| Popis: |
In our investigation, we have developed innovative statistical models tailored to predict specific phenological stages of winter oilseed rape (WOSR) cultivation in Luxembourg. Leveraging extensive field observations and meteorological data, our modeling approach accurately forecasts critical growth stages of WOSR, including inflorescence emergence (BBCH 51), initial flowering (BBCH 60), and cessation of flowering (BBCH 69), capitalizing on accumulated heat units. Our findings challenge conventional assumptions surrounding base temperatures, advocating for a specific base temperature of 3 °C for winter oilseed rape emergence, consistent with prior research. Validation via leave-one-out cross-validation yields promising outcomes, with average Root Mean Square Error (RMSE) values below 1, surpassing analogous studies. Particularly noteworthy is our model’s performance in predicting crucial growth stages, notably BBCH 60, pivotal for pest control. Despite advancements, hurdles persist in forecasting late-stage phenological events influenced by leaf senescence and anticipated climate change impacts, likely accelerating WOSR development and introducing new risks. In response, cultivar selection strategies informed by individual development rates and temperature sensitivities emerge as vital mitigation measures. As climate variability intensifies, precision agriculture assumes paramount importance in optimizing resource allocation and ensuring sustainable WOSR cultivation practices. Our study advocates for proactive integration of predictive modeling into adaptive management frameworks, empowering stakeholders to make informed decisions taking climatic dynamics into account. |
