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Soil Moisture Depletion Modelling Using a TDR Multi-Sensor System, GIS, Soil Analyzes, Precision Agriculture and Remote Sensing on Maize for Improved Irrigation-Fertilization Decisions

Agathos Filintas

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Abstract

The effects of three drip irrigation (IR1: Farmer’s, IR2:Full (100%ETc), IR3:Deficit (80%ETc) irrigation), and two fertilization (Ft1, Ft2) treatments were studied on maize yield and biomass by applying new agro-technologies (TDR—sensors for soil moisture (SM) measurements, Precision Agriculture, Remote Sensing—NDVI (Sentinel-2 satellite sensor), soil-hydraulic analyses and Geostatistical models, SM-rootzone modelling-2D-GIS mapping). A daily soil moisture depletion (SMDp) model was developed. The two-way-ANOVA statistical analysis results revealed that irrigation (IR3 = best) and fertilization treatments (Ft1 = best) significantly affect yield and biomass. Deficit irrigation and proper fertilization based on new agro-technologies for improved management decisions can result in substantial improvement on yield (+116.10%) and biomass (+119.71%) with less net water use (−7.49%) and reduced drainage water losses (−41.02%).

Topics & Concepts

Environmental scienceIrrigationWater contentPrecision agricultureBiomass (ecology)Human fertilizationNormalized Difference Vegetation IndexAgricultural engineeringAgronomyRemote sensingAgricultureHydrology (agriculture)Soil scienceLeaf area indexEngineeringGeographyBiologyGeotechnical engineeringArchaeologySoil Moisture and Remote SensingGreenhouse Technology and Climate ControlSmart Agriculture and AI
Soil Moisture Depletion Modelling Using a TDR Multi-Sensor System, GIS, Soil Analyzes, Precision Agriculture and Remote Sensing on Maize for Improved Irrigation-Fertilization Decisions | Litcius