Eco-Sustainable Innovative Approaches for Water-Soil-Nutrient-Crop Management
An integrated and appropriate management of water, soil, nutrients, and crops is a fundamental aspect of agronomy, and it is essential for sustainable agricultural production. Today, it is of particular importance as resources are shrinking and degraded, while demand for food is increasing due to uncapped population growth. In this context, the agricultural sector requires innovative and eco-sustainable management solutions to optimize the use of resources and preserve ecosystem services. This is crucial for both agricultural production at local and global level and the achievement of the Sustainable Development Goals (SDGs), since the water–soil–nutrient–crop continuum is among the most fragile and most relevant constituents of ecosystems and their functioning. This Special Issue (SI) aims to present the results of the most innovative research on the water–soil–nutrient–crop continuum and best practices, strategies, and advancement for eco-efficient resource use in agriculture. Hence, the SI intends to offer a broad overview of the latest achievements focusing on (i) smart management strategies and tools to promote eco-sustainable crop cultivation under various pedoclimatic conditions, (ii) innovative options for sustainable and integrated water–soil–nutrient–crop management at plot/farm scale, (iii) novel approaches for water–soil–nutrient–crop management, and the (iv) integration of the latest IT technologies with remote/proximal sensing and field data to optimize crop response to specific growing conditions. All types of manuscripts (original research, reviews, short communications) are welcome.
Dr. Rossella Albrizio
Prof. Dr. Anna Maria Stellacci
Dr. Vito Cantore
Prof. Dr. Mladen Todorovic
- water–soil–nutrient–crop continuum
- eco-efficient resource use
- best practices
- sustainable management
- smart agriculture
- remote and proximal sensing
|Journal Name||Impact Factor||CiteScore||Launched Year||First Decision (median)||APC|
|3.949||3.9||2011||18.7 Days||2000 CHF||Submit|
|3.530||4.8||2009||17.8 Days||2200 CHF||Submit|
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Published Papers (13 papers)
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Coupling remote sensing data and AquaCrop model for simulation of winter wheat growth under rainfed and irrigated conditions in a Mediterranean environment
Authors: Marie Therese Abi Saab 1; Razane El Alam 2; Ihab Jomaa 3; Sleiman Skaf 3; Salim Fahed 1; Rossella Albrizio 4; Mladen Todorovic 2
Affiliation: 1 Lebanese Agricultural Research Institute, P.O. Box 90-1965, Fanar, Lebanon 2 CIHEAM – Mediterranean Agronomic Institute of Bari, Via Ceglie 9, 70010, Valenzano (BA), Italy; 3 Lebanese Agricultural Research Institute, P.O. Box 287, Tal Amara, Lebanon;
Abstract: The coupling of remote sensing technology and crop growth models represents a promising approach to support crop yield prediction and irrigation management. In this study, five vegetation indices were derived from the Copernicus-Sentinel 2 satellite to investigate their performance for monitoring winter wheat growth in a Mediterranean environment, in the Bekaa Valley of Lebanon. Among those indices, the fraction of canopy cover was integrated into AquaCrop model to simulate biomass and yield of wheat grown under rainfed conditions and fully irrigated regimes.. The experiment was conducted during three consecutive growing seasons (from 2017 to 2019) characterized by different precipitation patterns. AquaCrop model was calibrated and validated for different water regimes and its performance was tested when coupled with remote sensing canopy cover. The results showed a good fit between measured canopy cover and LAI data, and those derived from Sentinel 2 images. The R2 coefficient was of 0.79 for canopy cover and 0.77 for LAI. Moreover, the regressions were fitted to relate biomass with Sentinel 2 vegetation indices. In descending order of R2, the indices were ranked CC, LAI, fAPAR, NDVI and EVI. Particularly, CC and LAI were highly correlated with biomass. The results of AquaCrop calibration showed that the modeling efficiency values, NSE, were respectively 0.99 for well-watered treatments and 0.95 for rainfed conditions confirming the goodness of fit between measured and simulated values. The validation results confirmed that the simulated yield varied from 2.59 to 5.36 t ha−1, while the measured yield varied from 3.08 to 5.63 t ha−1 for full irrigation and rainfed treatments. After integrating the canopy cover into AquaCrop, the percentage of deviation of simulated and measured variables was reduced. The RMSE for yield was ranging between 0.08 and 0.69 t ha-1 before coupling, and between 0.04 and 0.42 t ha-1 after integration. This result confirmed that the integration framework is very effective tool, which needs further development and improvement before being applied on a larger scale in the Mediterranean areas