Development of a temperature-based seed germination model for silverleaf nightshade (Solanum elaeagnifolium). Issue 4 (19th July 2022) - Kapiluto, Omer; Eizenberg, Hanan; Lati, Ran Nisim
Abstract: Silverleaf nightshade ( Solanum elaeagnifolium Cav.) has become a highly troublesome weed in irrigated summer crops in Israel. Because herbicide-based options to control this weed are limited, the best way to improve weed control is through a study of its biology, particularly its germination dynamics. The main objective of this study was to determine the impact of temperature on the seed germination dynamics of S. elaeagnifolium and to develop a temperature-based (thermal) prediction model for three S. elaeagnifolium populations growing in different ecosystems in Israel. To this end, a laboratory study was undertaken in which the germination proportion of S. elaeagnifolium seeds was monitored under seven temperature regimes: 2/8, 7/13, 12/18, 17/23, 22/28, 27/33, and 32/38 C (night/day). In addition, the impact of alternating temperature regimes between night and day temperatures (of 0, 2, 4, 6, 8, and 10 C), averaged over 20 and 25 C, was determined. It was found that the three populations shared similar germination characteristics and dynamics. An alternation of ≥6 C between night and day temperatures was needed for optimal germination, with no germination taking place under constant temperatures. In all three populations, the minimal requirement for germination was a 12/18 C (night/day) regime, with the final germination proportion lying between 0.25 and 0.36. The highest final germination proportion of ≥0.8 was observed for the 17/23 C regime in all three populations. Modeling the germination rate as a function of temperature allowed us to determine cardinal temperatures for all three populations taken together, with the values being T b = 10.8 C (base temperature), T o = 23.8 C (optimal temperature), and T c = 35.9 C (ceiling temperature). These biological parameters allowed accurate (root mean-square error < 0.06%) prediction of S. elaeagnifolium seed germination over the entire temperature range.