Pipe material governs biofilm development and microbial communities more than organic suspended solids in drip irrigation systems in greenhouse settings.

Mitigating emitter clogging in high-sediment water drip irrigation systems through selection of appropriate organic fertilizers

It is crucial to accurately obtain the flow index in designing and developing labyrinth drip irrigation emitters. This study designed a pit drip irrigation emitter based on plant biomimetic principles, and created training-testing datasets (160 data points) and external validation datasets (25 data points) through experiments. The improved backpropagation neural network (BP) regression algorithm based on particle swarm optimization (PSO) is used to predict the flow index of the pit drip irrigation emitter. The input parameters include the pit depth l, the inner and outer boundary spacing h, the flow channel angle θ, and the pit aperture j. There were four combinations with the different hidden layer settings, namely BP1, BP2, BP1-PSO, BP2-PSO. 85% of the training-testing dataset was used to train the developed model (using 5-fold cross-validation), of which 15% was used for testing. The reliability of the prediction model was evaluated using mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), mean absolute percentage error (MAPE), uncertainty at 95%(U95), coefficient of determination (R2), and global performance indicator (GPI). The results indicated that the optimal structures of BP1 and BP (input-hidden layer-output) were 4-7-1 and 4-4-9-1. The BP2-PSO model had the best prediction accuracy and stability, MAE, MSE, RMSE, MAPE, U95, R², and GPI values were 1.98 × 10- 3, 5.49 × 10- 6, 2.34 × 10- 3, 4.09 × 10- 3, 6.46 × 10- 3, 0.9456, and 3.74 × 10- 3, respectively. the evaluation values were 6.46 × 10- 3, 0.9456 and 3.74 × 10- 3 respectively. The GPI of BP1, BP2, BP1-PSO and BP2-PSO were 6.35 × 10- 3, 5.96 × 10- 3, 4.88 × 10- 3 and 3.74 × 10- 3 respectively, indicating good prediction accuracy. The ranking of prediction accuracy was as follows: BP2-PSO > BP1-PSO > BP2 > BP1. The four models were tested on the external validation dataset, the R² values of all four models were higher than 0.85, indicating good correlation. Through SHAP analysis, the importance of structural parameters to the flow index is ranked as: j > θ > h > l. In order to verify the validity and extensive superiority of BP-PSO model in solving drip irrigation emitter flow index prediction problem, it was compared with six representative machine learning models, including classical models (GR and MLR), integrated models (CatBoost and LSBoost) and hybrid models (MLP-SVM and MLP-DT). The BP2-PSO and BP1-PSO models had the highest prediction accuracy in the training-testing process among ten machine learning methods, and BP2-PSO model had the highest prediction accuracy in the external validation process, which indicated that particle swarm optimization can improve the accuracy of neural network models. The BP2-PSO model was used to predict the flow index had greater advantages during the design and development stages of pit drip irrigation emitters.

Efficient water management is critical for sustainable chrysanthemum production under protected cultivation was conducted at Indian Agricultural Research Institute (IARI), New Delhi, India. While HYDRUS-based models are widely used for simulating soil water dynamics under drip irrigation, their application in floriculture crops remains limited, particularly for deriving crop-specific irrigation strategies. This study integrates field experimentation (2020-2023) with HYDRUS-2D simulations to evaluate soil water distribution under drip fertigation across multiple soil types. The effects of emitter discharge, irrigation scheduling, and soil hydraulic properties were analyzed to determine optimal root-zone moisture conditions. Results showed that soil moisture remained within the optimal range for up to 48h after irrigation under appropriate scheduling. Among soil types, moisture retention followed the order: silt ≈ silty clay loam > loam > sandy clay loam > sandy loam. Model validation demonstrated high accuracy (R2 = 0.90-0.96; RMSE = 0.011-0.012; Ceff = 0.90-0.92), confirming the reliability of HYDRUS-2D. Simulation results indicated that an emitter discharge of 1.0 lph combined with a 48-hour irrigation interval maintained optimal root-zone moisture while minimizing deep percolation losses. The study highlights the potential of simulation-based approaches for optimizing irrigation design and improving water-use efficiency in greenhouse floriculture systems.

Function diagrams focus on physiological concepts rather than associated structures and can serve as elaboration tools and mnemonic aids. A function diagram prototype of the gastrointestinal system was recently described (Wilson TE, Barrett KE. Adv Physiol Educ 45: 264-268, 2021). In this article, a functional diagram of the glomerulus, nephron, urinary system, and bladder is proposed. Colloquially named "Nessie the Nephron" to loosely capture the looping structure and elusive understanding of renal blood flow, glomerular filtration, and epithelial transport for the student, not to mention the nearly mythical countercurrent multiplier. "Navigating the Lochs" references Nessie's possible habitat and more importantly the movement and storage of the modified ultrafiltrate from the nephron. The primary analogies that form the structure of this function diagram are Rain Barrel, Soaker Hose, and Hose Nozzle (afferent and efferent blood flow and filtration pressure); Water Purification System (glomerular filtration barrier forming multiple step filtration process involving the capillary, basement membrane, and podocytes); Mixed Recycling Machine (proximal tubule individual, co-, and bulk transport); Desiccator and Briner (thin descending limb removal of water and thin/thick ascending limb removal of salt); Conveyor Belt Picker (distal nephron selective ion transport); and Concentrator (collecting duct water and urea transport). The primary analogies that elaborate Navigating the Lochs are Aqueduct and Cistern System (fluid movement and collection); and Pressure Gauge, Syringe Bulb, and Two-Valve Plumbing (bladder storage and micturition). Complementing these analogies is the rich potential for inclusion of clinical and comparative applications and examples to link previous knowledge and strengthen memories for future retrieval.NEW & NOTEWORTHY Function diagrams put the focus on physiology and physiological concepts rather than the associated anatomy and can serve as elaboration tools and mnemonic aids. The function diagram of the nephron can provide analogies for glomerular filtration, bulk and selective epithelial transport, and overall ability to create concentrated or dilute urine. The function diagram of the urinary system and bladder can provide analogies for moving and storing urine and finally micturition.

Valorization of vitamin C industrial byproduct as a soil amendment: Environmental benefits and enhancement of maize productivity.

Drip irrigation and integrated amendments drive soil–crop system improvements in calcareous soils

Enhancing Food Security and Environmental Sustainability Using Magnetically Treated Saline Groundwater with Trickle Irrigation

Effect of Surface Drip Irrigation Partial Root-Zone Drying and Polymer Addition on Some Soil Water Criteria and Cauliflower Production

Water scarcity is emerging as a critical constraint for tea plantations in the Dooars region of West Bengal, India, where irrigation largely relies on groundwater resources and conventional overhead sprinklers often lack precision and uniformity. This study employed remote sensing techniques in sprinkler-irrigated and drip-irrigated plots in the Dooars during the pre-monsoon and post-monsoon seasons over a three-year period (2018-2020) to determine how the two different irrigation systems (sprinkler and drip) influence tea canopy growth. Correlations between canopy cover and its influencing factors, i.e., normalized difference vegetation index (NDVI), leaf area index (LAI), soil moisture content, and land surface temperature (LST) were assessed. Results showed that the mean NDVI increased by 11.14% in the pre-monsoon season and 6.17% in the post-monsoon season. These changes in the mean NDVI in the drip-irrigated plot indicated higher tea canopy growth due to adequate water availability in the root zone. The values of NDVI (0.47 to 0.55), LAI (2.79 to 3.14), and soil moisture (0.09 to 0.17 m3 m-3) were higher under drip irrigation system. Also, strong correlations among NDVI, LAI, LST and soil moisture parameters demonstrated that water availability in the root zone of the tea plantation under drip irrigation improved canopy growth driven by favorable soil-plant-water interactions. Therefore, drip irrigation outperformed sprinkler system in improving soil moisture retention and promoting tea canopy growth, making it a sustainable long-term solution for tea estates in the region.

Implementing fully on-demand irrigation in existing rotational networks often requires extensive and costly infrastructure rehabilitation, limiting its practical applicability in many irrigation systems. Therefore, identifying operational strategies capable of improving delivery flexibility without major structural modification remains a critical challenge. In this study, limited on-demand operation was evaluated as an intermediate operational strategy for two pressurized drip irrigation networks in Iran operating under rotational water distribution systems: the gravity-fed Ziviyeh network and the pump-supplied Lali network. Hydraulic performance under different operational scenarios was simulated using the COPAM modeling framework, while network flexibility was evaluated using the Delivery Flexibility Index (DFI). The results showed that neither network could reliably support fully on-demand operation under existing conditions because the minimum required hydrant pressure was satisfied in only 10% and 13% of operational combinations in the Ziviyeh and Lali networks, respectively. In addition, pressure-deficit conditions affected approximately 26% and 27% of hydrants in the Ziviyeh and Lali networks, respectively, under a 90% probability of occurrence. However, under limited on-demand operation, pressure deficits occurred in less than 2% of hydrants for DFI values up to 3 in the Ziviyeh network and 4.5 in the Lali network, while hydraulic reliability remained within acceptable limits. These findings demonstrate that DFI-based operational management can substantially improve delivery flexibility without requiring physical infrastructure upgrades. The proposed approach provides a practical and economically feasible transitional modernization strategy for pressurized irrigation networks operating under water-scarcity and financial constraints.

Magnetization of irrigation water has gained increasing attention in agriculture. Salinity stress markedly decreases caraway growth and productivity. This study aimed to determine the optimal irrigation approach using magnetic water technology for improving caraway genotype efficiency, yield, and irrigation water productivity (IWP). This investigation was conducted at the Wadi El-Natrun Research Station, under the auspices of the Water Management Research Institute, National Water Research Center, Egypt. This study included four treatments, using magnetic and non-magnetic water, applied under two different drip irrigation systems (surface and subsurface). The findings indicated that in the absence of magnetic treatment, EC values increased after irrigation at all soil depths. In contrast, the use of magnetized water consistently reduced irrigation requirements in both surface (SDI) and subsurface (SSDI) drip systems, with reductions of 619 and 681 m³/ha, respectively. Furthermore, magnetized water increased IWP by approximately 16% and 14% under SDI in the 1st and 2nd seasons, respectively, compared to non-magnetized treatments. SSDI with magnetized water also had a pronounced positive effect on overall caraway productivity per feddan, with average friut yield increasing by approximately 10.38% and essential oil yield rising by more than 24.56%. The benefit–cost ratio improved from 2.48 to 2.53 under SDI and from 2.54 to 2.62 under SSDI in the first season, highlighting increased economic efficiency. These results underscore the potential of advanced magnetic technologies and modern irrigation practices in enhancing caraway performance under saline stress. Future studies will assess different magnetic field strengths, optimal exposure time, and the best placement of the magnetization unit to maximize water use efficiency.

To deliver freshwater for drip irrigation, our study presents an optimal techno-economic based on a Water Pumping Photovoltaic System (WPPVS) that integrates a Hydrogen Energy Storage System (HySS) to ensure reliable freshwater for agricultural irrigation in remote arid regions. A critical operational challenge in WPPVS is mechanical vibration at low flow rates, which degrades the pump efficiency and lifespan. Our methodology directly addresses this issue by incorporating a vibration-avoidance strategy that ensures that the pump operates only within its stable and, efficient range. To reduce the loss of water supply probability and overall annual costs of the drip irrigation system, a multi-objective optimization framework using Multi-Objective Particle Swarm Optimization (MOPSO) and Gaussian Mixture Model (GMM) clustering to simultaneously minimize the Loss of Water Supply Probability (LWSP), and the system’s total life-cycle cost. The model’s practical applicability is demonstrated through a detailed techno-economic feasibility analysis for a tomato crop drip irrigation project in Sakaka, Saudi Arabia. Sensitivity analysis is performed on dynamic head, crop prices, and interest and inflation rates, confirming the robustness of the system against variable economic indicators. In comparison to 1071 h without HySS, the results revealed that the seasonal irradiation harvest hours are 1863, which represents 21% of the seasonal hours employing the developed hybrid energy storage coordination. This integrated approach provides a holistic and economically viable solution for designing reliable solar irrigation systems with long-term mechanical integrity.

Coastal reclaimed polders with shallow saline groundwater support intensive greenhouse horticulture but require timely diagnosis of root-zone water and salinity conditions. This study developed a compact Internet-of-Things (IoT) monitoring system based on the M5Stamp Pico microcontroller to acquire SDI-12 soil-sensor data, buffer records locally, and transfer them to a low-cost cloud dashboard. Outside-greenhouse validation showed high operational reliability, with a missing observation rate of only 0.9%, and acceptable agreement with a reference TDR100 for both volumetric water content (θ) and bulk electrical conductivity (ECb). The system was then applied to ridge-position monitoring in a commercial pepper greenhouse on a coastal reclaimed polder. The ridge records captured depth-dependent infiltration and salinity redistribution under drip irrigation, together with contrasting responses between the cultivated layer and shallow groundwater. Potential-based interpretation indicated that the monitored ridge root zone was often not strongly limited by matric potential, whereas osmotic potential derived from pore-water salinity showed reduced water availability even when the soil remained relatively wet. These results demonstrate that continuous real-time monitoring at the ridge position can support diagnosis of root-zone stress and provide useful information for irrigation and fertigation management in salt-affected greenhouse soils.

ABSTRACT Enhancing sustainability in intensive vegetable production systems, such as raised-bed plasticulture with drip irrigation, requires precise nitrogen (N) management to balance productivity with environmental stewardship. Field experiments and 15N tracer studies demonstrated that conventional fertilizer practices in sandy soils were often associated with low recovery of applied N, indicating substantial inefficiencies when application rates and timing exceeded crop demand. Aligning N inputs more closely with crop requirements maintained adequate plant nutrition and favorable soil C:N ratios but did not result in measurable increases in soil organic matter, highlighting the need for complementary soil management practices in systems with inherently low organic carbon. To improve synchronization between N availability and crop uptake, controlled-release fertilizers were evaluated as alternatives to split-applied soluble urea. When applied at rates aligned with crop N requirements, controlled-release fertilizers improved nitrogen use efficiency, reduced labor requirements, and supported yield stability, particularly under warm-season production conditions characterized by rapid soil N turnover and elevated irrigation demand. Economic analyses indicated that, despite higher upfront fertilizer costs, controlled-release fertilizers improved net returns through labor savings and more consistent marketable yields. Collectively, these results support a nutrient management framework that integrates optimized fertilizer rates, improved fertilizer technologies, and complementary practices such as cover cropping. This approach offers a practical pathway for improving agronomic efficiency and economic viability while reducing the risk of N losses, and provides field-based evidence to inform extension, policy, and nutrient management programs focused on sustainable vegetable production.

Background and Aim: Guava (Psidium guajava L.), often referred to as the ‘Apple of Tropics,’ is a vital fruit crop in tropical and sub-tropical regions worldwide. This study focused on a sub-mountainous, undulating terrain with high cultivation costs and no permanent water sources, aiming to optimize fertilizer efficiency, enhance fruit yield and quality, and conserve water for future generations. Drip irrigation recognized as effective method for delivering water and nutrients, results in reduced water usage while, improving fruit quality. The research investigated the effects of fertigation on the phenological and physico-chemical responses of guava cv. Allahabad Safeda in the lower Shiwalik belt of Punjab. Study Design: The experimental trial utilized a simple randomized block design with ten different treatments replicated thrice. Place and Duration of Study: The research was conducted at Fruit Research Fram, Dr D R Bhumbla Regional Research Station, Ballowal Saunkhri, Balachaur, SBS Nagar, Punjab. The trial was conducted for duration of nine months. Methodology: The experiment comprised of 10 different treatment viz. T1 - I1F1 (100% of PE + 100% RDF), T2 – I1F2 (100% of PE + 75% RDF), T3 – I1F3 (100% of PE + 50% RDF), T4 – I2F1 (80% of PE + 100% RDF), T5 - I2F2 (80% of PE + 75% RDF), T6 - I2F3 (80% of PE + 50% RDF), T7 – I3F1 (60% of PE + 100% RDF), T8 - I3F2 (60% of PE + 75% RDF), T9 - I3F3 (60% of PE + 50% RDF) and T0 - control (no fertigation) and replicated thrice. The data were recorded and analyzed as per standard procedures. Results: The results showed significant improvements in phenological traits viz., date of initiation & period of vegetative bud emergence, date of initiation & period of flower bud initiation, date of initiation & period of peak flowering, date of initiation & period of fruit set; and date of initiation & period of fruit maturity. Additionally, the fruit's physico-chemical properties were also enhanced, yielding higher Vitamin C and pectin content, along with lower titratable acidity. Conclusion: This work underscores the importance of efficient water and nutrient management for sustainable guava production and improved nutritional security in agriculturally challenged areas.

Subsurface drip irrigation (SDI) is an efficient irrigation method widely used in arid and semi-arid regions; however, its effectiveness largely depends on soil physical properties and the resulting soil water distribution. This study investigated soil wetting pattern dynamics under SDI and developed empirical models to predict wetted soil geometry as influenced by emitter discharge, installation depth, irrigation time, soil texture, and bulk density. Laboratory experiments were conducted using two representative soils from the Kurdistan Region of Iraq (Semel—silty clay and Zakho—clay loam). Emitters with discharge rates of 2 and 4 L h⁻¹ were installed at depths of 12.5, 25, and 37.5 cm, and equal water volumes (8 L) were applied to monitor the advancement of the wetting front. Nonlinear regression models were developed to estimate maximum horizontal wetted diameter (H) and average vertical wetted depth (V) as functions of emitter discharge (q), irrigation time (t), clay content (c), and bulk density (ρb). The models showed strong predictive performance, with coefficients of determination (R²) ranging from 0.87 to 0.98. Model validation indicated acceptable accuracy, with root mean square error (RMSE) values of 1.676–5.033 cm, mean absolute error (MAE) of 4.531–10.745 cm, and mean absolute percentage error (MAPE) of 5.468–10.613%. The index of agreement (d) ranged from 0.968 to 0.995, while mean bias error (MBE) values were close to zero, indicating minimal systematic error. The results demonstrated that wetting front expansion was primarily governed by irrigation time, whereas emitter discharge had a comparatively smaller influence, particularly at shallow depths. Increased clay content reduced both horizontal and vertical wetting dimensions, while the effect of bulk density varied with emitter depth. Lower discharge applied over longer durations enhanced lateral water movement, whereas higher discharge promoted vertical flow and deep percolation. The developed models provide practical tools for predicting soil water distribution and can support the optimization of emitter spacing, irrigation scheduling, and water-use efficiency in SDI systems under semi-arid conditions.

Abstract Upland cotton ( Gossypium hirsutum L.) production in the Samarkand province is dependent on irrigation. Although reduced irrigation requirements under drip compared with furrow irrigation can partly address water scarcity problems in the region, cotton fertilizer requirements likely vary in response to irrigation method. In a 3‐year field study, we examined the yield response of upland cotton to furrow and drip irrigation under conventional on‐farm and improved nutrient (nitrogen, phosphorus, and potassium) split application methods at two rates: 150, 105, and 75 kg ha −1 and 200, 140, and 100 kg ha −1 of N, P, and K, respectively. Irrigation method significantly influenced seed cotton yield in 2 years ( p ≤ 0.039), with drip irrigation having greater seed cotton yields in all 3 years. Drip irrigation water productivity was 74% greater than furrow irrigation and saved an average of 3000 m 3 ha −1 year −1 . Improved fertilizer application methods significantly increased yield in all study years ( p ≤ 0.013) with a greater yield response to application method under drip (0.69 t ha −1 ) compared with furrow (0.29 t ha −1 ) irrigation. Improved fertilizer application methods also significantly increased first harvest boll weights and 1000‐seed weights. Seed cotton yield significantly responded to the high fertilizer rate ( p ≤ 0.012) in two of the study years. Optimal fertilizer strategies varied with irrigation method, with potentially lower requirements under drip irrigation compared with furrow irrigation. Use of drip irrigation may offer a way to not only reduce irrigation requirements but also nutrient inputs for cotton production in the Samarkand region.

Water stress and scarcity are turning into major obstacles to sustainable agricultural production, especially in arid and semiarid areas. Therefore, this study aimed to investigate the effects of three different irrigation levels, two irrigation techniques, and three buried lateral depths. The three irrigation levels were as follows: full irrigation, I100, comprising 100% crop evapotranspiration (ETc) and two stress irrigation levels, I80 and I60, comprising 80% ETc and 60% ETc). The two irrigation techniques were partial root zone drying (PRD) and conventional single lateral (CSL) drip irrigation. The three buried lateral depths were 0 cm [surface drip irrigation (SDI)] and 15 cm and 30 cm [subsurface drip irrigation (SSDI)]. The effects on the growth and physiological parameters, productivity of potatoes ( Solanum tuberosum L. cv. Spunta), and water use efficiency were evaluated. The findings indicated that irrigation treatment I100 applied under PRD and SSDI with a buried lateral depth of 15 cm produced the maximum mean values for potato yield, growth parameters (including plant height, stem diameter, number of branches per plant, leaf area, and dry weight), and physiological parameters (such as relative water content, membrane stability index, and relative chlorophyll concentration). The mean values of potato yield decreased when irrigation deficit treatments increased from I100 to I80 and I60. In contrast, irrigation water use efficiency of the I60 treatment was higher than that of the I80 and I100 treatments by 5.74% and 20.24%, respectively. The application of PRD resulted in higher potato yield values for irrigation treatments I100, I80, and I60. When irrigation water was abundant, the full irrigation treatment (I100) and PRD irrigation under SSDI with a buried lateral depth of 15 cm may be recommended to optimize potato crop production. Under water scarcity, applying the RDI treatment (I80) and PRD irrigation under SSDI with a buried lateral depth of 15 cm will conserve 20% of the irrigation water applied with minimal reduction in potato crop production.

Optimizing drip irrigation and organic fertilizer management across diverse environments: Global patterns of nitrogen-driven production efficiency