Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-11T01:44:55.275Z Has data issue: false hasContentIssue false

Estimating seed production of three Setaria species in row crops

Published online by Cambridge University Press:  20 January 2017

Nathalie Colbach
Affiliation:
Station d'Agronomie, INRA, BV 1540, 17 rue Sully, 21034 Dijon Cedex, France
George O. Kegode
Affiliation:
Department of Agronomy and Plant Genetics and West Central Research and Outreach Center, University of Minnesota, Morris, MN 56267

Abstract

Seed production of weedy species of Setaria in crops of Zea mays and Glycine max was studied for 2 yr in western Minnesota and eastern South Dakota. Viable seed production was curvilinearly related to panicle length. A 100-mm-long panicle of S. pumila, S. faberi, and S. viridis produced 129, 323, and 851 viable seeds, respectively. Values were consistent across years, crops, and herbicide treatments. Frequency distributions of panicle lengths of all panicles within a population closely followed nonlinear Weibull functions and were stable across years and crops but not species or herbicide treatment. Positive skewness of these distributions decreased, and median panicle size (mm) increased, in the following order: S. viridis (41), S. pumila (52), and S. faberi (78). Postemergence herbicides applied at full label rates increased skewness and reduced median panicle size (to 11 mm) and seed production of S. viridis. Skewness lessens the reliability of using average panicle size as a measure of seed production for the entire population. However, integration of panicle size–frequency and panicle size–fecundity relationships provided estimates of the number of seeds per panicle that were more representative of the population than the statistical average panicle. These estimates were 52, 242, and 246 seeds per panicle for S. pumila, S. viridis, and S. faberi, respectively. Multiplication of these values by panicle densities generated seed production estimates that were similar to actual counts of seeds. Setaria seed production tended to be higher in Z. mays than in G. max only because of higher plant and panicle densities. Early-maturing panicles tended to be larger than those maturing later, but seed viability generally was stable across maturity times.

Type
Research Article
Copyright
Copyright © Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Present address: Department of Plant Sciences, North Dakota State University, Fargo, ND 58101

References

Literature Cited

Anonymous. 1994. STATISTIX. Version 4.1. Analytical Software, Tallahassee, FL.Google Scholar
Biniak, B. M. and Aldrich, R. J. 1986. Reducing velvetleaf (Abutilon theophrasti) and giant foxtail (Setaria faberi) seed production with simulated-roller herbicide applications. Weed Sci. 34:256259.Google Scholar
Box, G.E.P., Hunter, W. G., and Hunter, J. S. 1978. Statistics for experimenters: An introduction to design, data analysis and model building. New York: J. Wiley.Google Scholar
Defelice, M. S., Brown, W. B., Aldrich, R. J., Sims, B. D., Judy, D. T., and Guethle, D. R. 1989. Weed control in soybeans (Glycine max) with reduced rates of postemergence herbicides. Weed Sci. 37:365374.Google Scholar
Fausey, J. C., Kells, J. J., Swinton, S. M., and Renner, K. A. 1997. Giant foxtail (Setaria faberi) interference in nonirrigated corn (Zea mays). Weed Sci. 45:256260.CrossRefGoogle Scholar
Forcella, F., King, R. P., Swinton, S. M., Buhler, D. D., and Gunsolus, J. L. 1996a. Multi-year validation of a decision aid for integrated weed management in row crops. Weed Sci. 44:650661.Google Scholar
Forcella, F., Peterson, D. H., and Barbour, J. C. 1996b. Timing and measurement of weed seed shed in corn. Weed Technol. 10:535543.Google Scholar
Gomez, K. A. and Gomez, A. A. 1984. Statistical procedures for agricultural research. New York: J. Wiley, pp. 372378.Google Scholar
Nadeau, L. B. and Morrison, I. N. 1986. Influence of soil moisture on shoot and root growth of green and yellow foxtail (Setaria viridis and S. lutescens). Weed Sci. 34:225232.Google Scholar
Norris, R. F. 1992a. Relationship between inflorescence size and seed production in barnyardgrass (Echinochloa crus-galli). Weed Sci. 40:7478.Google Scholar
Norris, R. F. 1992b. Case history for weed competition/population ecology: barnyardgrass (Echinochloa crus-galli) in sugar beets (Beta vulgaris). Weed Technol. 6:220227.Google Scholar
Santlemann, P. W., Meade, J. A., and Peters, R. A. 1963. Growth and development of yellow foxtail and giant foxtail. Weeds 11:139142.Google Scholar
[SAS] Statistical Analysis Systems. 1989. SAS/STAT User's Guide. Version 6. Cary, NC: Statistical Analysis Systems Institute.Google Scholar
Schreiber, M. M. 1965. Effect of date of planting and stage of cutting on seed production of giant foxtail. Weeds 13:6062.CrossRefGoogle Scholar
Vanden Born, W. H. 1971. Green foxtail: seed dormancy, germination, and growth. Can. J. Plant Sci. 51:5359.Google Scholar
Wall, D. A. 1993. Comparison of green foxtail (Setaria viridis) and wild oat (Avena fatua) growth, development, and competitiveness under three temperature regimes. Weed Sci. 41:369378.Google Scholar