Taking Note of the Ending Reproductive Stages of Your Soybean Crop
Nebraska’s 2019 soybean crop is nearing the end of its life cycle. Growers have asked how to differentiate these final stages and what impacts the impending frost/freeze may have on soybean.
Determining R7 Stage
R7 is defined as the calendar date when 50% (or all) of the field plants possess one mature pod. In most years, most leaves and pods will have changed color (from green to yellow-green or yellow) by this plant-based R7 date. On an individual pod basis, R7 occurs when the pod wall interior membrane ceases to cling tightly to the seeds and instead stays attached to the pod wall (as shown in Figure 1). This pod membrane status is an observable marker of soybean seed physiological maturity (i.e., no further increase in dry matter thereafter), and is effectively equivalent to black layer formation at the base of a corn kernel, a marker of corn seed physiological maturity (Nielsen, 2019).
Soybean stems typically turn brown shortly after R7 begins, though the stem can remain green due to an abnormally low pod/seed set. For a good review of the causes of green stem syndrome, see the article by Holshouser, 2009. Still, even then, dry matter gain in the seeds will have already ceased within any pod that has reached R7.
The timing of the ending R stages in soybean is governed by planting date (PD) and varietal maturity group (MG), though the date of R7 can be hastened if water stress and high temperatures prevail in August.
- Your varietal MG choice should reflect the actual planting date (early versus late). If you want the crop to avoid being impacted by a fall frost or freeze, the crop must attain the critical stage of R7 (physiological maturity) on or before the calendar date (for your location) of a 10% probability of a 32° F frost.
- On an individual pod basis, physiological maturity occurs when the pod membrane no longer clings tightly to seeds in that pod (equivalent to how black layer indicates physiological maturity in corn).
- You can use the online program SoyWater to project the probable in-field dates of the successive Vn and Rn stages in a soybean field.
Determining the R8 Stage
The final soybean stage is R8, which occurs when 95% of pods have attained maturity and have a variety-dependent color of brown or tan. Note that the date of the R8 stage is used by soybean breeders to establish/assign an MG number (e.g., 3.1) to each newly released variety. This is based on multi-site-year performance trials in which its R8 maturity date is matched with the R8 date of one of the known maturity-check varieties in those trials.
Seed moisture in a soybean pod undergoes a dry-down phase from about 60% at R7 to about 13% at R8. The rate and duration of this dry-down phase are governed by the daily degree of atmospheric evaporative demand, which is a function of solar radiation, humidity, temperature, wind speed, and soil surface moisture. In Iowa State University research studies, the dry-down period averages about 12 days, but can be faster or slower depending on coincident weather (Martinez-Feria et al. 2017).
Impact of Fall Frost/Freeze
Relative to the impact of a fall frost/freeze, the soybean stage of key importance is R7. Seed yield loss from a frost/freeze occurring on/after R7 will be limited to the fraction of pods on an R7 plant that have not yet reached a pod-based stage of R7 (as depicted by the second pod in Figure 1). However, if the frost/freeze occurs at stage R6 (full seed), the yield loss can be substantial, perhaps as much as 45-50%.
Using Crop Models in Soybean Staging
The calendar date of each sequential soybean vegetative (Vn) stage of main stem nodal development, and each successive reproductive (Rn) stage can be projected by most available soybean crop simulation models. The UNL-developed SoySim model (Setiyono et al., 2010) was shown to predict the dates of observed in-field Vn and Rn stages with minimal error (Torrion et al., 2011). Still, like other models, SoySim requires user input of current year and historical multi-year weather data, which is not an easy task for many soybean producers.
Another online program, UNL SoyWater, was developed (with funding from the Nebraska Soybean Board) for easy use by soybean producers to schedule seasonal irrigation events in a timely and water-efficient manner. This program automatically acquires daily (and historical) weather data from an automated weather data station closest to the producer’s field to reliably estimate daily/cumulative soybean water use via an evapotranspiration (ET) calculation. By embedding the SoySim model into the online SoyWater program, the weather data can now be used by SoySim to make Vn and Rn calendar date projections.
Producers can use SoyWater to project/track calendar dates for each Vn and Rn stage in a given soybean field and need only supply these four inputs:
- the field's GPS location,
- planting date,
- variety maturity group (MG), and
- field soil texture – selected from a map.
If you use SoyWater, you already know about its ability to reliably project calendar dates for seasonal progression of Vn and Rn stages in a soybean field. If not, click here to learn the steps needed to register for this free online program. (Approximately 1000+ producers have registered to date.) Then, you too can analyze the ending Rn stage dates for your 2019 fields.
See a related CropWatch article that details how SoyWater was used to project calendar dates of the Vn and Rn stages in 16 combinations of four planting dates with four varieties differing in maturity group (MG) in eastern Nebraska.
Holshouser, D. 2009. Green Stem Syndrome in Soybean. Virginia Polytechnic Institute and State University 2912-1430. https://www.pubs.ext.vt.edu/content/dam/pubs_ext_vt_edu/2912/2912-1430/2912-1430_pdf.pdf
Martinez-Feria, R., S. Archontoulis, and M. Licht. 2017. How Fast do Soybeans Dry Down in the Field? Iowa State University Extension https://crops.extension.iastate.edu/cropnews/2017/09/how-fast-do-soybeans-dry-down-field
Nielsen, R. L. 2019. Grain fill stages in corn. Purdue University. https://www.agry.purdue.edu/ext/corn/news/timeless/grainfill.html
Setiyono, T.D., K.G. Cassman, J.E. Specht, A. Dobermann, A. Weiss, H. Yang, S.P. Conley, A.P. Robinson, P. Pedersen, and J.L. De Bruin. 2010. Simulation of Soybean Growth and Yield in Near-optimal Growth Conditions. Field Crops Research 119: 161-174.
Torrion, J., T.D. Setiyono, K. Cassman, and J. Specht. 2011. Soybean Phenology Simulation in the North-Central United States. Agronomy Journal 103:1661-1667.