Modelling of wheat black point incidence based on meteorological variables in the southern Argentinean Pampas region

Ricardo C. Moschini; M. N. Sisterna; M. A. Carmona

doi:10.1071/AR05275

RESEARCH ARTICLE

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Modelling of wheat black point incidence based on meteorological variables in the southern Argentinean Pampas region

Ricardo C. Moschini ^A ^D , M. N. Sisterna ^B and M. A. Carmona ^C

+ Author Affiliations

- Author Affiliations

^A Instituto de Clima y Agua, CNIA, INTA Castelar, CP: 1712, V. Udaondo, Buenos Aires, Argentina.

^B Facultad de Ciencias Agrarias y Forestales, UNLP, C.I.C. (Prov. Bs. As.), CC 31, CP: 1900, La Plata, Argentina.

^C Fitopatología, Facultad de Agronomía, Universidad de Buenos Aires, Avenida San Martín 4453, CP:1417, Capital Federal, Argentina.

^D Corresponding author. Email: rmoschini@cnia.inta.gov.ar

Australian Journal of Agricultural Research 57(11) 1151-1156 https://doi.org/10.1071/AR05275
Submitted: 21 July 2005 Accepted: 30 June 2006 Published: 27 October 2006

Abstract

Studies were undertaken during 3 growing seasons at several locations on the Argentinean Pampas to investigate the relationships between environmental factors and black point incidence, and to develop predictive models. The strongest associations were observed throughout the critical period starting at 543 degree-days from heading to 861 degree-days (base temperature = 0°C). After a selection process, the best regression equation was: PI % = –6.50 + 0.07 DPrDDTd + 0.23 DRH, where PI is predicted disease incidence, DPrDDTd is a product of days with precipitation and the total degree-day accumulation of mean daily temperatures greater than 17°C (DDTd), and DRH is the total days with relative humidity above 62%. The equation accounted for 87% of the total variance in the disease incidence. Using logistic regression techniques, a model including precipitation frequency and DDTd could satisfactorily explain the probability of occurrence of severe, moderate, and light epidemics.

Additional keywords: Alternaria alternata, Bipolaris sorokiniana, linear regression models.

Acknowledgments

The authors thank Dr Mike J. Gooding, Director of Research, School of Agriculture, Policy and Development, University of Reading, England, for revision of the manuscript and useful advice. We appreciate reviewers’ and editor’s critical comments and constructive suggestions that enhanced this paper.

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Modelling of wheat black point incidence based on meteorological variables in the southern Argentinean Pampas region

Abstract

Acknowledgments

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