BACKGROUND AND AIMS: Models based on thermal-time approaches have been a useful tool for characterizing and predicting seed germination and dormancy release in relation to time and temperature. The aims of the present work were to evaluate the relative accuracy of different thermal-time approaches for the description of germination in Lithospermum arvense and to develop an after-ripening thermal-time model for predicting seed dormancy release. METHODS: Seeds were dry-stored at constant temperatures of 5, 15 or 24 degrees C for up to 210 d. After different storage periods, batches of 50 seeds were incubated at eight constant temperature regimes of 5, 8, 10, 13, 15, 17, 20 or 25 degrees C. Experimentally obtained cumulative-germination curves were analysed using a non-linear regression procedure to obtain optimal population thermal parameters for L. arvense. Changes in these parameters were described as a function of after-ripening thermal-time and storage temperature. KEY RESULTS: The most accurate approach for simulating the thermal-germination response of L. arvense was achieved by assuming a normal distribution of both base and maximum germination temperatures. The results contradict the widely accepted assumption of a single T(b) value for the entire seed population. The after-ripening process was characterized by a progressive increase in the mean maximum germination temperature and a reduction in the thermal-time requirements for germination at sub-optimal temperatures. CONCLUSIONS: The after-ripening thermal-time model developed here gave an acceptable description of the observed field emergence patterns, thus indicating its usefulness as a predictive tool to enhance weed management tactics.
BACKGROUND AND AIMS: Models based on thermal-time approaches have been a useful tool for characterizing and predicting seed germination and dormancy release in relation to time and temperature. The aims of the present work were to evaluate the relative accuracy of different thermal-time approaches for the description of germination in Lithospermum arvense and to develop an after-ripening thermal-time model for predicting seed dormancy release. METHODS: Seeds were dry-stored at constant temperatures of 5, 15 or 24 degrees C for up to 210 d. After different storage periods, batches of 50 seeds were incubated at eight constant temperature regimes of 5, 8, 10, 13, 15, 17, 20 or 25 degrees C. Experimentally obtained cumulative-germination curves were analysed using a non-linear regression procedure to obtain optimal population thermal parameters for L. arvense. Changes in these parameters were described as a function of after-ripening thermal-time and storage temperature. KEY RESULTS: The most accurate approach for simulating the thermal-germination response of L. arvense was achieved by assuming a normal distribution of both base and maximum germination temperatures. The results contradict the widely accepted assumption of a single T(b) value for the entire seed population. The after-ripening process was characterized by a progressive increase in the mean maximum germination temperature and a reduction in the thermal-time requirements for germination at sub-optimal temperatures. CONCLUSIONS: The after-ripening thermal-time model developed here gave an acceptable description of the observed field emergence patterns, thus indicating its usefulness as a predictive tool to enhance weed management tactics.