Combining Simple Phenotyping and Photothermal Algorithm for the Prediction of Soybean Phenology: Application to a Range of Common Cultivars Grown in Europe - Schoving, Céline; Stöckle, Claudio Osvaldo; Colombet, Céline; Champolivier, Luc; Debaeke, Philippe; Maury, Pierre (Frontiers in Plant Science, 2020)
Developing new cropping strategies (very early sowing, crop expansion at higher latitudes, double cropping) to improve soybean production in Europe under climate change needs a good prediction of phenology under different temperature and photoperiod conditions. For that purpose, a simple phenology algorithm (SPA) was developed and parameterized for 10 contrasting soybean cultivars (maturity group 000 to II). Two experiments were carried out at INRA Toulouse (France) for parameterization : 1- Phenological monitoring of plants in pots on an outdoor platform with 6 planting dates. 2- Response of seed germination to temperature in controlled conditions. Multi-location field trials including 5 sites, 4 years, 2 sowing dates, and 10 cultivars were used to evaluate the SPA phenology predictions. Average cardinal temperatures (minimum, optimum and maximum) of germination were around 2, 30 and 40°C, respectively with differences for photoperiod sensitivity among cultivars. The parameterized algorithm showed an RMSE of less than 6 days for the prediction of crop cycle duration (i.e. cotyledons stage to physiological maturity) in the field trials including 75 data points. Because SPA can be also parameterized using data from field experiments, it can be useful as a plant selection tool across environments. The algorithm can be readily applied to species other than soybean, and its incorporation into cropping systems models would enhance the assessment of the performance of crop cultivars under climate change scenarios.