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Incorporating environmental factors to describe wild radish (Raphanus raphanistrum) seedling emergence and plant phenology

Published online by Cambridge University Press:  26 August 2020

Theresa Reinhardt Piskackova ,
S. Chris Reberg-Horton ,
Robert J. Richardson ,
Katie M. Jennings  and
Ramon G. Leon Open the ORCID record for Ramon G. Leon [Opens in a new window]
Theresa Reinhardt Piskackova
Affiliation:
Graduate Research Assistant, Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, USA
S. Chris Reberg-Horton
Affiliation:
Professor, Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, USA
Robert J. Richardson
Affiliation:
Professor, Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, USA
Katie M. Jennings
Affiliation:
Associate Professor, Department of Horticulture Science, North Carolina State University, Raleigh, NC, USA
Ramon G. Leon*
Affiliation:
Associate Professor, Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, USA
*
Author for correspondence: Ramon G. Leon, Department of Crop and Soil Sciences, North Carolina State University, 4402C Williams Hall, Raleigh, NC27695. Email: [email protected]
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Abstract

Wild radish (Raphanus raphanistrum L.) is a weed found globally in agricultural systems. The facultative winter annual nature of this plant and high genetic variability makes modeling its growth and phenology difficult. In the present study, R. raphanistrum natural seedbanks exhibited a biphasic pattern of emergence, with emergence peaks occurring in both fall and spring. Traditional sigmoidal models were inadequate to fit this pattern, regardless of the predictive environmental variable, and a corresponding biphasic model (sigmoidal + Weibull) was used to describe emergence based on the best parameters. Each best-fit chronological, thermal, and hydrothermal model accounted for at least 85% of the variation of the validation data. Observations on phenology progression from four cohorts were used to create a common model that described all cohorts adequately. Different phenological stages were described using chronological, thermal, hydrothermal, daylength-dependent thermal time, and daylength-dependent hydrothermal time. Integrating daylength and temperature into the models was important for predicting reproductive stages of R. raphanistrum.

Keywords

Hydrothermal timeintegrated weed managementpredictive modelsthermal timeweed growth
Type
Research Article
Information
Weed Science , Volume 68 , Issue 6 , November 2020 , pp. 627 - 638
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the Weed Science Society of America

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Footnotes

Associate Editor: Vipan Kumar, Kansas State University

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