Finding Contents or People

Integrated Multi-Level Intermodal Network Design Problem: A Sustainable Approach, Based on Competition of Rail and Road Transportation Systems
Biochar, manure and superabsorbent improve the physical quality of saline-sodic soil under greenhouse conditions
Biochar, manure and superabsorbent improve the physical quality of saline-sodic soil under greenhouse conditions
Biochar, manure and superabsorbent improve the physical quality of saline-sodic soil under greenhouse conditions
Essential oil composition and total phenolic content in Cupressus arizonica G. in response to microbial inoculation under water stress conditions
Essential oil composition and total phenolic content in Cupressus arizonica G. in response to microbial inoculation under water stress conditions
Prediction and variability mapping of some physicochemical characteristics of calcareous topsoil in an arid region using Vis-SWNIR and NIR spectroscopy
Prediction and variability mapping of some physicochemical characteristics of calcareous topsoil in an arid region using Vis-SWNIR and NIR spectroscopy
Prediction and variability mapping of some physicochemical characteristics of calcareous topsoil in an arid region using Vis-SWNIR and NIR spectroscopy
Prediction and variability mapping of some physicochemical characteristics of calcareous topsoil in an arid region using Vis-SWNIR and NIR spectroscopy
Soil Fertilization With Medicinal Plant Processing Wastes Suppresses Tuta absoluta (Lepidoptera: Gelechiidae) and Aphis gossypii (Hemiptera: Aphididae) Populations
Effectiveness of the policy for organising self-evacuation by private vehicle transport, as verified in microsimulations
Soil Fertilization With Medicinal Plant Processing Wastes Suppresses <i>Tuta absoluta</i> (Lepidoptera: Gelechiidae) and <i>Aphis gossypii</i> (Hemiptera: Aphididae) Populations
Effects of different sources and spatial resolutions of environmental covariates on predicting soil organic carbon using machine learning in a semi-arid region of Iran
Effects of different sources and spatial resolutions of environmental covariates on predicting soil organic carbon using machine learning in a semi-arid region of Iran