Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-22T17:31:25.192Z Has data issue: false hasContentIssue false
  • English
  • Français

Methods for Optimizing Seed Mortality Experiments

Published online by Cambridge University Press:  20 January 2017

Brian J. Schutte ,
Erin R. Haramoto  and
Adam S. Davis
Brian J. Schutte*
Affiliation:
United States Department of Agriculture–Agricultural Research Service, Global Change and Photosynthesis Research Unit, 1102 S. Goodwin Avenue, Urbana, IL 61801
Erin R. Haramoto
Affiliation:
United States Department of Agriculture–Agricultural Research Service, Global Change and Photosynthesis Research Unit, 1102 S. Goodwin Avenue, Urbana, IL 61801
Adam S. Davis
Affiliation:
United States Department of Agriculture–Agricultural Research Service, Global Change and Photosynthesis Research Unit, 1102 S. Goodwin Avenue, Urbana, IL 61801
*
Corresponding author's E-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Experiments investigating mortality in the soil seedbank are aided by using only seeds that are initially viable and capable of remaining ungerminated (hereafter “persistent seeds”). However, seed mortality experiments often use heterogeneous populations containing persistent, nonviable, and germinable individuals. In this investigation we developed and compared nondestructive tests for isolating persistent seeds of two weed species characterized by physical seed dormancy (dormancy imposed by a water-impermeable seed coat): velvetleaf and ivyleaf morningglory. Individual seeds were weighed, steeped in water (hereafter “steepate”) for 48 h, and then assayed for imbibition. These seeds were then subjected to persistence assays conducted under controlled conditions (60 d in hydrated soil under 25/15 C day/night temperatures, 14-h photoperiod). Persistent seeds were less likely to imbibe and more likely to produce steepates with low electrical conductivity compared with germinable and nonviable seeds. For velvetleaf, persistent seeds were best segregated by comparing changes in steepate conductivity during 4 to 48 h of soaking, with the corresponding classification and regression tree (CART) model making few false discoveries (false discovery rate for persistence; FDRp = 8.6%, n = 93) and many true positive classifications (true positive rate for persistence; TPRp = 100%, n = 85). For ivyleaf morningglory, both a change in steepate conductivity from 4 to 48 h of soaking and imbibition status after soaking accurately separated persistent seeds (accuracy measures of corresponding CART models: FDRp = 5.6%, n = 150; TPRp = 100%, n = 142). Thus, for species with physical seed dormancy, we recommend use of steepate conductivity and imbibition status after soaking for isolation of persistent seeds. These seeds can then be used to optimize experiments on mortality in the soil seedbank. Nondestructive tests for isolating persistent seeds of species characterized by physiological seed dormancy require further research.

Los experimentos que investigan la mortalidad del banco de semillas en el suelo se ayudan utilizando solamente semillas que son inicialmente viables y capaces de permanecer sin germinar (de ahora en adelante “semillas persistentes”); sin embargo, los experimentos de mortalidad de semillas, frecuentemente utilizan poblaciones heterogéneas que contienen individuos persistentes, no viables y germinables. En esta investigación desarrollamos y comparamos pruebas no destructivas para aislar semillas persistentes en dos especies de malezas caracterizadas por latencia física de las semillas (latencia impuesta por una capa impermeable de la semilla): la Abutilon theophrasti Medicus ABUTH y la Ipomea hederacea Jacq. IPOHE. Semillas individuales se pesaron, se remojaron en agua (de ahora en adelante “el líquido de remojo”) por 48 horas y después fueron evaluadas para determinar su imbibición. Estas semillas fueron sometidas después a ensayos de persistencia llevados al cabo bajo condiciones controladas (60 días en suelo hidratado bajo temperaturas de 25/15 C día/noche y 14 h de foto-período). Las semillas persistentes demostraron ser menos susceptibles a absorber agua y más susceptibles a producir líquido de remojo con baja conductividad eléctrica, comparada con semillas germinables y no variables. Para la Abutilon theophrasti Medicus ABUTH, las semillas persistentes se segregaron mejor a través de comparar los cambio en la conductividad del líquido durante un período de 4 a 48 horas de remojo, con la clasificación correspondiente y el modelo de regresión CART, resultando en muy pocos descubrimientos falsos (taza de descubrimiento falso para la persistencia; FDRp = 8.6%, n = 93) y muchas clasificaciones verdaderas positivas (taza de positivos verdaderos para la persistencia; TPRp = 100%, n = 85). Para la Ipomea hederacea Jacq. IPOHE, tanto un cambio en la duración de la conductividad del liquido durante un período de 4 a 48 horas de remojo como un cambio en el nivel de imbibición después del remojo separó con exactitud las semillas persistentes. Las medidas de exactitud de los modelos CART correspondientes fueron: FDRp = 5.6%, n = 150; TPRp = 100%, n = 142. Por lo tanto, para especies con latencia física de la semilla, recomendamos el uso de la conductividad del líquido de remojo y el nivel de imbibición después del remojo para aislar las semillas persistentes. Estas semillas pueden ser utilizadas para optimizar los experimentos sobre la mortalidad en el banco de semillas en el suelo. Las pruebas no destructivas para el aislamiento de semillas persistentes en especies caracterizadas por latencia fisiológica, requieren de mayor investigación.

Keywords

Ivyleaf morningglory, Ipomea hederacea Jacq. IPOHEvelvetleaf, Abutilon theophrasti Medicus ABUTHNondestructive seed testingseed conductivity testweed seedbanksoil seedbank dynamicsphysical seed dormancy
Type
Note
Information
Weed Technology , Volume 24 , Issue 4 , December 2010 , pp. 599 - 606
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.)

References

Literature Cited

Baloch, H. A., DiTommaso, A., and Watson, A. K. 2001. Intrapopulation variation in Abutilon theophrasti seed mass and its relationship to seed germinability. Seed Sci. Res. 11:335–343.Google Scholar
Baskin, C. C. and Baskin, J. M. 1998. Seeds: Ecology, Biogeography, and Evolution of Dormancy, and Germination. San Diego, CA: Academic. 666 p.Google Scholar
Bewley, J. D. and Black, M. 1994. Seeds Physiology of Development and Germination. New York: Plenum. 445 p.Google Scholar
Breiman, L., Friedman, J. H., Olshen, R., and Stone, C. 1984. Classification and Regression Trees. Monterey, CA: Wadsworth. 358 p.Google Scholar
Calero, E., West, S. H., and Hinson, K. 1981. Water absorption of soybean seeds and associated causal factors. Crop Sci. 21:926–933.Google Scholar
Chee-Sanford, J. C., Williams, M. M., Davis, A. S., and Sims, G. K. 2006. Do microorganisms influence seed-bank dynamics? Weed Sci. 54:575–587.CrossRefGoogle Scholar
Davis, A. S., Kathleen, A. I., Hallett, S. G., and Renner, K. A. 2006. Weed seed mortality in soils with contrasting agricultural management histories. Weed Sci. 54:291–297.Google Scholar
De'ath, G. and Fabricius, K. E. 2000. Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81:3178–3192.Google Scholar
Fenner, M. and Thompson, K. 2005. The Ecology of Seeds. Cambridge, UK: Cambridge University Press. 250 p.Google Scholar
Franklin, R. B. and Mills, A. L. 2009. Importance of spatially structured environmental heterogeneity in controlling microbial community composition at small spatial scales in an agricultural field. Soil Biol. Biochem. 41:1833–1840.Google Scholar
Gallandt, E. R., Fuerst, E. P., and Kennedy, A. C. 2004. Effect of tillage, fungicide seed treatment, and soil fumigation on seed bank dynamics of wild oat (Avena fatua). Weed Sci. 52:597–604.CrossRefGoogle Scholar
Gallandt, E. R., Liebman, M., and Huggins, D. R. 1999. Improving soil quality: implications for weed management. J. Crop Prod. 2:95–121.CrossRefGoogle Scholar
Givelberg, A., Horowitz, M., and Poljakoffmayber, A. 1984. Solute leakage from Solanum nigrum L. seeds exposed to high temperatures during imbibition. J. Exp. Bot. 35:1754–1763.CrossRefGoogle Scholar
Hamman, B., Halmajan, H., and Egli, D. B. 2001. Single seed conductivity and seedling emergence in soybean. Seed Sci. Technol. 29:575–586.Google Scholar
Hampton, J. and TeKrony, D. M. 1995. Handbook of Vigour Test Methods. Zurich, Switzerland: ISTA. 117 p.Google Scholar
Hampton, J. G., Johnstone, K. A., and Euaumpon, V. 1992. Bulk conductivity test variables for mungbean, soybean and french bean seed lots. Seed Sci. Technol. 20:677–686.Google Scholar
Hampton, J. G., Lungwangwa, A. L., and Hill, K. A. 1994. The bulk conductivity test for Lotus seed lots. Seed Sci. Technol. 22:177–180.Google Scholar
Hanks, R. S. and Ashcroft, G. L. 1980. Applied Soil Physics: Soil Water and Temperature Applications. New York: Springer-Verlag. 159 p.CrossRefGoogle Scholar
Harrison, S. K., Regnier, E. E., Schmoll, J. T., and Harrison, J. M. 2007. Seed size and burial effects on giant ragweed (Ambrosia trifida) emergence and seed demise. Weed Sci. 55:16–22.Google Scholar
Harrison, S. K., Regnier, E. E., Schmoll, J. T., and Webb, J. E. 2001. Competition and fecundity of giant ragweed in corn. Weed Sci. 49:224–229.Google Scholar
Hoekstra, F. A., Golovina, E. A., Van Aelst, A. C., and Hemminga, M. A. 1999. Imbibitional leakage from anhydrobiotes revisited. Plant Cell Environ. 22:1121–1131.Google Scholar
Jayasuriya, K. M. G. G., Baskin, J. M., Geneve, R. L., and Baskin, C. C. 2009. Sensitivity cycling and mechanism of physical dormancy break in seeds of Ipomoea hederacea (Convolvulaceae). Int. J. Plant Sci. 170:429–443.Google Scholar
Khan, M., Cavers, P. B., Kane, M., and Thompson, K. 1997. Role of the pigmented seed coat of proso millet (Panicum miliaceum L.) in imbibition, germination and seed persistence. Seed Sci. Res. 7:21–25.Google Scholar
Kuo, W. H. J. 1989. Delayed-permeability of soybean seeds: characteristics and screening methodology. Seed Sci. Technol. 17:131–142.Google Scholar
Leggatt, C. W. 1939. Statistical aspects of seed analysis. Bot. Rev. 5:505–529.Google Scholar
McDonald, A. J. and Riha, S. J. 1999. Model of crop: weed competition applied to maize: Abutilon theophrasti interactions. II. Assessing the impact of climate: implications for economic thresholds. Weed Res. 39:371–381.CrossRefGoogle Scholar
McDonald, M. B. 1994. Seed lot potential: viability, vigour, and field performance. Seed Sci. Technol. 22:421–425.Google Scholar
McDonald, M. B. 1999. Seed deterioration: physiology, repair and assessment. Seed Sci. Technol. 27:177–237.Google Scholar
[NCDC] National Climate Data Center 2010. Annual Climatological Summaries, http://www.ncdc.noaa.gov/oa/climate/stationlocator.html. Accessed: April 23, 2010.Google Scholar
Nelson, E. B. 2004. Microbial dynamics and interactions in the spermosphere. Annu. Rev. Phytopathol. 42:271–309.Google Scholar
Nelson, O. E. and Burr, H. S. 1946. Growth correlates with electromotive force in maize seeds. Proc. Natl. Acad. Sci. USA 32:73–84.CrossRefGoogle ScholarPubMed
Neter, J., Kutner, M. H., Nachtsheim, C. J., and Wasserman, W. 1996. Applied Linear Statistical Models. Chicago, IL: Irwin. 1408 p.Google Scholar
Nurse, R. E. and DiTommaso, A. 2005. Corn competition alters the germinability of velvetleaf (Abutilon theophrasti) seeds. Weed Sci. 53:479–488.CrossRefGoogle Scholar
Pandey, D. K. 1992. Conductivity testing of seeds. Pages 273–304. In Linskens, H. F. and Jackson, J. F. eds. Seed Analysis. Berlin: Springer-Verlag.Google Scholar
Peters, J. 2000. Tetrazolium Testing Handbook. Contrib. No. 29 to the Handbook on Seed Testing. Lincoln, NE: Association of Official Seed Analysts. 21 p.Google Scholar
Schafer, D. E. and Chilcote, D. O. 1969. Factors influencing persistence and depletion in buried seed populations, I: a model for analysis of parameters of buried seed persistence and depletion. Crop Sci. 9:417–418.Google Scholar
Schutte, B. J., Davis, A. S., Renner, K. A., and Cardina, J. 2008. Maternal and burial environment effects on seed mortality of velvetleaf (Abutilon theophrasti) and giant foxtail (Setaria faberi). Weed Sci. 56:834–840.Google Scholar
Shephard, H. L. and Naylor, R. E. L. 1996. Effect of the seed coat on water uptake and electrolyte leakage of sorghum (Sorghum bicolor L. Moench) seeds. Ann. Appl. Biol. 129:125–136.CrossRefGoogle Scholar
Steere, W. C., Levengood, W. C., and Bondie, J. M. 1981. An electronic analyzer for evaluating seed germination and vigour. Seed Sci. Technol. 9:567–576.Google Scholar
Thompson, K. 2000. The functional ecology of soil seed banks. Pages 215–236. In Fenner, M. ed. Seeds: The Ecology of Regeneration in Plant Communities. New York: CABI Pub.Google Scholar
Tigabu, M. and Oden, P. C. 2004. Rapid and non-destructive analysis of vigour of Pinus patula seeds using single seed near infrared transmittance spectra and multivariate analysis. Seed Sci. Technol. 32:593–606.Google Scholar
Venables, W. N. and Ripley, B. D. 2002. Modern Applied Statistics with S. 4th ed. New York: Springer. 495 p.CrossRefGoogle Scholar
Wagner, M. and Mitschunas, N. 2008. Fungal effects on seed bank persistence and potential applications in weed biocontrol: a review. Basic Appl. Ecol. 9:191–203.Google Scholar
Westerman, P., Liebman, M., Menalled, F. D., Heggenstaller, A. H., Hartzler, R. G., and Dixon, P. M. 2005. Are many little hammers effective? Velvetleaf (Abutilon theophrasti) population dynamics in two- and four-year crop rotation systems. Weed Sci. 53:382–392.Google Scholar