Comprehensive understanding of tree characteristics and conditions holds paramount importance for the precise management of hazelnut orchards. It facilitates the determination of tree vigor, pruning requirements, phytosanitary interventions, and plant water consumption. The primary objective of this study was to explore, for the first time on a fruit tree with a bushy structure and across trees of four Italian distinct hazelnut cultivars, the efficacy of multispectral and thermal UAV (Unmanned Aerial Vehicle) technologies in assessing canopy attributes, vegetative growth, and predicting abiotic stresses. These technologies serve as tools for precision agriculture, enabling the computation of various indices such as the Normalized Difference Vegetation Index (NDVI) and crop water stress index (CWSI). The study of water content is of particular importance at this time, especially considering the increasing water stress levels in Europe as well as globally. While Red Green Blue (RGB) and thermal imagery collectively demonstrated superior performance in model reconstruction, the multispectral UAV remained more adept at characterizing size traits of hazelnut plants. Thermal images alone proved inadequate for accurately reconstructing hazelnut biometric characteristics. Furthermore, all indices were found to be cultivar-specific, underscoring the importance of conducting studies across different cultivars. The utilization of two UAVs, namely multispectral and thermal, facilitated the examination of the relationship between NDVI and CWSI across tree species.

In water scarcity regions, using data-driven approaches to predict groundwater level is challenging due to limited data availability. However, these regions have substantial water needs and require cost-effective groundwater utilization strategies. In this study, we use artificial intelligence to predict groundwater levels to provide guidance for drilling shallow boreholes for subsistence irrigation. The Bilate watershed, which is located in southern Ethiopia, was selected as the study area. This is typical of areas in Africa with high demand for water and limited availability of well data. Using a non-time-series database of 75 boreholes, machine learning models including multiple linear regression, multivariate adaptive regression spline, artificial neural networks, random forest regression, and gradient boosting regression (GBR) were constructed to predict the depth to the water table. 20 independent variables were considered in the models. GBR performed the best of the approaches with an average 0.77 R-squared value on testing data. Finally, a map of predicted water levels in the Bilate watershed was created based on the best model with water levels ranging from 1.6 to 245.9 meters. With the limited set of borehole data, the results show a clear signal that can provide guidance for borehole drilling decisions for sustainable irrigation with additional implications for drinking water.

This study was to determine the effects of different irrigation, fertigation and mulching applications on the yield and quality parameters of strawberries. The study was conducted at the Bursa Uludağ University Yenişehir Ibrahim Orhan Vocational School Agricultural Research Field in 2019-2020. In the research, four different irrigation topics, three different fertigation and three different mulching topics were selected The maximum and minimum yield values of the study years were calculated as 5.05-18.70 t ha-1 and 1.20-8.7 t ha-1, respectively, from I100F100M1 and I25F50M0 treatments. As a result, a three-factor study determined that irrigation, fertigation, and mulching had a significant effect on the yield and quality characteristics of strawberries. However, when the reductions in yield and quality losses are evaluated together, despite the reductions in irrigation water and fertigation levels, I75 and F75 topics can be recommended. Also, in mulching treatments, black mulch material (M1) should be chosen over clear mulch material (M1) and no mulch (M0).

Light and heat resources are ample in Xinjiang plain oasis region. Planting structure is single in irrigation area, which leads to severe seasonal water shortages due to high concentration of water utilization. Therefore, how to make full use of light and heat resources to develop oasis agriculture without expanding planting scale has become the focus of research. The biannual cropping patterns are possible solutions to the problem. Manas River Irrigation area, which is located on the northern slope of Tianshan Mountain in Xinjiang in China is regarded as a typical case study to analyze the suitable planting structure and planting scale for biannual cropping pattern. The effects of optimizing planting patterns on alleviating the contradiction between water supply and water need，and the efficiency of water resources utilization was also studied. The results of the study show that：(1) the suitable planting scales of Manas River irrigation area in wet year (P = 25%), normal year (P = 50%), and low flow year (P = 75%) are about 72.66%, 78.73% and 83.91% of the current planting scale. (2) After the planting structure was optimized, the water use process in the irrigation area extends from May to August at present to April to November. The water use ratio at the peak period of water use decreased from 0.847 to 0.601, and the water use peak was significantly dispersed. (3) Economic benefits per cubic metre of water of the biannual cropping patterns increased from 8.65 yuan·m⁻³ at present to 9.45 yuan·m⁻³, 10.31 yuan·m⁻³ and 11.43 yuan·m⁻³ in wet year (P = 25%), in normal year (P = 50%) and low flow year (P = 75%) respectively, which proved that replanting crops could improve the efficiency of water resources utilization in irrigated areas. Therefore, the optimal planting pattern can be implemented to improve the utilization efficiency of soil and water resources in irrigation area in the arid oasis with single planting pattern with excessive concentration of water use peak and serious water shortage.

Implementation of the German Climate change Strategy in the Federal State of Saxony-Anhalt is discussed in this paper. It shares the requirement and importance of sustainable development. An overview of strategy, The DAS Indicator System is provided with results of a portion of work being done for the ministry of agriculture by Deutscher Wetterdienst (DWD). Applicability of the indicator system is also shown by evaluation of results for specific indicators from 1961-2015.

This paper provides a study on the development of solar energy, its prospects, and its impacts in Africa. Although the main focus is on technologies adopted for different uses (solar farms, mini-grids, off-grid, solar houses, irrigation, lighting, etc.), we also consider some aspects that increase the adoption of solar energy, such as legislation and business models. Finally, we will examine current and future solar projects managed by NGOs and international companies and how they benefit to leveraging social and economic standards, quality of life as well as capacity building in Africa. This study shows the plethoric interest of institutions outside Africa in the market of solar energy in the continent and that there is no African strategy to increase its independency toward a sustainable development particularly through energy transition.

In times of water scarcity, water conservation measures from authorities are primarily directed to the residential sector—homeowners and renters who engage in individual activities to reduce water consumption. Business owners, manufacturers, and institutional workers—the ICI sector, generally, do not receive targeted information and education on water savings measures, and when they do, the information, typically, refers to indoor technologies, and behavior choice. In answer to this shortfall, this research illustrates how the ICI sector might engage in outdoor water conservation and, thus, realize water savings using the well-established Pittenger’s Simplified Landscape Irrigation Design Estimation (SLIDE) formula that estimates outdoor water conservation/savings for the lesser studied industrial, commercial, and institutional (ICI) sector. We applied the SLIDE formula five diverse climate areas in Texas to demonstrate the potential water savings in each, as well as identifying the type of water technology measures that yielded the greatest water savings for outdoor ICI landscapes. Overall, the greatest water savings for outdoor ICI landscapes was realized through smartscape design with soil moisture sensors-SMS technology, second best. Our findings will provide ICI facility owners/managers with knowledge and examples of a simplified system for quantitative decision making when considering choices among technologies and/or practices toward outdoor water conservation for their own facilities.

For water-stressed regions like Iran improving the effectiveness and productivity of agricultural water-use is of utmost importance due to climate change and unsustainable demands. Therefore, a hydro-economic model has been developed here for the Zarrine River Basin with the central concept of that demands are value-sensitive functions, where quantities of water-uses at different locations and times have a changeable economic benefits. To do this, the potential crop yields and the surface and groundwater resources, especially Boukan Dam inflow are simulated using the hydrologic model, SWAT, based on predicted climatic scenarios i.e. quantile mapping-downscaled projections. Then, to allocate the agricultural water based on the agro- economic crop water productivity (AEWP) of crops, a basin-wide water management tool, MODSIM, is customized. Next, a simulation- optimization model has been developed using a coupled CSPSO-MODSIM, to optimize the total AEWP, considering climatic impact and crop pattern scenarios, for 2020-2038, 2050-2068 and 2080-2098 periods. Finally, the optimum crop pattern and crop water irrigation depths are presented for different RCPs and periods. The results indicated that this approach will improve considerably the AEWPs and decrease the agricultural water-use up to 40%. Thus, this integrated model is able to support water authorities and other stakeholder in a water-scarce basin, as is the study area.

Irrigated agriculture determines large blue water withdrawals, and it is considered a key intervention area to reach sustainable development objectives. Precision agriculture technologies have the potential to mitigate water resource depletion that often characterizes conventional agricultural approaches. This study investigates the factors influencing farmers' intentions to adopt variable rate irrigation (VRI) technology. The Technology Acceptance Model 3 (TAM-3) was employed as a theoretical framework to design a survey to identify the factors influencing farmers' decision-making process when adopting VRI. Data were gathered through quantitative face-to-face interviews with a sample of 138 fruit and grapevine producers from the Northeast of Italy (Veneto, Emilia-Romagna, Trentino-Alto Adige, Friuli-Venezia Giulia). Data were analyzed using partial least squares path modelling (PLS-PM). The results highlight that personal attitudes, such as perceived usefulness and subjective norm, positively influence the intention to adopt VRI. Also, the perceived ease of use positively affects intention, but it is moderated by subject experience.

A method for calibrating models of agricultural production and resource use presented by Howitt [1] for policy analysis is proposed to leverage multidisciplinary agricultural research at the National Center for Alluvial Aquifer Research (NCAAR). An illustrative example for Sunflower County, MS is presented to show how plot-level research can be extended to draw systemic region or basin wide implications. A hypothetical improvement in yields for dryland soybean varieties is incorporated to the model and shown to have a positive impact on aquifer outcomes and producer profits. The example illustrates that a change in one practice-crop combination can have system-wide impacts as evidenced by the change in acreages for all crops and practices.