Evaluating quinoa crop yield in the face of agro-climatic stressors using the NL-CROP model

Crop models are a key tool for developing adaptation strategies in the agriculture sector. With their evolution over time, they have gradually incorporated new approaches and tools. This document develops a non-linear model for simulating the performance of crops with an innovative approach that includes non-linear functions, thus allowing a more realistic representation of agricultural systems. Focusing on quinoa, we use experimental and field data of zones of the Bolivian Altiplano (high plateau) to evaluate different production outcomes under various climatic and agricultural management scenarios that include multiple agro-climatic stressors. The study reveals that the varieties of quinoa adapted to the local conditions of the study areas have better performance than conventional varieties. This underscores the importance of having material that is genetically adapted for facing the impacts of climate change. Additionally, the results show that the NL-CROPmodel has a satisfactory ability to both reproduce and predict observed quinoa patterns, considering water and thermal stress impacts. This makes the model a key tool for assessing the impact of climate change and also for anticipating the challenges and opportunities that will arise for quinoa in the future, providing valuable assistance in agricultural planning.