 with 0.125% (vol./vol.) non-ionic surfactant. Beginning at full flower (R2 stage), bi-weekly measurements of leaf area index (LAI), normalized difference vegetation index (NDVI), will be measured and leaf chlorophyll will be monitored with a chlorophyll meter. Disease incidence will also be assessed for each plot at these times. Common diseases may include but not be limited to septoria brown spot (Septoria glycines), cercospora leaf spot (Cercospora kikuchii), and frogeye leaf spot (Cercospora sojina). Beginning at the mid-R6 stage (full-seed), percent defoliation will be visually rated every week until full maturity (R8 stage). Seed yield, seed moisture, plant height, and lodging will be measured at harvest. Data will be subjected to analysis of variance Mean comparisons will be made using Fisher’s protected LSD test (P ≤ 0.05).