Irrigation Water Use Efficiency Research Articles

Simulating the exploration of the optimal irrigation of spring wheat in drought areas based on SWAP model

AbstractWater scarcity and low irrigation efficiency are the main factors causing yield losses in spring wheat in arid areas. To propose optimised irrigation scheduling for spring wheat in the arid areas of Ningxia, China, we first calibrated the SWAP (soil–water–atmosphere–plant) model and then utilised the well‐tested SWAP model during three typical rainfall years to evaluate the 542 irrigation schemes. The results showed that the model performed well in simulating the plant height, leaf area index (LAI) and biomass of spring wheat under different water stress conditions. The R2 values of the above three crop growth indicators were all greater than 0.89, and the normalised root mean square error (NRMSE) was less than 18% in the validation period. Additionally, the model achieved a high degree of accuracy in simulating the soil water content, evapotranspiration and yield, with RMSEs of 2%, 31 mm, and 326 kg/ha, respectively. The total irrigation amounts of 290, 320 and 350 mm with five, six and six irrigation times in the wet, average, and dry years, respectively, could achieve relatively high yields as well as improved water use efficiency (WUE) and irrigation water use efficiency (IWUE). The results can provide useful information for the efficient utilisation of irrigation water resources in arid areas.

Optimization of water and nitrogen management in wheat cultivation affected by biochar application − Insights into resource utilization and economic benefits

In the context of global climate change and natural resource scarcity, agricultural production is facing multiple challenges in improving crop yields and optimizing natural resource use. It is of great practical significance to optimize agricultural practices to achieve sustainable agricultural development. In this study, a two-year winter wheat field experiment was conducted in the Guanzhong Plain, Shaanxi, China, from 2020 to 2022 to assess the effects of biochar, irrigation, and N fertilizer rates on the yield, water-nitrogen use efficiency, and economic benefits of winter wheat. Specifically, biochar was applied to winter wheat at 30 t ha−1 in combination with two irrigation application rates, including regular irrigation (I100; actual evapotranspiration) and deficit irrigation (I80; 0.8 actual evapotranspiration), and three different N fertilizer rates at 210 (NH; conventional applied N rate by local farmers), 160 (NM; moderate N rate), and 110 kg ha−1 (NL; low N rate). The control groups in this study consisted of experimental plots under the NM and N0 (no N) without biochar application. The aboveground dry matter mass (ADM), yield, and net ecosystem economic budget (NEEB) of winter wheat showed increasing trends with increasing N application rates without significant differences between the NH and NM treatments. On the other hand, the water use efficiency (WUE), agronomic N fertilizer use efficiency (aNUE), and N fertilizer recovery efficiency (NRE) showed increasing-decreasing trends with increasing N fertilizer rates, reaching the highest values under the NM treatment scenario. The biochar addition significantly increased the winter wheat yield and WUE (P<0.05). On the other hand, the I80 treatment resulted in higher WUE and irrigation water use efficiency (IWUE) than those under I100 by 5.63 and 13.52 %, respectively. TOPSIS results indicated that the combined I80B1NM treatment was the optimal winter wheat management practice, maintaining high productivity while improving resource use efficiency and economic benefits. The results of the present study provide an important scientific basis and guidance for ensuring efficient and high-quality agricultural products in the Guanzhong Plain and other regions in China with similar climatic characteristics.

ReLU surrogates in mixed-integer MPC for irrigation scheduling

Efficient water management in agriculture is important for mitigating the growing freshwater scarcity crisis. Mixed-integer Model Predictive Control (MPC) has emerged as an effective approach for addressing the complex scheduling problems in agricultural irrigation. However, the computational complexity of mixed-integer MPC still poses a significant challenge, particularly in large-scale applications. This study proposes an approach to enhance the computational efficiency of mixed-integer MPC-based irrigation schedulers by employing Rectified Linear Unit (ReLU) surrogate models to describe the soil moisture dynamics of the agricultural field. By leveraging the mixed-integer linear representation of the ReLU operator, the proposed approach transforms the mixed-integer MPC-based scheduler with a quadratic cost function into a mixed-integer quadratic program, which is the simplest class of mixed-integer nonlinear programming problems that can be efficiently solved using global optimization solvers. The effectiveness of this approach is demonstrated through comparative studies conducted on a large-scale agricultural field across two growing seasons, involving other machine learning surrogate models, specifically Long Short-Term Memory (LSTM) networks, and the triggered irrigation scheduling method. The ReLU-based approach significantly reduces solution times—by up to 99.5%—while achieving comparable performance to the LSTM approach in terms of water savings and Irrigation Water Use Efficiency (IWUE). Moreover, the ReLU-based approach achieves enhanced performance in terms of irrigation water savings and IWUE compared to the triggered approach.

Plant stress index (PSI) based irrigation scheduling of wheat in Punjab, India

A field experiment was caried out over a period of two years (2022-23 and 2023-24) at Lovely Professional University, Phagwara, Punjab with eight irrigation treatments (based on PSI, soil moisture depletion &amp; critical growth stages) and four replications in RBD Design. The different irrigation levels had an impact on plant growth, parameters contributing to yield, grain and straw production, as well as irrigation water use efficiency (IWUE). Among all the PSI based irrigation treatments, schedule irrigation at 0.50 PSI was found the best irrigation level for growing wheat with significant grain yield (5.67 t ha-1), IWUE (0.092 t ha-1 cm) and gave 11.16% water saving over I50% FC (irrigation as per farmer practices). To schedule irrigation as per the soil moisture depletion approach, irrigation levels I50% FC and I75% FC result in maximum grain yield over PSI &amp; critical growth stage-based irrigation treatments, but this practice does not support sustainable wheat production in water-scarce regions. Therefore, irrigation can be tailored for wheat crops based on 0.5 PSI in water-scarce and water-abundant regions of Punjab.

Efficiency of Irrigation Water Use in Egyptian Agricultural Production

Efficiency of Irrigation Water Use in Egyptian Agricultural Production

Impact of Irrigation Management Decisions on the Water Footprint of Processing Tomatoes in Southern Spain

The water footprint is an increasingly demanded environmental sustainability indicator for certifications and labels in agricultural production. Processing tomatoes are highly water-intensive, and existing studies on water footprint have uncertainties and do not consider the impact of different irrigation configurations (e.g., surface drip irrigation (SDI) and subsurface drip irrigation (SSDI)) and irrigation strategies. This study presents a two-year experimental investigation to determine the water footprint of processing tomatoes grown in southern Spain (Andalusia) and the impact of SSDI and deficit irrigation. Five irrigation treatments were established: SDI1 (surface drip irrigation without water limitation), SDI2 (surface drip irrigation without water limitation adjusted by soil moisture readings), SSDI1 (subsurface drip irrigation without water limitation and a dripline depth of 15 cm), SSDI2 (similar to SSDI1 but with mild/moderate water deficit during the fruit ripening stage), and SSDI3 (subsurface drip irrigation without water limitation and a dripline depth of 35 cm (first year) and 25 cm (second year)). Measurements included crop vegetative growth, leaf water potential, leaf gas exchange, nitrate concentration in soil solution, and crop yield and quality. The soil water balance components (actual evaporation, actual transpiration, deep drainage), necessary for determining the total crop water footprint, were simulated on a daily scale using Hydrus 2D software. Results indicated that SSDI makes more efficient use of irrigation water than SDI. The water footprint of SSDI1 was 20–35% lower than that of SDI1. SSDI2 showed similar water footprint values to SDI1 under highly demanding environmental conditions and significantly lower values (≈40%) in a year with lower evaporative demand. The dripline depth in SSDI was critical to the water footprint. With a 35 cm installation depth, SSDI3 had a significantly higher water footprint than the other treatments, while the values were similar to SSDI1 when the depth was reduced to 25 cm.

Deficit Irrigation as an Effective Way to Increase Potato Water Use Efficiency in Northern China: A Meta-Analysis

Water scarcity poses a significant threat to the sustainable production of crops in Northern China. Despite this, the effect of water management practices, such as deficit irrigation, on the yield and WUE of potatoes has been rarely explored. Based on the meta-analysis of field experiment data, this study evaluated the influence of deficit irrigation on potato yield, evapotranspiration (ET), water use efficiency (WUE) and irrigation water use efficiency (IWUE) under variable soil types, water-saving ratio, irrigation methods, soil organic carbon (SOC) content, and fertilizer rate in Northern China. Here, we determined that potato WUE and IWUE were significantly increased by 10.0 and 31.6%, respectively, under deficit irrigation, while ET was significantly decreased by 26.3% compared to full irrigation. Conclusively, deficit irrigation significantly reduced potato yields by 16.4% compared to full irrigation. Furthermore, SOC content played a vital role in improving the WUE and alleviating potato yield losses under deficit irrigation. Our study suggested that maximum WUE with lower potato yield losses under deficit irrigation can be achieved in the Central Plains region of China or in yellow loam soil, brown soil, and meadow soil under alternate root-zone irrigation when the water-saving ratio was less than 45% and fertilizer application rates were 300 kg N ha−1, &gt;240 kg P2O5 ha−1, and 181–300 kg K2O ha−1. Overall, these findings highlight the need for a comprehensive understanding of various agricultural management practices and local environmental conditions to optimize the benefits of deficit irrigation in potato-growing regions across Northern China.

Dry Matter Accumulation, Water Productivity and Quality of Potato in Response to Regulated Deficit Irrigation in a Desert Oasis Region.

As one of the most important food crops, the potato is widely planted in the oasis agricultural region of Northwest China. To ascertain the impact of regulated deficit irrigation (RDI) on various facets including dry matter accumulation, tuber yield, quality and water use efficiency (WUE) of potato plants, a two-growth season field experiment under mulched drip irrigation was conducted in the desert oasis region of Northwest China. Water deficits, applied at the seedling, tuber formation, tuber expansion and starch accumulation stages, encompassed two distinctive levels: mild (55-65% of field capacity, FC) and moderate (45-55% FC) deficit, with full irrigation (65-75% FC) throughout the growing season as the control (CK). The results showed that water deficit significantly reduced (p < 0.05) above-ground dry matter, water consumption and tuber yield compared to CK, and the reduction increased with the increasing water deficit. A mild water deficit at the tuber formation stage, without significantly reducing (p > 0.05) yield, could significantly increase WUE and irrigation water use efficiency (IWUE), with two-year average increases of 25.55% and 32.33%, respectively, compared to CK. Water deficit at the tuber formation stage increased starch content, whereas water deficit at tuber expansion stage significantly reduced starch, protein and reducing sugar content. Additionally, a comprehensive evaluation showed that a mild water deficit at the tuber formation stage is the optimal RDI strategy for potato production, providing a good balance between yield, quality and WUE. The results of this study can provide theoretical support for efficient and sustainable potato production in the desert oasis regions of Northwest China.

Water and fertilizer decision model for synergistic optimization of yield, quality and efficiency of cherry tomato based on combination evaluation

The scientific nutrient supply under deficit irrigation can ensure the yield and quality of crops, and balance water and fertilizer benefits. The model of the combination of water and fertilizer was constructed based on the analysis of the effects of irrigation, K2O and MgO application on yield, quality and water and fertilizer use efficiency of cherry tomato over two growing seasons. Deficit irrigation contributed to quality accumulation, while full irrigation resulted in higher yields. The optimal irrigation water use efficiency (IWUE) was attained with a moderate level of potassium and magnesium. An evaluation system of cherry tomato was established containing totally 6 indicators from 3 categories of yield, quality and efficiency based on correlation analysis, and yield obtained the highest weight of 0.402 and 0.373 in the two study seasons, respectively. The overall differential combination model was adopted to comprehensively evaluated combination of water and fertilizer factors by integrating three single models of TOPSIS, Membership function analysis and Grey relational analysis, and the correlation coefficient of any two single model was greater than 0.614. The response of comprehensive score for cherry tomato to each single factor of irrigation, K2O and MgO followed a downward-opening parabola. The analytical model revealed that the coupling of potassium and magnesium has a mutually reinforcing effect when they were both at medium level, while an inhibitory effect was observed at higher or lower level. The model verification showed that 7 out of the total 10 indicators reached more than 80 % of maximum value of the corresponding single indicator under the condition of the water and fertilizer with highest comprehensive score. Considering yield, quality and efficiency, the optimal combination of irrigation, K2O, and MgO was 80.6 ∼ 83.2 % Evaporation (Ep), 161.40 ∼ 171.27 kg/ha, and 19.59 ∼ 20.17 kg/ha in 2021S. The corresponding combination for 2021F was 75.4 ∼ 77.9 % Ep, 133.41 ∼ 140.45 kg/ha, and 13.99 ∼ 14.80 kg/ha. This strategy can maintain yield, improve quality, save irrigation amount, and increase fertilizer efficiency, which guides the production of deficient irrigation in northwest China.

Scheduling irrigation events in corn using three soil water potential strategies

AbstractScheduling irrigation events is important for high corn (Zea mays L.) yield, water use efficiency, economic returns, and water conservation. The use of shallow subsurface drip irrigation (S3DI) is cost effective for small irregular shaped field areas. Currently there are no irrigation scheduling recommendations for S3DI systems for corn production. The objective was to evaluate three water potential value strategies for scheduling irrigation events and the effect on corn yield, test weight, irrigation water use efficiency (IWUE), and value water use efficiency (VWUE). Corn was grown multiple years (2012–2013; 2019–2023) at two locations (Dawson and Shellman, GA) using soil water potential sensors to schedule irrigation events. Sensors were installed at 10 and 20 inches (25 and 50 cm) soil depth. Irrigation events were scheduled when the average water potential was between 40 to 60 cbar (I1), 60 to 80 cbar (I2), 80 to 100 cbar (I3), and compared to a dryland control (I0). There was no difference in corn yield, IWUE, or VWUE between irrigation treatments, but all irrigation treatments had greater yield than I0, except in high rainfall years. At the Shellman location, total water applied for I3 was 46% less than for I1. At Dawson, I2 applied 17% more water than either I1 or I3. Across both sites, I1 and I2 applied 1.5 and 1.3 times more water than I3, respectively. Therefore, irrigation events scheduled at 80 to 100 cbar can be a viable technique for irrigating corn using S3DI without yield reductions while promoting water conservation.

Artificial Neural Network Modeling for Investigation on the Effect of Deficit Irrigation and Nitrogen Levels on Yield and Quality of Hay Remaining After Seed Harvest of Sorghum Sudangrass Hybrid

ABSTRACT This study aims to develop an Artificial Neural Network (ANN) modeling to be trained to forecast the effects of different irrigation water levels and fertilizer doses on the hay yield and some quality traits of herbal parts of Sorghum × Sudan grass hybrid (Sorghum sudanense vs. Sorghum bicolor). The ANN model was developed on the limited field experiments implemented in Bilecik, Turkey, for 2 years in 2021 and 2022. Experiments were conducted in split-plot design with three replications. In the study, three irrigation levels (I100, I60, and I30) were placed in the main parcels, and four fertilizer levels (N0, N50, N100 and N150 kg ha−1) were placed in the sub-parcels. Irrigations were made in three critical periods according to the amount of cumulative evaporation occurring in the Class A Pan. The results showed that irrigation and fertilization are important in terms of yield and quality characteristics. The yield increased depending on the irrigation and fertilization dose, and the highest value was obtained from the I100 × N150 interaction (28.10 t ha−1). The highest protein yield was determined from the I60 × N150 (2.37 t ha−1) interaction, and the Relative Feed Value (RFV) value was determined from the I30 × N150 (92.17) interaction. Irrigation Water Use Efficiency (IWUE) and Water Use Efficiency (WUE) values increased with decreasing irrigation amount, and the highest IWUE was determined from I30 and the highest WUE was determined from I60 irrigation subjects. According to the field experiments and ANN model, the I80 irrigation with 100 kg ha−1 nitrogen doses would suit the feed yield and quality of Sorghum × Sudan grass hybrid.

Efficiency of irrigation water use for maize crops in Salah El-Din Governorate / Al-Dour District

Efficiency of irrigation water use for maize crops in Salah El-Din Governorate / Al-Dour District

Evaluasi Kapasitas Jaringan Irigasi Lanrae Pada Kebutuhan Air Sawah di Kabupaten Barru

Irrigation is an infrastructure to increase land productivity and increase the intensity of annual harvests, the availability of adequately controlled irrigation water is an input to increase crop production. The Lanrae irrigation area which has 1400 Ha of agricultural rice fields that need water, Lanrae is one of the areas located in Nepo Village, Mallusetasi District, Barru Regency. This research aims to meet the needs of irrigation water for farmers who usually experience crop failure due to lack of irrigation water and to increase the potential of existing agricultural products in the Lanrae area in particular and in Barru Regency in general as well as to overcome complaints from farmer groups who experience a lack of water to increase yields. harvest. This research was conducted in the Lanrae Area, Mallusetasi District, Barru Regency, which was carried out from January to March 2017 using quantitative methods. The results of the research on weirs and irrigation in the Lanrae area of Barru Regency showed that the availability of water in the Lanrae river is currently still sufficient to meet the needs for irrigation water in the Lanrae irrigation area and the utilization of irrigation networks for irrigation water services is not optimal and the efficiency of irrigation water use is very low. As well as the use of irrigation water in the upstream areas tends to be excessive and the use of irrigation water in the middle and even downstream areas is very short of water.

Silicon drip fertigation improved sugar beet root and canopy growth and alleviated water deficit stress in arid areas

Crop growth is highly susceptible to drought stress due to water scarcity in arid areas. Silicon (Si) fertilizer could improve the tolerance of crops to drought stress, but the effect of drip fertigation of Si fertilizer on the growth and yield of sugar beets under drought stress is still unclear. In this field experiment conducted in 2022 and 2023 in the arid northwest China, the effects of different Si fertilizer application rates (0 kg ha−1 (Si0), 15 kg ha−1 (Si1), 38 kg ha−1 (Si2), 75 kg ha−1 (Si3)) on the growth, yield, and resource use efficiency of sugar beets (cultivars Beta356 (BT) and Strube13092 (ST)) under deficit irrigation (60 % of crop evapotranspiration (ETc), W2) were explored. The results showed that deficit irrigation (W2Si0) reduced the taproot and fibrous root growth, leaf net photosynthetic rate (Pn), leaf relative water content (LRWC), and leaf area index (LAI) of cultivar BT compared with full irrigation (100 % of ETc, W1). Under deficit irrigation, Si application (W2Si1, W2Si2, and W2Si3) alleviated the drought stress by increasing the number of fibrous roots in 17.5–70.0 cm soil layer and promoted the growth of taproots. Besides, it also increased the leaf moisture and photoassimilate production by increasing plant Si uptake, LRWC, LAI, and Pn. This finally increased the taproot yield (TY), irrigation water use efficiency (IWUE), and partial factor productivity of nitrogen (PFPN) by 11.2 % - 22.9 %, 6.5 % - 19.3 %, and 6.3 % - 19.3 %, respectively in cultivar BT and by 8.8 % - 27.1 %, 13.4 % - 30.8 %, and 13.4 % - 30.8 %, respectively in cultivar ST, compared with W2Si0. Regression analysis showed that the Si fertilizer application rate 64 kg ha−1 could maximize the TY of cultivar BT, but the net revenue (NR) was significantly lower than that of the W1 treatment. The Si fertilizer application rate 71 kg ha−1 could increase the TY of cultivar ST and achieve a NR similar to that of the W1 treatment. Therefore, in arid regions, Si application could alleviate the adverse effects of drought stress on drip-irrigated sugar beet root and shoot growth and improve yield, but the Si application rate varied with sugar beet cultivars.

Synergistic Effects of Soil-Based Irrigation and Manure Substitution for Partial Chemical Fertilizer on Potato Productivity and Profitability in Semiarid Northern China.

Soil-based irrigation and the partial substitution of chemical fertilizers with manure are promising practices to improve water and nitrogen (N) use efficiency. We hypothesize that their combination would simultaneously benefit potato production, tuber quality and profitability. A two-year experiment was conducted in semiarid northern China to investigate the combined effects of three water treatments [rainfed (W0), soil-based irrigation (W1), conventional irrigation (W2)] and three N treatments [no N (N0), chemical N (N1), 25% manure substitution (N2)] on these indicators, and to perform a comprehensive evaluation and correlation analysis. The results showed that water and N treatments separately affected all indicators except vitamin C content. Compared to W2, W1 significantly increased water productivity by 12% and irrigation water use efficiency (IWUE) by 30% due to 10% lower evapotranspiration and 21% lower water use. However, W1 and W2 negatively affected crude protein content. Conversely, this was compensated by the combination with N1 and N2. There were slight differences between N1 and N2 for all indicators on average across water treatments, while under W1, N2 significantly increased leaf area index (LAI) and N recovery efficiency (REN) by 18% and 29.4%, respectively, over N1. Also, comprehensive evaluations showed that W1N2 performed best, with the highest tuber yield, profit and acceptable quality. This can be explained by the increase in LAI, IWUE and REN due to the positive correlations with tuber yield and net return. Consequently, soil-based irrigation combined with 25% manure substitution had complementary effects on tuber quality and synergistic effects on potato productivity and profitability.

Enhancing Wheat Growth, Physiology, Yield, and Water Use Efficiency under Deficit Irrigation by Integrating Foliar Application of Salicylic Acid and Nutrients at Critical Growth Stages.

Transitioning from full to deficit irrigation (DI) has become a key strategy in arid regions to combat water scarcity and enhance irrigation water use efficiency (IWUE). However, implementing DI requires additional approaches to counter its negative effects on wheat production. One effective approach is the foliar application of salicylic acid (SA), micronutrients (Mic; zinc and manganese), and macronutrients (Mac; nitrogen, phosphorus, and potassium). However, there is a lack of knowledge on the optimal combinations and timing of foliar application for these components to maximize their benefits under arid conditions, which is the primary focus of this study. A two-year field study was conducted to assess the impact of the foliar application of SA alone and in combination with Mic (SA + Mic) or Mic and Mac (SA + Mic + Mac) at various critical growth stages on wheat growth, physiology, productivity, and IWUE under DI conditions. Our result demonstrated that the foliar application of different components, the timing of application, and their interaction had significant effects on all investigated wheat parameters with few exceptions. Applying different components through foliar application at multiple growth stages, such as tillering and heading or tillering, heading, and grain filling, led to significant enhancements in various wheat parameters. The improvements ranged from 7.7% to 23.2% for growth parameters, 8.7% to 24.0% for physiological traits, 1.4% to 21.0% for yield and yield components, and 14.8% to 19.0% for IWUE compared to applying the components only at the tillering stage. Plants treated with different components (SA, Mic, Mac) exhibited enhanced growth, production, and IWUE in wheat compared to untreated plants. The most effective treatment was SA + Mic, followed by SA alone and SA + Mic + Mac. The foliar application of SA, SA + Mic, and SA + Mic + Mac improved growth parameters by 1.2-50.8%, 2.7-54.6%, and 2.5-43.9%, respectively. Yield parameters were also enhanced by 1.3-33.0%, 2.4-37.2%, and 3.0-26.6% while IWUE increased by 28.6%, 33.0%, and 18.5% compared to untreated plants. A heatmap analysis revealed that the foliar application of SA + Mic at multiple growth stages resulted in the highest values for all parameters, followed by SA alone and SA + Mic + Mac applications at multiple growth stages. The lowest values were observed in untreated plants and with the foliar application of different components only at the tillering stage. Thus, this study suggested that the foliar application of SA + Mic at various growth stages can help sustain wheat production in arid regions with limited water resources.

Automatic Irrigation System Based on Computer Vision and an Artificial Intelligence Technique Using Raspberry Pi

Efficient irrigation water use directly affects crop productivity as demand increases for various agricultural products due to population growth worldwide. While technologies are being developed in various fields, it has become desirable to develop automatic irrigation systems to reduce the waste of water caused by traditional irrigation processes. This paper presents a novel approach to an automated irrigation system based on a non-contact computer vision system to enhance the irrigation process and reduce the need for human intervention. The proposed system is based on a stand-alone Raspberry Pi camera imaging system mounted at an agricultural research facility which monitors changes in soil color by capturing images sequentially and processing captured images with no involvement from the facility’s staff. Two types of soil samples (sand soil and peat moss soil) were utilized in this study under three different scenarios, including dusty, sunny, and cloudy conditions of wet soil and dry soil, to take control of irrigation decisions. A relay, pump, and power bank were used to achieve the stability of the power source and supply it with regular power to avoid the interruption of electricity.

Improving Irrigation Management of Cotton with Small Unmanned Aerial Vehicle (UAV) in Texas High Plains

The rapid decline in water availability for irrigation on the Texas High Plains (THP) is a significant problem affecting crop production and the viability of a large regional economy worth approximately USD 7 billion annually. This region is the largest continuous cotton-producing area in the United States, and the timely delivery and efficient use of irrigation water are critical to the sustainability and profitability of cotton production in this region. Current irrigation scheduling must be improved to reduce water consumption without compromising crop production. Presently, irrigation scheduling based on reference evapotranspiration (ETo) is limited due to the lack of reliable and readily available in-field weather data and updated crop coefficients. Additionally, in-field variability in crop water demand is often overlooked, leading to lower irrigation efficiency. To address these challenges, we explored the potential use of an unmanned aerial vehicle (UAV)-based crop monitoring system to support irrigation management decisions. This study was conducted in Lubbock, Texas, in 2022, where high temporal and spatial resolution images were acquired using a UAV from a cotton field experiment with four irrigation levels. Soil moisture and canopy temperature sensors were deployed to monitor crop response to irrigation and rainfall. The results indicated a significant effect of water stress on crop growth (revealed by UAV-based canopy cover (CC) measurements), yield, and fiber quality. Strong correlations between multi-temporal CC and lint yield (R2 = 0.68 to 0.88) emphasized a clear trend: rainfed treatments with lower yields exhibited reduced CC, while irrigated plots with higher CC displayed increased yields. Furthermore, irrigated plots produced more mature and uniform fibers. This study also explored various evapotranspiration calculation approaches indicating that site-specific CC measurements obtained from a UAV could significantly reduce irrigation application. A regression model linking evapotranspiration to canopy cover demonstrated promising potential for estimating water demand in crops with an R2 as high as 0.68. The findings highlight the efficacy of UAV-based canopy features in assessing drought effects and managing irrigation water in water-limited production regions like the THP.

Productivity and energy-efficiency indices for diversified rice (Oryza sativa) based cropping systems in West Central Table Land Zone of Odisha

A long-term field experiment was conducted at Chiplima, Odisha, under irrigated medium land condition during 2006–07 to 2012–13, to evaluate the production potential and economics of 10 rice (Oryza sativa L.)-based crop ping systems. Rice–maize (Zea mays L.)–cowpea [Vigna unguiculata (L.) Walp.] and rice–groundnut (Arachis hypogaea L.)–bottle gourd [Lagenaria siceraria (Molina) Standl.] cropping systems recorded significantly higher average rice equivalent yield (19.55 and 18.57 t/ha, respectively) than the other systems evaluated, the relative production efficiency being 85.8 and 76.5% over the rice–groundnut system. Rice-based 3-cropping systems hav ing groundnut as winter (rabi) crop had higher land-use efficiency (83%). Rice–maize–cowpea recorded the high est irrigation water-use efficiency (230 kg REY/ha), whereas rice–groundnut–bottle gourd recorded the highest ap parent nutrient use efficiency (60.8 kg REY/kg NPK applied). Rice–maize–cowpea also recorded the highest en ergy-use efficiency (5.89), energy-output efficiency (1,240 MJ/ha/day) and energy productivity (0.34 kg REY/MJ). Rice–maize–cowpea had the highest employment generation efficiency (124.7%), followed by rice–groundnut bottle gourd (120.5%) and rice–groundnut–cowpea (120.0%). Rice–maize–cowpea gave the highest net returns of 135,087/ha, followed by rice–groundnut–bottle gourd system ( 111,777/ha). Rice–maize–cowpea system showed the highest system profitability ( 370/ha/day) and crop profitability ( 500/ha/day). This system also gave the highest benefit: cost ratio (2.56), with highest relative production efficiency (85.8%) and relative economic effi ciency (168.5%) compared to rice–groundnut system.

Intelligent decision‐making for fertigation treatment of tomatoes cultivated in greenhouse: An experimental study

AbstractTo verify the effectiveness of the intelligent decision method for fertigation, an automatic control system for fertigation in greenhouses was designed, and three intelligent decision methods based on evapotranspiration (T1), soil moisture (T2) and accumulated temperature (T3) were tested. Intelligent decisions included monitoring meteorological information, automatically monitoring soil moisture, utilizing fertigation application systems and using automated control modules. The system was stable and accurately controlled according to the decision scheme. The results showed that the average errors of the automated control system for decision‐making and irrigation were 1.1 and 0.8%, respectively. The study findings serve as a reference for the integration of intelligent irrigation decision‐making and control systems and for further improving the efficiency of water and fertilizer utilized. Compared with those of the control, the three intelligent decision‐making methods increased the tomato yield by 8, 12 and 7%, respectively. In addition, the irrigation water and fertilizer levels decreased significantly compared with those in the control treatment. Although the accuracy of the soil water content (SWC) estimated based on ET and temperature in irrigation decision‐making is low, the general trend is consistent with practice. In addition, the irrigation water use efficiency (IWUE) and partial factor productivity of fertilizer (PFP) were significantly improved. Similarly, the IWUE in T1 was the highest (60 kg m⁻3), and the PFP in T3 was the highest (669 kg kg⁻¹).