Research led by Ana Carcedo, a postdoctoral researcher at the Digital Geospatial Farming Systems Consortium from the Sustainable Intensification and Innovation Lab (SIIL), showcases how limited field data represents a challenge for crop models to provide valuable insights.
This certainly applies to several African regions, where crop models built regional scenarios based on low-resolution field data, leading to unsupported agricultural interventions on smallholders' systems.
Ana's research aims to highlight the value of standardized protocols to collect, store and deploy field data and highlights the critical issue of limited data accessibility of published manuscripts and the unavailability of a data-sharing platform.
She explained that investment in local-level data collection and sharing platforms is critical to guarantee scientific advancement and provide reliable assessments to address complex challenges of food, nutrition, and climate security in Africa.
To assess this investigation, she provided a synthesis analysis of crop modeling efforts in Africa using Agricultural Production Systems Simulator (APSIM) literature as a case study.
The dataset encompassed 71 publications (1474 yield observations) across 24 countries within Africa, including seven significant crops.
The review highlighted that 53% of the gathered publications had no calibration, and 18% needed validation with relevant local-level field data.
Her analysis describes past and current research efforts, discussing limitations, challenges, and future research investments for relevant food security assessments in Africa.
To conclude, the research emphasizes the critical need for future investments in collecting local-level field data and the need to promote the development of standard protocols for data collection, as well as the importance of data sharing and accessibility for future usage. This is a major challenge as data is limited and unavailable in this region.