Brief Summary of Minutes of Annual Meeting

The meeting was started at 8:00 a.m. July 16, 2002 with a welcome from UNL representatives, introductions, an update from our Administrative Advisor, and an introduction to the Regional IPM coordinator followed by a discussion about our role in implementing IPM. We then spent nearly 3 hours discussing the status of and future plans on our efforts to accomplish Objective 1  Understand the basis and relative importance of variability in weed/crop competition. After lunch, we spent 2 _ hours discussing our progress and future plans for accomplishing Objective 2  Understand the variability of weed seed in the soil seedbank and its impact on weed/crop competition. We concluded the afternoon with a discussion of where we are with objective 3  Develop DSS modules to incorporate risk into weed management recommendations. On Wednesday morning, July 17, 2002, we concluded unfinished business from the day before and made several administrative decisions.

Objective 1 - Understand the basis and relative importance of variability in weed/crop competition

Protocol studies had been designed to determine the relative competitive indices of selected annual weeds in corn and soybeans (1a) and the effect of relative time of emergence on relative competitive indices (1b) using the biomass of individual weed plants as surrogates for competitiveness. An expanded protocol (1e and 1f) designed to obtain the same information using corn and soybean yield loss was optional. Objectives 1 c and d were not discussed because they are to be completed during years 3-5. Participants are listed in Appendix 3.
Shawn Hock (NE) described results of research into Objective (1a) and (1b). The Nebraska group planted 12 weed species (8 broadleaf and 4 grass) at two soybean row spacings and two locations. Shawn outlined some problems with weed establishment, particularly with Pennsylvania smartweed and late-planted cohorts (due to drought). Frank Forcella (USDA/ARS, MN) noted that smartweed germination could be improved with prolonged cold-water soaking treatments (1 month at 4 deg C). Kathrin Schirmacher (KSU) presented more results from Objective 1a and b. KSU examined four broadleaf (ABUTH, AMAPA, CHEAL, HELAN) and four grass (DIGSA, PANDI, SETFA and SORVU) weeds in corn and soybean. They found the relative competitive indices on a per-individual basis to be 6/6/4/10 for the broadleaves and 0.1/0.2/0.3/3.0 for grasses. The KSU crew also implemented the objective 1e and f protocol and found that the biomass ranks differed from the competitive impact ranks. It was noted that the yields at that site/year were very low. Corey Guza (MI) summarized his work on two studies designed to complete objectives 1a and 1b (study 1) and 1e and 1f (study 2) in corn. Study 1 involved 8 weed species at 4 planting times. In study 2, good populations and uniformity were achieved using 3 species and an untreated area. Approximately 5% of the study was lost due to soil water problems. Some irrigation was used to save plots that might have otherwise perished.
Due to problems with survival of late emerging seedlings, the group discussed the pros and cons of adopting an emergency irrigation treatment. Sharon suggested that we should water fields to their historical averages. There was no firm consensus on the best course of action, though most agreed that irrigation was preferable to losing a treatment altogether. Sharon Clay then presented a re-analysis of the corn-foxtail interference data. She plotted estimates of the i and a parameters of the conventional yield-loss function against number of growing degrees days from emergence to physiological maturity and found a strong negative correlation, indicating that a shorter season brought on by stress resulted in greater yield reduction from weeds. Sharon also presented data on the rate of nitrogen uptake in weedy and weed-free plots. They found the rate (on a per-plant basis as a function of nitrogen levels) to be the same. Therefore, it might be feasible to predict weed size from nitrogen level.

Objective 2  Understand the variability of weed seed in the soil seedbank and its impact on weed/crop competition.

Protocol studies had been designed to assess (2a) the fates of weed seed in the soil seed bank, (2b) weed seed decay due to depth, field site, and cropping system, and (2c) the predictability of seedling emergence from the weed seedbank. Most of our discussions were on objective 2b, as it was the most widely implemented protocol. Objective 2c will be addressed during years 3-5. Participants are listed in Appendix 3.
The discussion of Objective 2b began with Karen Renner (MI) stepping forward as moderator. The group began by providing current updates of the activities of all states. Iowa State (Dekker) had extensive measurements of the fate of giant foxtail seed in soil using a seeded core method of study (Objective 2a). Minnesota (Forcella) examined fall chisel, no-till and moldboard plow systems and the fate of velvetleaf, giant foxtail and lambsquarters at 0, 2 and 10 cm depth. They divide the year into two segments (Oct  April  Oct) and harvested/planted bags at the beginning and end of the cycles. Gregg Johnson (MN) was also investigating objective 2b. Wisconsin (Luschei) examined five species, those used by MN + wild proso millet and yellow foxtail. Depths and evaluation times were the same as MN. WI used three systems: a conventional continuous corn system using pre- and post-emergence herbicides as well as row cultivation, no-till and no-chem system that used cultivation and rotary-hoeing for weed control. Illinois used the three core species plus giant ragweed, common water hemp and woolly cupgrass. They used the same depths and systems as MN but had three different types of evaluation timings (Oct  Oct, Oct April  Oct, Oct  April  July  Oct). Sprague (IL) also mentioned enlisting the cooperation of a soil microbiologist to investigate the microbial community biomass on the surface of the seeds in various treatments. Ohio State (Joel Felix) examined velvetleaf only, but had several different types of treatments that involved moving bags between different soil depths at certain times (the method was designed to mimic the position in the profile that one would likely find weeds after agronomic operations).
Luschei (WI) suggested performing reciprocal transplant studies to eliminate some of the potential biases in selecting seed for study and enhancing the ability to investigate the influence of environmental effects on seed fate. Several states noted interest. An involved discussion began as to what methods were appropriate and economical to assess the final state of seeds after burial treatments. Among the methods used were: tetrazolium test to assess viability, germination tests to assess viability or germinability, forceps or pressure tests to assess viability. Many states noted that predation occurred on bags located on the soil surface, particularly of the large seeded weeds.

Objective 3  Develop DSS modules to incorporate risk into weed management recommendations.

Lynn Bills (UNL) explained the algorithms involved in the decision support tool WeedSoft (WS). WS is a heuristic management tool based on expert opinion and small-scale experimentation. The WS development group uses user-input cropping system data and a prediction of the economic value of weed impact to help select the most economical weed control measures for a given field. The strength of WS was in the yield-loss estimation, which included adjustments for crop health, row spacing and relative emergence time. From its inception, the first objective of NC202 was designed to evaluate whether the yield loss estimates would be stable across the region. Bills noted that the decision support system (DSS) is being locally adapted to many states throughout the region. The current objective 1 is designed to provide data that will be used to adjust these yield loss estimates within the local versions of WeedSoft.
While WS incorporates a rough categorization of potential weed population effects of particular management strategies, the estimates are based on product efficacy data and not studies of realized population growth rates. It was noted that there is a natural fit between the activities of the NC202 group and the WS development team. There was strong support from the entire group for encouraging further collaboration between the WS team and the NC202 group. It was suggested that group activities at the 2002 North Central Weed Science Society meeting (NCWSS) be made to overlap in order to facilitate the communication between these two groups. Members of NC202 also will attend the regional WS meeting in September, 2002.
In order to realize the full potential usefulness of the research being conducted within the NC202 group, it was emphasized that a formal economic analysis incorporating risk into the decision making process is needed. By using stochastic life-cycle models in combination with economic models, the NC202 group will be able to couch forecasts of the weed population consequences of management tactics considered in the WS DSS in probabilistic terms. This would be an important step in the evolution of WS from a heuristic-based expert system to scientific forecasting tools. A formal plan for moving the risk-based bioeconomic analysis forward was drawn up that included delivery of data to one and possibly several agricultural economists and the issuance of a preliminary report at the December NCWSS meeting. John Lindquist and Jack Dekker both said they would contact ag economist Paul Mitchell (TX), who was unable to attend the 2002 meeting due to scheduling. Frank Forcella (USDA-ARS) stated that he would approach Dave Archer (USDA MN) about possibly assisting with the economic and risk analysis. George Kegode (NDSU) also will contact an agricultural economist he worked with at NDSU. Bruce Maxwell (MT) remains interested in NC202 and is becoming more involved in risk analysis research. Participants in the planning stage for this objective are listed in Appendix 3.
Jim Kells passed out a recently completed paper comparing the economic performance of three postemergence weed control decision aids (Swinton et al. 2002).

Action Plans and Administrative Decisions

There was unanimous support for drawing together a regional extension publication of competitive impact and weed seed population dynamics. Such a publication would provide valuable information to both growers and the research community. This publication could potentially impact tens of thousands of acres of corn and soybean production across the region.
Jim Kells raised the question of how many site-years were necessary to answers the questions implicit in objective 1. For corn, there was a current tally of 12 site-years of data and there would be 18 by the end of 2003. For soybean, there were 11 site-years currently with another 8 possible next year. For corn and soybean, there were currently 6 site-years with another 8 possible. Jim suggested that we compile data before the NCWSS meeting in order to answer the question of whether current data was sufficient to meet objectives. Kathryn Schirmacher from KSU agreed to collate data sets for objectives 1a and 1b in corn. She will solicit data from MN, IL, MI and ND. Shawn Hock (NE) will collect the soybean data for objectives 1a and b, obtaining data from MN, SD, ND, and KS. Corey Guza (MI) will work on collecting and processing the corn and soybean data for objective 1e, obtaining data from NE, WI, ND, and KS. Karen Renner (MI) agreed to collate and summarize the objective 2 data. These individuals will also be in charge of data analysis and manuscript preparation.
Ed Luschei agreed to send out a request for multi-species competitive impact data (from the previous five year project), analyze those data, and write up the manuscript.
The 2003 NC202 annual meeting will be held July 15 & 16 (tentative), 2003 in Champaign/Urbana Illinois. Christy Sprague has agreed to serve as local host and vice chair. John

Publications in 2002:

Buhler, D. D. 2002. Challenges and opportunities for integrated weed management. Weed Science 50:273-280.

Cardina, J., C. P. Herms, and D. J. Doohan. 2002. Crop rotation and tillage system effects on weed seedbanks. Weed Science 50:448-460.

Conley, S. P., L. K. Binning, C. M. Boerboom, and D. E. Stoltenberg. 2002. Estimating giant foxtail cohort productivity in soybean based on weed density, leaf area, or volume. Weed Science 50:72-78.

Dekker J., M. Hargrove. 2002. Weedy adaptation in Setaria spp.: V. Effects of gaseous environment on giant foxtail (Setaria faberii R. Hermm.) (Poaceae) seed germination. American Journal of Botany 89(3):410-416.

Dekker, J., J. Lathrop, B. Atchison, and D. Todey. 2001. The weedy Setaria spp. phenotype: How environment and seeds interact from embryogenesis through germination. Proceedings of the Brighton Crop Protection Conference-Weeds 2001:65-74.

Fischer D. W. and R. G. Harvey. 2002. Yellow nutsedge (Cyperus esculentus) and annual weed control in glyphosate-resistant field corn (Zea mays). Weed Technology 16:482-487.

Gower, S. A., M. M. Loux, J. Cardina, and S. K. Harrison. 2002. Effect of planting date, residual herbicide, and postemergence application timing on weed control and grain yield in glyphosate-tolerant corn (Zea mays). Weed Technology 16:488-494.

Hoffman, M. L. and D. D. Buhler. 2002. Utilizing Sorghum as a functional model of crop-weed competition. I. Establishing a competitive hierarchy. Weed Science 50:466-472.

Hoffman, M. L., D. D. Buhler, and E. E. Regnier. 2002. Utilizing Sorghum as a functional model of crop-weed competition. II. Effects of manipulating emergence time or rate. Weed Science 50:473-478.

Johnson, G. A. and T. R. Hoverstad. 2002. Effect of row spacing and herbicide application timing on weed control and grain yield in corn (Zea mays). Weed Technology 16:548-553.

Knezevic, S. Z. S. P. Evans, E. Blankenship, R. C. Van Acker, and J. Lindquist. 2002. Critical period for weed control: The concept and data analysis. Weed Science (in press).

Moechnig, M. J., D. E. Stoltenberg, C. M. Boerboom, and J. M. Norman. 2002. Canopy development, biomass accumulation, and corn-yield loss as influenced by time of weed emergence. Weed Sci. Soc. Am. Abstr. 42:45.

Murphy, C. and J. L. Lindquist. 2002. Growth response of velvetleaf to three post emergence herbicides. Weed Science 50:364-369.

Nelson, K. A., K. A. Renner, and D. Penner. 2002. Yellow nutsedge (Cyperus esculentus) control and tuber yield with glyphosate and glufosinate. Weed Technology 16:360-365.

Nelson, K. A. and K. A. Renner. 2002. Yellow nutsedge (Cyperus esculentus) control and tuber production with glyphosate and ALS-inhibiting herbicides. Weed Technology 16:512-519.

Retrum, J. and F. Forcella. 2002. Giant foxtail (Setaria faberi) seedling assay for resistance to sethoxydim. Weed Technology 16:464-466.

Shrestha, A., S. Z. Knezevic, R. C. Roy, B. R. Ball-Coelho, and C. J. Swanton. 2002. Effect of tillage, cover crop and crop rotation on the composition of weed flora in a sandy soil. Weed Research 42:72.

Swinton, S. M., K. A. Renner and J. J. Kells. 2002. On-Farm Comparison of Three Postemergence Weed Management Decision Aids in Michigan. Weed Technology 16(3): 691-698.

Tharp, B. E. and J. J. Kells. 2002. Residual herbicides used in combination with glyphosate and glufosinate in corn (Zea mays). Weed Technology 16:274-281.

Traore, S., J. L. Lindquist, A. R. Martin, D. A. Mortensen, and S. C. Mason. 2002. Comparative ecophysiology of grain sorghum and Abutilon theophrasti in monoculture and in mixture. Weed Research 42:65-75.

Tranel, D., J. Dekker. 2002. Differential seed germinability in triazine-resistant and -susceptible giant foxtail (Setaria faberii). Asian Journal of Plant Sciences 1(4):334-336.

Van Wychen, L. R., E. C. Luschei, A. J. Bussan, and B. D. Maxwell. 2002. Accuracy and cost effectiveness of GPS-assisted wild oat mapping in spring cereal crops. Weed Science 50:120-129.

Wiles, L. and E. Schweizer. 2002. Spatial dependence of weed seedbanks and strategies for sampling. Weed Science 50:595-606.

Williams, B. J. and R. G. Harvey. 2002. Influence of simulated seed rain on the seed bank of wild-proso millet. Weed Science 50:340-343.

Williams, M. M., D. A. Mortensen, W. J. Waltman, and A. R. Martin. 2002. Spatial inference of herbicide bioavailability using a geographic information system. Weed Technology. 16:603-611.

Wyse-Pester, D. Y., L. J. Wiles, and P. Westra. 2002. Infestation and spatial dependence of weed seedling and mature weed populations in corn. Weed Science 50:54-63.