Simulating the influence of vernalization, photoperiod and optimum temperature on wheat developmental rates

Background and Aims

Accurately representing development is essential for applying crop simulations to investigate the effects of climate, genotypes or crop management. Development in wheat (Triticum aestivum, T. durum) is primarily driven by temperature, but affected by vernalization and photoperiod, and is often simulated by reducing thermal-time accumulation using vernalization or photoperiod factors or limiting accumulation when a lower optimum temperature (T_optl) is exceeded. In this study T_optl and methods for representing effects of vernalization and photoperiod on anthesis were examined using a range of planting dates and genotypes.

Methods

An examination was made of T_optl values of 15, 20, 25 and 50 °C, and either the most limiting or the multiplicative value of the vernalization and photoperiod development rate factors for simulating anthesis. Field data were from replicated trials at Ludhiana, Punjab, India with July through to December planting dates and seven cultivars varying in vernalization response.

Key Results

Simulations of anthesis were similar for T_optl values of 20, 25 and 50 °C, but a T_optl of 15 °C resulted in a consistent bias towards predicting anthesis late for early planting dates. Results for T_optl above 15 °C may have occurred because mean temperatures rarely exceeded 20 °C before anthesis for many planting dates. For cultivars having a strong vernalization response, anthesis was more accurately simulated when vernalization and photoperiod factors were multiplied rather than using the most limiting of the two factors.

Conclusions

Setting T_optl to a high value (30 °C) and multiplying the vernalization and photoperiod factors resulted in accurately simulating anthesis for a wide range of planting dates and genotypes. However, for environments where average temperatures exceed 20 °C for much of the pre-anthesis period, a lower T_optl (23 °C) might be appropriate. These results highlight the value of testing a model over a wide range of environments.Key words: Wheat, Triticum aestivum, T. durum, air temperature, thermal time, shoot apex, phenology, growth stages, anthesis, flowering