| dc.creator | Filintas A. | en |
| dc.date.accessioned | 2023-01-31T07:37:57Z | |
| dc.date.available | 2023-01-31T07:37:57Z | |
| dc.date.issued | 2021 | |
| dc.identifier | 10.3390/engproc2021009036 | |
| dc.identifier.issn | 26734591 | |
| dc.identifier.uri | http://hdl.handle.net/11615/71565 | |
| dc.description.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%). © 2021 by the author. | en |
| dc.language.iso | en | en |
| dc.source | Engineering Proceedings | en |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127335077&doi=10.3390%2fengproc2021009036&partnerID=40&md5=35cc7fdad119ec93cb69152e7c04438f | |
| dc.subject | MDPI | en |
| dc.title | 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 † | en |
| dc.type | journalArticle | en |
