| dc.creator | Filintas A., Nteskou A., Katsoulidi P., Paraskebioti A., Parasidou M. | 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/engproc2021009037 | |
| dc.identifier.issn | 26734591 | |
| dc.identifier.uri | http://hdl.handle.net/11615/71566 | |
| dc.description.abstract | The effects of two irrigation (IR1: rainfed; IR2: rainfed + supplemental drip irrigation), and two fertilization (Ft1, Ft2) treatments were studied on cotton yield and seed oil by applying a number of new agro-technologies such as: TDR sensors; soil moisture (SM); precision agriculture; remote-sensing NDVI (Sentinel-2 satellite sensor); soil-hydraulic analyses; geostatistical models; SM-rootzone, and modelling 2D GIS mapping. A daily soil-water-crop-atmosphere (SWCA) balance model was developed. The two-way ANOVA statistical analysis results revealed that irrigation (IR2 = best) and fertilization treatments (Ft1 = best) significantly affected yield and oil content. Supplemental irrigation, if applied during critical growth stages, could result in substantial improvement on yield (+234.12%) and oil content (+126.44%). © 2021 by the authors. | en |
| dc.language.iso | en | en |
| dc.source | Engineering Proceedings | en |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137842805&doi=10.3390%2fengproc2021009037&partnerID=40&md5=0beb3f76c6211049e57fcca54ab5624c | |
| dc.subject | MDPI | en |
| dc.title | Rainfed and Supplemental Irrigation Modelling 2D GIS Moisture Rootzone Mapping on Yield and Seed Oil of Cotton (Gossypium hirsutum) Using Precision Agriculture and Remote Sensing † | en |
| dc.type | journalArticle | en |
