LSTM Raw Data for Irrigation Forecasting in Mango (Mangifera indica L.), Chimichagua, Colombia
Published: 7 July 2025| Version 4 | DOI: 10.17632/94hx6tg4gp.4
Contributors:
Jose Javier Zapata, , Description
This dataset contains daily time-series of averaged soil matric potential and calculated reference evapotranspiration from a commercial mango (Mangifera indica L.) plantation in Chimichagua, Cesar, Colombia, for the period of December 21, 2022, to April 10, 2023. Although original sensor data were collected at 15-minute intervals, the provided dataset consists of daily values processed for validating predictive models based on LSTM neural networks for efficient irrigation management. The file includes both field-derived observed values and LSTM model predictions, enabling applications in precision agriculture, water resource management, and agricultural sustainability in tropical climates.
Files
Institutions
- Universidad Cooperativa de Colombia Campus Santa Marta Biblioteca Juan Luciano Olivella Jacquin
Categories
Precision Agriculture, Monitoring in Agriculture
Funders
- Ministerio de Ciencia, Tecnología e InnovaciónColombiaGrant ID: Minciencias No. 917 , Minciencias No. 934