Irrigation Requirements Research Articles

The Synergistic Production Effect of Water and Nitrogen on Winter Wheat in Southern Xinjiang.

Water and nitrogen management are crucial for food security and the efficient use of water and fertilizer, especially in arid regions. Three irrigation levels, namely, 80% crop water requirement (ETC) (W1), 100% ETC (W2), and 120% ETC (W3), and three nitrogen application levels, namely, 0 kg/ha (N1), 207 kg/ha (N2), and 276 kg/ha (N3), were used as the experimental treatments, and a control group, denoted as CK, was created. The results show that the maximum height achieved was 82.16 cm under W3N3. There was a single-peak variation trend throughout the growth stages of SPAD. It peaked at 58.44 under W3N3 and then at 27.9 under W2N2. The net photosynthetic and transpiration rates displayed bimodal peaks and the phenomenon of a "photosynthetic midday depression". And the prominent peaks in leaf water use efficiency occurred at 14:00 and 18:00, alongside noteworthy enhancements observed under the W3 treatment. Water and nitrogen and their interactions significantly affected the dry matter (DM) of winter wheat, with the spike accounting for the highest percentage. The W2N2 treatment demonstrated superior effectiveness in enhancing winter wheat water use efficiency, offering the potential to decrease irrigation requirements by 20% and nitrogen application by 25%. Moreover, the maximum PFPN attained under W2N2 reached 60.13, representing a noteworthy 35.25% increase compared to the control group (CK), but the HI of the W2N2 treatment only reached 0.56. The highest HI was achieved with W3N2 (0.73), and the nitrogen application of 207 kg/ha was more conducive to obtaining a higher HI. The highest yield was achieved under W3N3 (13.599 t/ha), followed by W2N2 (12.447 t/ha), and the spike proportion exceeded 60% with W2N2, and its production cost and economic benefit ratio of under 0.31 were superior to those for other treatments. Multiple regression analysis revealed that the maximum yield reached 12.944 t/ha with an irrigation amount of 3420.1 m3/ha and a nitrogen application of 251.92 kg/ha. Overall, our study suggests using an optimal water-nitrogen combination, specifically an irrigation level of 2829 m3/ha and a nitrogen application rate of 207 kg/ha, leading to increased winter wheat yields and economic benefits. These research results provide a pragmatic technique for improving winter wheat production in southern Xinjiang.

Improving mangoes' productivity and crop water productivity by 24-epibrassinosteroids and hydrogen peroxide under deficit irrigation

In nature, plants are frequently subjected to a wide range of abiotic stresses that drastically reduce crop productivity. Deficit in irrigation is one of the main factors of abiotic stresses that affect agricultural productivity. Nevertheless, not much research has been done on how to use water with brassinosteroids (Br) and hydrogen peroxide (H2O2)in deficit water conditions in order to reach comparatively good values of mango tree growth, productivity, and fruit quality as well as crop water productivity (WPC). A split-plot experiment in a complete randomized block system design study with 3 regulated deficit irrigation levels i.e. 100% IR (Irrigation requirement), 80% IR, and 60% IR was implemented in 2022 and 2023, each irrigation regime was combined with the foliar application of distilled water (control), 1 mg/L Br, 10 mM H2O2, 1 mg/L Br + 10 mM H2O2. Foliar treatments were applied at 3 different phenological stages: flower bud induction and differentiation, full bloom, and beginning of fruit set. The results showed that fruit shape index and acidity significantly improved as irrigation volume increased, however, the proportion of fruit mineral content and fruit chemical characteristics was inversely correlated with the volume of water. Meanwhile, moderate regular deficit irrigation (80% IR) achieved marked increases in leaf minerals and total chlorophyll content, fruit quality, yield, and water use efficiency. Drought stress (60% IR) significantly decreased fruit set, fruit retention, yield traits, and fruit physical and chemical properties, at the same time, significant improvements in the content of stress indicators (proline, total phenols, and carotenoids) were observed compared with control. All treatments with Br and H2O2 alone or in combination under drought stress had a pronounced effect in this regard. Overall, foliar spray of 1 mg/L Br+10 mM H2O2 was the most powerful treatment that emended the unpropitious effect of water stress.

Comparing cryoballoon and contact-force guided radiofrequency ablation in pulmonary vein isolation for atrial fibrillation in patients with hypertrophic cardiomyopathy.

Pulmonary vein isolation (PVI) employing cryoballoon (CB) or contact force-guided radiofrequency (CF-RF) catheter ablation has been established as an effective strategy for managing atrial fibrillation (AF). However, its efficacy in hypertrophic cardiomyopathy (HCM) remains to be further explored. This retrospective study analyzed 60 consecutive AF patients with HCM (average age 67 ± 10 years; 41 men) who were consecutively admitted to our hospital from January 2014 to December 2022 and underwent initial PVI. The patients were treated with CB (26 patients) or CF-RF (34 patients). Successful PVI was achieved in both groups without significant complications. In the CF-RF group, additional ablations were performed on the cavotricuspid isthmus (14.7% of patients) and the anterior line (2.9%). The CB group benefited from reduced procedural times (93 ± 31 vs. 165 ± 60min, p < 0.05) and decreased saline irrigation requirements (77.5 ± 31.4 vs. 870 ± 281.9 mL, p < 0.0001). Using a contrast medium was exclusive to the CB group (33.8 ± 4.2 mL). In a 12-month follow-up, the atrial tachyarrhythmia recurrence-free rates in the CB and CF-RF groups were comparable (77% and 76%, respectively; p = 0.63 according to the log-rank test). Notably, pulmonary vein reconnection was prevalent in most (7 out of 8) patients requiring a secondary ablation procedure. PVI is feasible as a strategy for AF in patients with HCM employing either CB or CF-RF techniques. While the recurrence-free rates were comparable in both groups, differences were noted in procedure duration, saline usage, and the need for a contrast medium.

Assessment of Water Resources Potential of Ogun River for Irrigation Purposes at Middle Ogun Irrigation Project

The Middle Ogun Irrigation Project (MOIP) was conceived by the Federal Government of Nigeria to boost agricultural food production in the southwestern part of the country using modern irrigation facilities. However, water supply from the Ikere Gorge dam has been intermittent, particularly at the intake weir of this project, despite the enormous water resources on the dam. Therefore, this project assessed the water resources potential at the Odo Ogun intake weir guage station of the Middle Ogun Irrigation Project and evaluated the seasonal irrigation requirements on irrigation fields. The Flow Duration Curve (FDC) was derived at the gauge site for streamflow discharge from four quartiles and percentage reliability of Q95%, Q75%, Q50% and Q25%, which gave 32.40, 55.01, 60.00 and 90.00 m3/s, respectively. Hydrological modelling of the catchment was carried out using the MapWindow Soil and Water Assessment Tool (MWSWAT) for ten delineated sub-basins on the catchment and the average annual yield from the catchment was 10,094.00 mm/year. The net seasonal irrigation requirement of crops grown was evaluated using CROPWAT 8.0 and gave 428.46 mm per planting season.

Future Climate Change Impacts on Rice in Uttar Pradesh, India's Most Populous Agrarian State

AbstractUttar Pradesh, with a population of 237 million, is the largest agrarian state in India, located in the Indo‐Gangetic plains. Rice cultivation is widespread across all districts of Uttar Pradesh, which have varying climate regimes, irrigation infrastructures, crop management practices, and farm sizes. The state is characterized by different agroecological zones (AEZs) with semi‐arid to sub‐humid climates with significant variability in monsoon rainfall. In this study, the impact of climate change on Kharif‐season rice is estimated using crop‐climate scenarios in Uttar Pradesh. A process‐based Crop Simulation Model, Crop Estimation through Resource and Environment Synthesis‐Rice, was simulated with bias‐corrected and downscaled climate data for historical (1995–2014) and three future periods (the 2030s, 2050s, and 2090s) for two mitigation pathways (SSP2‐4.5 and SSP5‐8.5) from the Coupled Model Intercomparison Project 6. Phenology, irrigation amount, crop evapotranspiration, yield, and water use efficiency were evaluated and assessed for all AEZs. Based on the ensemble of 16 climate models, rainfed rice yield increased in the AEZs of western Uttar Pradesh due to increased rainfall, while in eastern Uttar Pradesh yield decreased, under both shared socioeconomic pathways (SSPs). Irrigated rice yield decreased in all AEZs under both SSPs due to an increase in temperature and a decrease in the length of the growing period, with reductions of up to 20% by the 2090s. Irrigation requirements decreased from the 2030s to the 2090s due to increased rainfall and decreased crop evapotranspiration. Despite the projected increase in rainfed yield, the overall rice yield is expected to decrease in the future under both SSPs.

Evaluating the precise grapevine water stress detection using unmanned aerial vehicles and evapotranspiration-based metrics

AbstractPrecise irrigation management requires accurate knowledge of crop water demand to adequately optimize water use efficiency, especially relevant in arid and semi-arid regions. While unoccupied aerial vehicles (UAV) have shown great promise to improve the water management for crops such as vineyards, there still remains large uncertainties to accurately quantify vegetation water requirements, especially through physically-based methods. Notably, thermal remote sensing has been shown to be a promising tool to evaluate water stress at different scales, most commonly through the Crop Water Stress Index (CWSI). This work aimed to evaluate the potential of a UAV payload to estimate evapotranspiration (ET) and alternative ET-based crop water stress indices to better monitor and detect irrigation requirements in vineyards. As a case study, three irrigation treatments within a vineyard were implemented to impose weekly crop coefficient (Kc) of 0.2 (extreme deficit irrigation), 0.4 (typical deficit irrigation) and 0.8 (over-irrigated) of reference ET. Both the original Priestley-Taylor initialized two-source energy balance model (TSEB-PT) and the dual temperature TSEB (TSEB-2T), which takes advantage of high-resolution imagery to discriminate canopy and soil temperatures, were implemented to estimate ET. In a first step, both ET models were evaluated at the footprint level using an eddy covariance (EC) tower, with modelled fluxes comparing well against the EC measurements. Secondly, in-situ physiological measurements at vine level, such as stomatal conductance (gst), leaf (Ψleaf) and stem (Ψstem) water potential, were collected simultaneously to UAV overpasses as plant proxies of water stress. Different variants of the CWSI and alternative metrics that take advantage of the partitioned ET from TSEB, such as Crop Transpiration Stress Index (CTSI) and the Crop Stomatal Stress Index (CSSI), were also evaluated to test their statistical relationship against these in-situ physiological indicators using the Spearman correlation coefficient (ρ). Both TSEB-PT and TSEB-2T CWSI related similarly to in-situ measurements (Ψleaf: ρ ~ 0.4; Ψstem: ρ ~ 0.55). On the other hand, stress indicators using canopy fluxes (i.e. CTSI and CSSI) were much more effective when using TSEB-2 T (Ψleaf: ρ = 0.45; Ψstem: ρ = 0.62) compared to TSEB-PT (Ψleaf: ρ = 0.18; Ψstem: ρ = 0.49), revealing important differences in the ET partitioning between model variants. These results demonstrate the utility of physically-based models to estimate ET and partitioned canopy fluxes, which can enhance the detection of vine water stress and quantitatively assess vine water demand to better manage irrigation practices.

Improving prediction accuracy of CSM-CERES-Wheat model for water and nitrogen response using a modified Penman-Monteith equation in a semi-arid region

Context or problemThe implementation of crop models for water and nitrogen management are important in preserving water resources and reducing groundwater pollution. The Decision Support System for Agrotechnology Transfer (DSSAT) is a collection of field-scale process-based crop models that simulate crop growth and yield in response to water and nitrogen management as well as many other factors. Objective or research questionThe objective of this study was to improve the simulation of irrigation and nitrogen fertilizer effects on growth and yield of winter wheat using locally modified Penman-Monteith (PM) equation. Specifically, we focused on improving the estimation of ETo using a locally modified Penman-Monteith (PM) equation in the CSM-CERES-Wheat model. MethodsField measured data from a two-year experiment (2009–2010 and 2010–2011) in a semi-arid region were used to calibrate and evaluate the CSM-CERES-Wheat model in a region with strong advective condition. In this experiment, the irrigation treatments were 1.2, 1.0, 0.8, 0.5 times by full irrigation requirements and rain-fed, and nitrogen treatments were 0, 46, 92, and 136 kg N ha−1. ResultsUsing the CSM-CERES-Wheat model with the unmodified PM equation resulted in some growth variables such as: aboveground dry matter, grain yield, and grain nitrogen uptake with high normalized root mean square error (NRMSE) of 0.51, 0.35, and 0.32, respectively. However, using the modified PM equation for ETo module under semi-arid condition improved the soil water content estimation and the model outputs, such as the above ground dry matter, grain yield and grain nitrogen uptake with NRMSE of 0.2, 0.15 and 0.16, respectively, that are accurate. This modification provided more accurate estimations, particularly in our experimental site in semi-aid region with strong advective conditions. ConclusionsThe findings of this study indicated that the locally modified PM equation in the CSM-CERES-Wheat model enhanced the accuracy of estimating irrigation and nitrogen fertilizer on the growth and yield of winter wheat. By improving the estimation of ETo value, the model's performance in simulating crop responses to water and nitrogen management was significantly enhanced. Implications or significanceThe utilization of the accurately estimated ETo value of the modified PM equation has significant importance in the practical application of the CSM-CERES-Wheat model. Furthermore, this modification greatly enhances the accuracy of model outputs, particularly at our experimental site located in a semi-arid region with robust advective conditions.

Controlling Sedimentation through Regulating the River by Thalpitigala Reservoir Project

Abstract. Mahaweli is the main river in Sri Lanka and it has many main multipurpose reservoirs, especially to cater power and irrigation requirement of the country. Reservoir capacity loss which is the major problems causing to the effectiveness of the major reservoirs in Sri Lanka, is mainly caused by sedimentation due to upstream erosion. Hence proper monitoring, calculating and adopting measures are very important in planning a reservoir. But due to the complex nature of factors effect on sedimentation and lack of long-term data make calculation difficult. This study discusses how different data obtained from numerical modelling and bathymetric surveys of different locations of the catchment and those are used to select and verify the empirical equation, calculation of capacity loss and make proposals to minimise sedimentation for proposed Thalpitigala Multipurpose Project in Mahaweli upper catchment. The outcomes indicate high erosion (690 m3 km−2) and sediment transportation making rapid loosing of the capacity (5.13 MCM in 15 years) of the proposed reservoir. Thus, upper catchment protection with reforestation to reduce erosion, introduction of check dams in the upstream flow to trap the transported sediment and introduction of proper removal measures of deposited sediment are discussed for the proposed reservoir project.

IOT BASED SMART PLANT MONITORING SYSTEM

In agriculture, the efficient use of water resources is crucial for maximizing crop yield. This project introduces an open-source, IoT-based smart system designed to predict irrigation requirements by monitoring soil moisture, temperature, humidity, and external factors like obstacles or intruders using infrared sensors. The system employs an algorithm that integrates sensed data to make irrigation predictions. Implemented on a pilot scale, the system wirelessly collects sensor data via cloud-based web services. Both web and mobile interfaces provide real-time insights and decision support based on sensor analysis. Results indicate significant differences between monitored and unmonitored environments, impacting plant health in the short and long term. Graphical representations aid in visualizing environmental variations over time intervals. Future enhancements may include integrating other technologies to predict rainfall, manage pH levels, and secure data stored in the cloud. This would enhance the system's long-term viability and reduce dependency on manual operation. Key Words: Agriculture, IoT (Internet of Things), Water Resources, Soil Moisture, Temperature, Humidity, Irrigation Management, Open-Source Technology ,Sensor Nodes etc.

Effects of Water Stress and NPK Levels on Growth and Yield Attributes of Greenhouse-Grown Cucumbers

Judicious use of water and nutrients is a key factor for successful off-season vegetable production in greenhouses. This experiment was conducted under plastic tunnels to evaluate the effect of water stress and NPK levels on the growth and yield attributes of greenhouse-grown cucumbers. Effect of three irrigation levels viz., 100%, 80% and 60% of actual crop evapotranspiration (ETc) and three drip fertigation levels, viz., 100%, 80% and 60% of the recommended dose of NPK (RDF) with control (furrow irrigation with 100% RDF) were studied in a randomized complete block design experiment. The study indicated better plant growth, a greater number of fruits per plant and enhancement in the yield under drip irrigation. Among the various treatments, T5 (W80%ETc.F80% RDF) resulted in the highest mean fresh fruit yield (66.7 ton/ha) while the full irrigation treatments T1 (W100%ETc.F100% RDF) and T2 (W100%ETc.F80%RDF) recorded the lowest mean fresh fruit yield of 12.9 t/ha and 13.9 t/ha, respectively, as against 9.6 t/ha for the control plot. Conversely, the fully stressed T7, T8 and T9 treatments reduced the irrigation requirement by 29%, 26% and 21% but the mean cucumber yield was significantly decreased by 40%, 70% and 59%, respectively. These results suggested that drip irrigation has a great scope for the production of off-season vegetables. A water deficit level of 80% ETc with 80% RDF is the most appropriate treatment and optimal level to obtain better yield, quality and profitability of greenhouse-grown cucumbers under scarce water resources.

Solar Based Smart Irrigation System

This article presents a novel mobile application utilizing modern information and communication technology for agriculture, centered on the Internet of Things (IoT), embedded systems, and unmanned aerial vehicles (UAVs). The proposed agricultural monitoring system, employing Arduino microcontroller boards, Wi-Fi modules, and environmental sensors, facilitates data collection on temperature, humidity, and soil moisture. UAVs gather environmental data across the farm, enabling cloud-based computation of irrigation requirements for each region. Additionally, the system remotely monitors farm conditions, including water needs, through an Android mobile application, aiding farmers. Results indicate the effectiveness of our IoT-based system in reducing unnecessary water irrigation, aligning with smart agriculture goals. As the global population burgeons, the demand for increased food production escalates. Traditional farming methods necessitate extensive labor and water usage. This paper introduces a compact automated agricultural system prototype. Employing directional guides, the hardware enables precise processes such as seeding, humidity sensing, and watering, ensuring optimal crop growth and economic viability. From seed sowing to watering, the entire system operates autonomously. Testing involved integrating the hardware with a scaled-down plantation model to validate functionality. Keywords: Solar Panels, Arduino Uno, Soil Moisture Sensor, Relay, Lithium Battery, PIR Sensor, TP4058 Module, Gear Motor, LDR Sensor, Submersible Pump, Buzzer.

Water and carbon footprints in irrigated vineyards: an on-farm assessment

AbstractThis research aims to contribute to improving water and carbon efficiency in irrigated grapevine production in the dry Mediterranean climate of southern Europe. In regions with water scarcity, irrigation has become a relevant input in viticulture, essential to increase productivity and achieve profits. The joint estimation of the water footprint (WF) and the carbon footprint (CF) can help to comprehensively assess the environmental implications and sustainability associated with water-intensive grapevine cultivation. In this study, the WF and CF, of the farming stage of grapes production, were calculated for three years, in three vineyards located in southern Portugal. Data used for the calculation included meteorological data, irrigation requirements, energy use, fertilizers, and pesticide inputs. The total WF mean value for the study period was 223 m3 ton−1, lower than values found for similar conditions, but the blue component, related to irrigation, was predominant, with a higher proportion (75%) occurring during the driest year. The mean total CF was 98 kg CO2e ton−1; the major contributors were fuel use, fertilizer greenhouse gas emissions, and energy for irrigation. The factor analysis revealed relationships between footprint components, yielding latent variables participated by irrigation water and energy use, pollution loads and agrichemicals use. The examination of trade-offs and/or advantageous relations between footprints and yields showed that seasonal climate conditions play an important role via their effect on the farming practices and the inputs most influential on these indicators, namely: crop water requirement; irrigation volumes; energy for irrigation; fuel consumption; nitrogen and phosphorus fertilization rates.

Machine learning and Sensor-Cloud Based Precision Agriculture for Intelligent Water Management for Enhanced Crop Productivity

The combination of Machine Learning algorithms with Internet of Things devices is emerging as an effective solution to redefining precision agriculture for better water management and crop cultivation. The purpose of this study is to use different learning models, such as Artificial Neural Networks , Support Vector Machines , Decision Trees , and Random Forest , to predict the irrigation need based on real-world sensor data. To retrieve the output variable, which is the irrigation requirement, data from temperature, soil moisture, water level, and humidity sensors that are available in a tomato cultivation facility are used. The dataset consists of 3422 readings, which are split into training and testing sets. A designated percentage of 70% is used for training the models, while the remaining 30% are used to test the outcomes. As the results of the study show, the ANN model is the most accurate predictor of irrigation need with the classification rate of 97.6%, followed by SVM , DT , and RF with 95.4%, 91.3%, and 88.9% correspondingly. The differences in the outcomes are demonstrated in confusion matrices, which identify the classification of the cases and indicate the percentage of correct predictions. Evidence of the predictive power of ML models implies that farmers can independently determine when to activate the pump when real-world data serve as the input. Additionally, the ability to collect real-world data using IoT sensors is beneficial, as it empowers farmers with up-to-date information to make a timely decision about pump activation. The limitations are associated with the type of crop and agricultural facility and, for this reason, future studies may investigate the generality of the conclusion with regard to other crop types and facilities.

7.5F Mini Flexible Ureteroscope in Retrograde Intrarenal Surgery: Initial Results from a Multicenter Randomized Clinical Trial.

Objective: To report the initial results of an randomized clinical trail comparing the safety and efficacy between 7.5F and 9.2F flexible ureteroscope (FUS) in the management of renal calculi <2 cm. Materials and Methods: Eighty patients were enrolled and received retrograde intrarenal surgery (RIRS) with a different size FUS. The operation results and complications were compared. Results: Two cases in the 7.5F group and four cases in the 9.2F group failed to insert the 12/14F ureteral access sheath (UAS), respectively, and no significant difference (p = 0.396) was noted. However, 10/12F UAS was inserted in the 7.5F group, but not available in the 9.2F group, and thus, the 10/12F UAS inserting rate in the 7.5F group was higher than in the 9.2F group (100% vs 0%, p = 0.014), and the UAS insertion failure rate in 9.2F group was higher than in the 7.5F group (10% vs 0%, p = 0.040). The operation time in 7.5F group was shorter than the 9.2F group (35.60 ± 7.86 vs 41.05 ± 8.14, p = 0.003). Less irrigation was required in 7.5F group (813.93 ± 279.47 mL vs 1504.18 ± 385.31 mL, p = 0.000). The postoperative fever rate in 9.2F group was higher than 7.5F group (20% vs 5%, p = 0.043). There was no significant difference in sepsis (0% vs 2.5%, p = 0.314) between the two groups. No significant difference was noted in hospital stay (0.93 ± 0.49 days vs 1.14 ± 0.64 days, p = 0.099) between the two groups. The final stone-free rate (SFR) in 7.5F group was higher than 9.2F group (95% vs 80%, p = 0.043). Conclusion: The latest 7.5F mini FUS was a reliable instrument in RIRS to keep a good visualization with low requirement of irrigation, low postoperative infection complication, and also a high SFR when compared with the conventional 9.2F FUS. Clinical Trial Registration: NCT05231577.

Assessment of Physicochemical Quality and Challenges of Municipal Sewage Water in Manchalapur Village in the Karnataka, India

The present study was carried out on characterization of municipal sewage water tank of Manchalapur village near Raichur city in Karnataka. The water samples were collectedeight times from four different locations like inlet, outlet and water spreading area of the Manchalapur tank during the year 2018-2019 in monsoon and post monsoon season. The collected water samples were analyzed for the water quality parameters by using standard procedure. The results obtained were compared with Central Pollution Control Board (CPCB) and Bureau of India Standards (IS 2296:1992) water quality requirements for irrigation. The results showed that pH (7.89, 8.54), Electrical Conductivity (1.41, 1.48 dSm-1), Total Dissolved Solids (929.63, 1031.56 mg L-1), Carbonate (2.15, 0.86 mg L-1), Bicarbonate (7.71,4.99 mg L-1), Nitrate (26.90, 34.09 mg L-1), Phosphate (9.85, 6.20 mg L-1), Calcium (3.38, 2.77 mg L-1), magnesium (5.16, 4.13 mg L-1), Sodium (0.85, 0.92 mg L-1), Biological Oxygen Demand (1396.88, 1252.31 mg L-1), Chemical Oxygen Demand (14480, 8573.0 mg L-1), Dissolved Oxygen (7.91, 8.02 mg L-1) and turbidity (13.33, 8.77 NTU) for monsoon and post monsoon respectively. All the water quality parameters were within the recommended range of irrigation standards except the parameters BOD, COD, DO and turbidity. The results could be applicable advice to farmers and agricultural researchers for proper management and use of tank water for agricultural purpose.

Cowpea (Vigna unguiculata L. Walp) morpho-physiological and yield responses to chemical, organic, and biofertilizers at various watering levels utilizing drip irrigation system

ABSTRACT The infertility of sandy soil hampers the growth of many crops. Typically, chemical fertilizers are used to handle this issue, but they are expensive and have deleterious implications on the ecosystem. A two-year field investigation was carried out on cowpea cultivated in sandy soil to assess the effects of different watering levels (70, 80, 90, and 100% of the actual irrigation requirements), chemical fertilizers, organic fertilizers, and biofertilizer (Bradyrhizobium sp.), and their combinations on the morpho-physiological traits and yield of cowpea (Vigna unguiculata L. Walp, cv. Giza 18). Overall, the findings showed that cowpea osmoregulatory molecules (sugars, proteins, and proline) demonstrated greater accumulation, with the content depending on the watering level. The applied fertilizers demonstrated improved cowpea performance at the regular watering level, with chopped potato tops outperforming other fertilizer formulations. Furthermore, the combination of water stress treatments and fertilizer formulations was impactful in relieving the detrimental consequences of water stress as it enhanced plant growth performance, production efficiency, metabolic homeostasis, nutritional value, and mineral ions composition. Subsequently, our results demonstrated agro-wastes, particularly chopped potato tops, could be an effective substitute for chemical fertilizers in sandy soils to sustainably increase soil fertility as well as cowpea yield performance.

Effect of super absorbent hydrogel on hydro-physical properties of soil under deficit irrigation

Due to water scarcity challenges, efficient management of irrigation water is becoming crucial. Water use efficiency (WUE) involves increasing crop productivity without increasing water consumption. This study was carried out to study the effect of hydrogel, deficit irrigation and soil type on WUE, soil hydro-physical properties and lettuce productivity. For this purpose, four irrigation treatments (100%, 85%, 70% and 60% of full irrigation requirements), four hydrogel concentrations (0, 0.1, 0.2 and 0.3% w/w) and three soil textural classes (clay, loamy sand, and sandy-clay soil) were conducted in pot experiment at open field during two consecutive seasons. The results revealed that crop growth parameters and soil hydro-physical properties were significantly affected by hydrogel application rates. Hydrogel addition significantly enhanced head fresh and dry weights, chlorophyll content, number of leaves and WUE. Application of hydrogel at 0.3% and 85% of irrigation requirements achieved the highest WUE without significant yield reductions. Changes in the studied hydro-physical properties of soil were more dependent on soil texture and hydrogel application rate than on the amount of irrigation water. The significant decrease in soil saturated hydraulic conductivity and bulk density confirms that super absorbent hydrogels could be recommended to improve soil water retention and enhance water use efficiency under deficit irrigation conditions.

The physical and chemical properties of the technosols in the pot experiment with waste and groundwater irrigation

&#x0D; &#x0D; &#x0D; Mediterranean areas are characterized by a strong spatial variability that makes the soil hydrogeological logical response highly complicated. Some seasons provoke dramatic changes in soil properties determining the runoff rates, such as soil water content or soil water repellency. In recent years, important progress has been made in adapting water needs to local conditions through the use of various parameters to assess soil water status. Estimation of the water status of the soil has been widely used in soil science as a tool for quantitative analysis. The main objective of this case study was to analyze technosol and irrigation water physical and chemical properties in the pot experiment with lysimeters. A pot experiment with Avocado rootstocks was equipped with lysimeters in the facilites of the «La Mayora Experimental Field site» of the Higher Council for Scientific Research (Spain). The scheme of the pot experiment included three sources of irrigation: a) groundwater; b) regenerated municipal wastewater (100%); c) a mix of ground and regenerated municipal wastewater (50 / 50%). Chemical analysis data indicate that the reclaimed wastewater does not meet irrigation requirements in terms of pH, EC and due to the significant content of sodium and chlorine. Even groundwater satisfies irrigation water qualitative requirements partially. The suitability of irrigation water on pH level can be characterized mainly as unsuitable and doubtful. Diluting regenerated wastewater with groundwater following the 50% principle led to a decrease in the potential risks for salinization of groundwater connected with leaching of the leachate. The dynamics of the change in the volume of leachate are related to precipitation, the frequency of irrigation, and different manifestations of the physical, mineralogical, and chemical properties of technosols.&#x0D; &#x0D; &#x0D;

Characterization of partially defatted moringa seed flour obtained at different temperatures

Moringa oleifera is a plant well-adapted to climate change due to its low irrigation requirements and resistance to high temperatures. The moringa seeds are very rich in proteins, oil and carbohydrates. For that reason, the aim of this study was the assessment of defatted moringa seeds (DMS), obtained after extracting oil from moringa seeds at different temperatures (from 70 to 220 °C), by analyzing the composition, aw, CIEL*a*b* coordinates, water holding capacity, antioxidant capacity and phenolic profile. The results showed that DMS had ≈50 % proteins, ≈10 % fats and ≈29 % carbohydrates, the rest being water (≈4 %) and ashes (7 %). The highest temperature applied caused a significant reduction in the b* coordinate (from 17.4 to 9.5) and luminosity (from 55 to 45), giving rise to DMS that were darker brown in color. DMS were rich in polyphenols, which were enhanced at the highest temperature (220 °C) such as in the case of gallic acid (from 4.4 to 43 mg/100 g DMS) and rutin (from ≈4.4 to 53 mg/100 g DMS), as also happened with the total antioxidant capacity. In conclusion, DMS obtained at 70-190 °C have similar properties and their rich protein and antioxidant profile may offer up new possible uses in different food matrices for prospective future uses.

Agrivoltaic system design tools for managing trade-offs between energy production, crop productivity and water consumption

Agrivoltaic systems that locate crop production and photovoltaic energy generation on the same land have the potential to aid the transition to renewable energy by reducing the competition between food, habitat, and energy needs for land while reducing irrigation requirements. Experimental efforts to date have not adequately developed an understanding of the interaction among local climate, array design and crop selection sufficient to manage trade-offs in system design. This study simulates the energy production, crop productivity and water consumption impacts of agrivoltaic array design choices in arid and semi-arid environments in the Southwestern region of the United States. Using the Penman–Monteith evapotranspiration model, we predict agrivoltaics can reduce crop water consumption by 30%–40% of the array coverage level, depending on local climate. A crop model simulating productivity based on both light level and temperature identifies afternoon shading provided by agrivoltaic arrays as potentially beneficial for shade tolerant plants in hot, dry settings. At the locations considered, several designs and crop combinations exceed land equivalence ratio values of 2, indicating a doubling of the output per acre for the land resource. These results highlight key design axes for agrivoltaic systems and point to a decision support tool for their development.