Plant Protect. Sci., X:X | DOI: 10.17221/175/2024-PPS

Comparison of different modeling approaches to estimate cardinal temperatures for germination of Persicaria lapathifolia, Polygonum aviculare and Solanum nigrumOriginal Paper

Donato Loddo ORCID...1, Stefano Carlesi ORCID...2, Nebojša Nikolić ORCID...3, Roberta Masin3
1 Institute for Sustainable Plant Protection, National Research Council of Italy, Legnaro, Italy
2 Group of Agroecology, Institute of Life Sciences, Scuola Superiore Sant'Anna, Italy
3 Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, Italy

Emergence predictive models can facilitate weed management, but estimating cardinal temperatures for germination of target species is necessary. Germination tests at a range of alternating temperatures from 12.5/2.5 °C to 35/25 °C were conducted to estimate cardinal temperatures of Persicaria lapathifolia (L.) Delarbre, Polygonum aviculare L. and Solanum nigrum L. Two statistical methodologies were tested: the Thermal time-to-event model (TTEM) and the Threshold limit model (TL). Germination of P. aviculare was maximum at low-mid temperatures, where its optimal range probably lies, and decreased at high temperatures. No differences were observed between the base (Tb) values estimated for this species with the two models (TTEM 3.5 °C, TL 4.1 °C), while a significantly higher ceiling (Tc) value was determined with TTEM (TTEM 41.5 °C, TL 33.6 °C). The Germination of P. lapathifolia and S. nigrum increased monotonically with the rise in temperature, indicating that their optimal temperature lies above the highest tested temperature. TTEM could not be applied to these species since it requires data from the supra-optimal thermal range. TL models could instead estimate Tb values (9.4 °C and 15.4 °C for P. lapathifolia and S. nigrum), while the lack of data in the supra-optimal thermal range impeded the estimation of Tc.

Keywords: emergence model; weed management; Thermal Time-to-event model; Threshold Limit model

Received: September 17, 2024; Revised: April 24, 2025; Accepted: April 28, 2025; Prepublished online: July 23, 2025 

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