Zusammenfassung (übersetzt):
Crop models are a key tool to develop adaptation strategies in the agriculture sector. With their evolution over time, crop models have been incorporating new approaches and tools. This paper proposes an innovative non-linear methodology to simulate crop's performance including non-linear functions that approach a more realistic representation of agricultural systems. Focused on the quinoa grain, we use experimental and field data from highland zones of Bolivia to evaluate different production outcomes under various climatic and agricultural management scenarios, including multiple agroclimatic stressors. The study reveals that quinoa varieties adapted to local conditions in the study areas have a better performance than the conventional varieties. This underscores the importance of having genetically adapted material to address the impacts of climate change. Additionally, the results show that the NL-CROP model has a satisfactory ability to both reproduce and predict observed quinoa patterns, considering water and heat stress impacts. This makes the afore mentioned model a valuable tool for assessing the impacts of climate change and anticipating the challenges and opportunities that quinoa production will face in the future, providing valuable assistance for agricultural planning.