Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-10T09:33:21.510Z Has data issue: false hasContentIssue false
  • English
  • Français

Characterization and Modeling of Itchgrass (Rottboellia cochinchinensis) Biphasic Seedling Emergence Patterns in the Tropics

Published online by Cambridge University Press:  20 January 2017

Ramon G. Leon ,
Jordi Izquierdo  and
José Luis González-Andújar∗
Ramon G. Leon*
Affiliation:
West Florida Research and Education Center, University of Florida, Jay, FL 32565
Jordi Izquierdo
Affiliation:
Departament of Enginyeria Agroalimentaria i Biotecnologia, Universitat Politecnica de Catalunya, Castelldefels, Spain
José Luis González-Andújar∗
Affiliation:
Instituto de Agricultura Sostenible, CSIC, Cordoba, Spain
*
Corresponding author's E-mail: rglg@ufl.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Itchgrass is an aggressive weed species in tropical agroecosystems. Because of phytosanitary restrictions to exports, pineapple producers must use a zero tolerance level for this species. An understanding of itchgrass seedling emergence would help producers to better time POST control. The objective of the present study was to characterize itchgrass seedling emergence patterns and develop a predictive model. Multiple field experiments were conducted in four agricultural fields in Costa Rica between 2010 and 2011 for a total of 9 site-years. Itchgrass consistently showed a biphasic emergence pattern, with a first emergence phase that was faster and more consistent across site-years than the second one. Weibull + logistic models based on chronological time (R2adj = 0.92) and thermal time with Tbase = 20 C (R2adj = 0.92) provided the best fit for the combined emergence data for two experimental locations in 2010. Both models predicted itchgrass seedling emergence adequately for most site-years, but the thermal-time model was more accurate (R2adj = 0.64 to 0.86) than the chronological model (R2adj = 0.31 to 0.74), especially when temperatures were high. Both models showed high accuracy in the first emergence phase but tended to underestimate emergence rate during the second phase. The models predicted 50% emergence at 14 d or 80 growing degree days and the stabilization of the first emergence phase at approximately 25 d or 200 growing degree days. Thus, these models can be used to properly time itchgrass POST control. More research is needed to understand the regulatory mechanisms responsible for the variability of the second emergence phase.

Keywords

Itchgrass, Rottboellia cochinchinensis (Lour.) W.D. Claytonpineapple, Ananas comosus (L.) Merr.Controldormancygerminationgrowing degree daysintegrated managementseed bankthermal-timetillage
Type
Weed Biology and Ecology
Information
Weed Science , Volume 63 , Issue 3 , September 2015 , pp. 623 - 630
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

Baskin, CC, Baskin, JM (2001) Seeds: Ecology, Biogeography, and Evolution of Dormancy and Germination. San Diego Academic Press. 666 p.Google Scholar
Bolfrey-Arku, GEK, Chauhan, BS, Johnson, DE (2011) Seed germination ecology of itchgrass (Rottboellia cochinchinensis). Weed Sci. 59:182–187.Google Scholar
Bradford, KJ (2002) Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Sci. 50:248–260.Google Scholar
Bridgemohan, P, Brathwaite, R (1989) Weed management strategies for the control of Rottboellia cochinchinensis in maize in Trinidad. Weed Res. 29:433–440.Google Scholar
Bridgemohan, P, Brathwaite, R, MacDavid, C (1991) Seed survival and patterns of seedling emergence studies of Rottboellia cochinchinensis (Lour.) W. D. Clayton in cultivated soils. Weed Res. 31:265–272.Google Scholar
Chauhan, BS, Johnson, DE (2009) Influence of tillage systems on weed seedling emergence pattern in rainfed rice. Soil Till Res. 106:15–21.Google Scholar
Colbach, N, Dürr, C, Roger-Estrade, J, Caneill, J (2005) How to model the effects of farming practices on weed emergence. Weed Res. 45:2–17.Google Scholar
Dorado, J, Sousa, E, Calha, IM, González-Andújar, JL, Fernández-Quintanilla, C (2009) Predicting weed emergence in maize crops under two contrasting climatic conditions. Weed Res. 49:251–260.Google Scholar
Forcella, F, Benech-Arnold, RL, Sanchez, R, Ghersa, C (2000) Modeling seedling emergence. Field Crop Res. 67:123–139.Google Scholar
Griffin, DT (1991) Itchgrass (Rottboellia cochinchinensis) control options in soybean (Glycine max). Weed Technol. 5:426–429.Google Scholar
Grundy, AC (2003) Predicting weed emergence: a review of approaches and future challenges. Weed Res. 43:1–11.Google Scholar
Hall, DW, Patterson, DT (1992) Itchgrass—stop the trains? Weed Technol. 6:239–241.Google Scholar
Hartnett, DC, Hartnett, BB, Bazzaz, FA (1987) Persistence of Ambrosia trifida populations in old fields and responses to successional changes. Am J Bot. 74:1239–1248.Google Scholar
Legates, DR, McCabe, GJ Jr. (1999) Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resour Res. 35:233–241.Google Scholar
Lencse, RJ, Griffin, JL (1991) Itchgrass (Rottboellia cochinchinensis) interference in sugarcane (Saccharum sp.). Weed Technol. 5:396–399.Google Scholar
Leon, R, Aguero, R (2001) Efecto de la profundidad del suelo sobre el establecimiento de plantas de Rottboellia cochinchinensis (Lour.) Clayton en el Agroecosistema de la caña de azúcar (Saccharum officinarum L.). Agron Mesoam. 12:65–69.Google Scholar
Leon, RG, Kellon, D (2012) Characterization of ‘MD-2’ pineapple planting density and fertilization using a grower survey. HortTechnology. 22:644–650.Google Scholar
Leon, RG, Owen, MDK (2006) Tillage systems and seed dormancy effects on common waterhemp (Amaranthus tuberculatus) seedling emergence. Weed Sci. 54:1037–1044.Google Scholar
Millhollon, RW, Burner, DM (1993) Itchgrass (Rottboellia cochinchinensis) biotypes in world populations. Weed Sci. 41:379–387.Google Scholar
Patterson, DT (1979) The effects of shading on the growth and photosynthetic capacity of itchgrass (Rottboellia exaltata). Weed Sci. 27:549–553.Google Scholar
Schutte, BJ, Regnier, EE, Harrison, SK, Schmoll, JT, Spokas, K, Forcella, F (2008) A hydrothermal seedling emergence model for giant ragweed (Ambrosia trifida). Weed Sci. 26:555–560.Google Scholar
Seber, GAF, Wild, CJ (2003) Nonlinear Regression. Hoboken, NJ Wiley-Interscience.Google Scholar
Thomas, PEL, Allison, JCS (1975) Seed dormancy and germination in Rottboellia exaltata . J Agr Sci. 85:129–134.Google Scholar