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Updated: Sep 12, 2025

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
Published on: February 2, 2019
A spatial dataset on Ecuadorian cropping systems and theoretical crop residue potentials
Christhel Andrade Díaz1,2, Ezequiel Zamora-Ledezma3, Lorie Hamelin1
1Toulouse Biotechnology Institute (TBI), INSA, INRAE UMR792, and CNRS UMR5504, Federal University of Toulouse, 135 Avenue de Rangueil, F-31077 Toulouse, France.
None:
This dataset provides a high-resolution, spatially explicit baseline of Ecuadorian cropping systems and associated pedoclimatic conditions to support long-term modeling of soil organic carbon (SOC) dynamics and biomass resource planning. The dataset is built from national sources, including Ecuadorian agricultural statistics and crop production surveys spanning 2002 - 2019. Ten dominant crops, representing over 90 % of the country's cultivated area, are characterized across 23,021 Agricultural Pedoclimatic Units (APCUs), each defined by unique combinations of soil attributes, climate variables, and crop types. For each APCU, the dataset includes theoretical harvestable crop residue potentials, above- and belowground carbon inputs, and SOC-relevant parameters such as root depth distribution and biomass composition. Residue-to-product ratios (RPR), root-to-shoot biomass ratios (R:S), and biomass-to-carbon conversion coefficients were compiled through a comprehensive literature review and transparently documented. Additionally, the dataset includes monthly projections of average temperature, cumulative precipitation, and estimated evapotranspiration from 2020 to 2070 under the RCP4.5 climate scenario. Temperature and precipitation data were obtained from downscaled daily projections based on an ensemble of global climate models, and evapotranspiration was subsequently calculated using the Thornthwaite method. All variables were spatially assigned to each APCU. This open-access dataset is designed for reuse in soil carbon modeling frameworks, supports the design of biomass mobilization strategies, and informs climate-smart land-use strategies in tropical agricultural systems.
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