Irrigation Management Strategies Research Articles

Maize response to different subsurface drip irrigation management strategies: Yield, production functions, basal and crop evapotranspiration

Grain yield, irrigation-yield production functions (IYPFs), evapotranspiration-yield production functions (ETYPFs), total soil water-yield production function (TSWYPF), crop evapotranspiration (ETc), and basal ET (ETb) response of subsurface drip-irrigated (SDI) maize were investigated under full irrigation treatment (FIT), 75 % FIT, 50 % FIT, and rainfed (RF). Yield response to irrigation differed significantly (P<0.05) between the treatments with FIT having the highest grain yield, followed by 75 % FIT, 50 % FIT, and RF in all growing seasons. There was a 14, 6, and 12 % yield reduction in 75 % FIT, 50 % FIT, and RF with respect to FIT, respectively. FIT had the highest ETc, followed by 75 % FIT, 50 % FIT, and RF. ETc reduction with 75 % FIT, 50 % FIT and RF with respect to FIT had similar reductions between the years. Under these experimental conditions, ETc of SDI-irrigated maize can be expected to be reduced by 5.2 % (25 mm), 13 % (65 mm), and 26 % (130 mm) with the limited irrigation (75 % FIT and 50 % FIT) and RF, respectively. The amount of irrigation water required for maximum grain yield varied between the growing seasons as a function of climatic conditions (262, 225, and 173 mm in 2004, 2005, and 2006, respectively). Based on the IYPFs, a 25.4 mm of irrigation application resulted in 0.061, 0.063, and 0.066 t/ha yield increase (beyond the intercept) in 2004, 2005, and 2006, respectively, with a 3-yr average of 0.063 t/ha. A 25.4 mm of irrigation application resulted in 15.6, 16.0, and 13.7 mm of increase in ETc (beyond the intercept) in 2004, 2005, and 2006 seasons, respectively, with a 3-yr average of 15.1 mm. On a three-year average basis, 10.7, 29.1, and 67 % yield reduction in 75 % FIT, 50 % FIT, and RF treatments with respect to FIT can be expected under these climate, soil-water, and crop management conditions with SDI-irrigated maize. A strong dependence of the ETYPF slopes on RF treatment’s yield was observed. ETb had substantial inter-annual variation as 356, 230, and 315 mm in 2004, 2005, and 2006, respectively. ETb was strongly and positively correlated (R2=0.99) with the seasonal precipitation and strongly, but negatively correlated (R2=0.89) with seasonal cumulative thermal unit (Growing Degree Days). Based on the pooled ETYPFs, a 25.4 mm of ETc resulted in 1.86, 1.72, and 2.61 t/ha grain yield (beyond the intercept) in 2004, 2005, and 2006, respectively, with a seasonal average of 2.1 t/ha. Data and information of this research can provide guidance for irrigation professionals, managers, advisors, engineers, agronomists, economists, and other professionals and can be incorporated into the planning, forecasting, allocating and managing of water resources availability-demand-actual use analyses and decisions to enhance crop production efficiency.

Soybean (Glycine max L.) Leaf Moisture Estimation Based on Multisource Unmanned Aerial Vehicle Image Feature Fusion.

Efficient acquisition of crop leaf moisture information holds significant importance for agricultural production. This information provides farmers with accurate data foundations, enabling them to implement timely and effective irrigation management strategies, thereby maximizing crop growth efficiency and yield. In this study, unmanned aerial vehicle (UAV) multispectral technology was employed. Through two consecutive years of field experiments (2021-2022), soybean (Glycine max L.) leaf moisture data and corresponding UAV multispectral images were collected. Vegetation indices, canopy texture features, and randomly extracted texture indices in combination, which exhibited strong correlations with previous studies and crop parameters, were established. By analyzing the correlation between these parameters and soybean leaf moisture, parameters with significantly correlated coefficients (p < 0.05) were selected as input variables for the model (combination 1: vegetation indices; combination 2: texture features; combination 3: randomly extracted texture indices in combination; combination 4: combination of vegetation indices, texture features, and randomly extracted texture indices). Subsequently, extreme learning machine (ELM), extreme gradient boosting (XGBoost), and back propagation neural network (BPNN) were utilized to model the leaf moisture content. The results indicated that most vegetation indices exhibited higher correlation coefficients with soybean leaf moisture compared with texture features, while randomly extracted texture indices could enhance the correlation with soybean leaf moisture to some extent. RDTI, the random combination texture index, showed the highest correlation coefficient with leaf moisture at 0.683, with the texture combination being Variance1 and Correlation5. When combination 4 (combination of vegetation indices, texture features, and randomly extracted texture indices) was utilized as the input and the XGBoost model was employed for soybean leaf moisture monitoring, the highest level was achieved in this study. The coefficient of determination (R2) of the estimation model validation set reached 0.816, with a root-mean-square error (RMSE) of 1.404 and a mean relative error (MRE) of 1.934%. This study provides a foundation for UAV multispectral monitoring of soybean leaf moisture, offering valuable insights for rapid assessment of crop growth.

Drip-Mediated Deficit Irrigation and Sub-Optimal Fertigation Management Strategy can Boost Yield, Soil Nutrient Availability, Plant Utilization and Soil Organic Carbon in Banana Plantation

Drip-Mediated Deficit Irrigation and Sub-Optimal Fertigation Management Strategy can Boost Yield, Soil Nutrient Availability, Plant Utilization and Soil Organic Carbon in Banana Plantation

Uptake and translocation of pharmaceutically active compounds by olive tree (Olea europaea L.) irrigated with treated municipal wastewater.

The use of treated municipal wastewater (TWW) represents a relevant opportunity for irrigation of agricultural crops in semi-arid regions to counter the increasing water scarcity. Pharmaceutically active compounds (PhACs) are often detected in treated wastewater, posing a risk to humans and the environment. PhACs can accumulate in soils and translocate into different plant tissues, reaching, in some cases, edible organs and entering the food chain. This study evaluated the uptake and translocation processes of 10 PhACs by olive trees irrigated with TWW, investigating their accumulation in different plant organs. The experiment was conducted in southern Italy, in 2-year-old plants irrigated with three different types of water: freshwater (FW), TWW spiked with 10 PhACs at a concentration of 200 µg L-1 (1× TWW), and at a triple dose (3× TWW), from July to October 2021. The concentration of PhACs in soil and plant organs was assessed, collecting samples of root, stem, shoot, leaf, fruit, and kernel at 0 (T0), 50 (T1), and 107 (T2) days of irrigation. PhACs extraction from soil and plant organs was carried out using the QuEChERS method, and their concentrations were determined by high-resolution mass spectrometry coupled with liquid chromatography. Results of uptake factors (UF) showed a different behavior between compounds according to their physicochemical properties, highlighting PhACs accumulation and translocation in different plant organs (also edible part) in 1× TWW and 3× TWW compared to FW. Two PhACs, carbamazepine and fluconazole, showed interactions with the soil-plant system, translocating also in the aerial part of the plant, with a translocation factor (TF) greater than 1, which indicates high root-to-leaf translocation. Findings highlight that only few PhACs among the selected compounds can be uptaken by woody plants and accumulated in edible parts at low concentration. No effects of PhACs exposure on plant growth have been detected. Despite the attention to be paid to the few compounds that translocate into edible organs, these results are promising for adapting wastewater irrigation in crops. Increasing knowledge about PhACs behavior in woody plants can be important for developing optimized wastewater irrigation and soil management strategies to reduce PhACs accumulation and translocation in plants.

From Farm to Fork: Irrigation Management and Cold Storage Strategies for the Shelf Life of Seedless Sugrathirtyfive Table Grape Variety

Background: Sustainable water management for table grape has the primary goal of optimizing irrigation through Smart Irrigation (SI) approaches, particularly in Mediterranean regions. In addition, extending the shelf life of table grapes through effective cold storage practices is crucial to meet consumer demands year-round. This research examined the journey “from farm to fork” of Sugrathirtyfive variety (Autumn Crisp® brand), exploring the combined effects of Irrigation Volumes (IV), SO2-Generating Pads (SGPs) and Cold Storage Duration (CSD) on the quality of grapes. Methods: Normal Irrigation (NI—based on the farmer’s experience) and SI (100% vine evapotranspiration restored) were supplied in 2023 to Sugrathirtyfive variety white table grape, trained to an overhead tendone system. Yield and quality parameters, berry texture, CIELAB colour coordinates, phenolic content, flavonoids, antioxidant activity and sensory attributes were evaluated on grapes subjected to different times and methods of cold storage. Results: SI grapes showed higher Total Soluble Solids (TSSs) and nutraceutical content, as well as improved CIELAB coordinates with interesting improved berry texture parameters. No differences emerged between single- or dual-release SGPs after 15 days (T1) and 40 days (T2) of CSD. Conclusions: Under our cold storage conditions (3 °C, 85% U.R.), 40 days represent the maximum temporal limit for the cold storage of Sugrathirtyfive variety, regardless of IV, provided they are refrigerated with the aid of SGPs.

Sugarcane Water Productivity for Bioethanol, Sugar and Biomass under Deficit Irrigation

Knowledge of how certain crops respond to water stress is one of the prerequisites for choosing the best variety and best management practices to maximize crop water productivity (WPc). The selection of a more efficient protocol for managing irrigation depths throughout the cultivation cycle and in the maturation process at the end of the growth period for each sugarcane variety can maximize bioethanol productivity and WPc for bioethanol, sugar and biomass, in addition to the total energy captured by the sugarcane canopy in the form of dry biomass. This study aimed to evaluate the effect of four irrigation depths and four water deficit intensities on the maturation phase for eight sugarcane varieties under drip irrigation, analyzing the responses related to WPc for bioethanol, sugar and biomass. These experiments were conducted at the University of São Paulo. The plots were positioned in three randomized blocks, and the treatments were distributed in a factorial scheme (4 × 8 × 4). The treatments involved eight commercial varieties of sugarcane and included four water replacement levels and four water deficits of increasing intensity in the final phase of the crop season. It was found that for each variety of sugarcane, there was an optimal combination of irrigation management strategies throughout the cycle and during the maturation process. The RB966928 variety resulted in the best industrial bioethanol yield (68.7 L·Mg−1), WPc for bioethanol (0.97 L·m−3) and WPc for sugar (1.71 kg·m−3). The energy of the aerial parts partitioned as sugar had a direct positive correlation with the availability of water in the soil for all varieties. The RB931011 variety showed the greatest potential for converting water into shoots with an energy of 1.58 GJ·ha−1·mm−1, while the NCo376 variety had the lowest potential at 1.32 GJ·ha−1·mm−1. The productivity of first-generation bioethanol had the highest values per unit of planted area for the greatest water volumes applied and transpired by each variety; this justifies keeping soil moisture at field capacity until harvesting time only for WR100 water replacement level with a maximum ethanol potential of 13.27 m3·ha−1.

Field and simulation studies on yield, water and nitrogen dynamics and use efficiency in rice-wheat crops in sequence

ContextThe dominant rice-wheat cropping system in the Indo-Gangetic plain faces challenges of water depletion and nitrogen pollution of groundwater as well as declining productivity caused by over irrigation and nitrogen fertilization by the farmers. To appreciate the apt use of irrigation water and nitrogen fertilizer in rice and wheat crops it is essential to explore the water and nitrogen balances as well as dynamics in these crops, involving complex interaction between weather, soil, irrigation water and nitrogen fertilizer management. ObjectiveThe objective of the study is to quantify yield, field water balance components, water use efficiency, water productivity, water footprint, and water and nitrogen dynamics of rice and wheat crops in relation to season, varieties, irrigation regimes and nitrogen levels. MethodsField experimentations were conducted in double split plot design along with calibrated and validated HYDRUS 1D model use for two years comprising of treatments in rice i.e. two varieties (PR122-V1 and PR126-V2), two irrigation regimes (2-days drainage period-I1 and soil water suction 16 kPa-I2) and two nitrogen levels (120-N1 and 90-N2 kg N ha−1); and in wheat, two varieties (Unnat PBW343-V1 and Unnat PBW550-V2), two irrigation (1.2 IW/CPE-I1 and 0.9 IW/CPE-I2) regimes and two nitrogen levels (120-N1 and 90-N2 kg N ha−1). ResultsThe highest grain yield recorded was 7.6 t ha−1 in treatment combination of V1I2N1 in rice and 5.4 t ha−1 in V1I1N1 in wheat owing to better plant growth and yield attributes (biomass production, number of effective tillers, panicle length, and 1000 grain weight). Total water footprints were lower in the treatment combination of V1I1N1 in rice and V1I2N1 in wheat. The water budget revealed a higher percent contribution of the total water input to drainage (62 %) in rice ensuing restoration of water in the soil profile; and to evapotranspiration (ET) (100 %) in wheat ensuing water depletion. Modeling water and nitrogen dynamics showed higher root water uptake in I2 treatment in rice and with I1 treatment in wheat; and leaching losses of NO3-N under rice than wheat; and under I2 treatment than I1 as well as in N1 than N2. ConclusionsThe V1I2N1 treatment in rice and V1I1N1 treatment in wheat demonstrated superior grain yield, soil water storage, and root water uptake. Conversely, V1I1N1 treatment in rice and V1I2N1 treatment in wheat showed higher water use efficiency and lower water footprint. SignificanceIt helps to evaluate the effectiveness of irrigation and nitrogen management strategies in maximizing crop productivity while minimizing environmental impacts.

Evaluating the Effects of Deficit Irrigation and Mulch Type on Yield and Yield Components of Onion in Fogera, Ethiopia

Water scarcity is a challenge for current irrigated agriculture globally. Under these circumstances, new on-farm irrigation management strategies should be established. An experiment was conducted at Fogera in 2021 to evaluate the effects of deficit irrigation (DI) and mulch type on onion yield and yield components. A factorial combination of three levels of DI (100%ETc, 75%ETc, and 50%ETc) and three mulch types No Mulch (NM), White Plastic Mulch (WPM), and Rice Straw Mulch (RSM)) were evaluated in RCBD with three replications. Monthly ETo, ETc, and irrigation scheduling were computed using CROPWAT 8.0 model. These studies showed that the onion yield and yield components were significantly affected by the main and the interaction effects. The maximum average plant heights (PH), leaf heights (LH), and number of leaves per plant (LNP) of 51.7 cm, 38.0cm, and 10.4 respectively, were recorded from 100%ETc whereas the minimum PH, LH, and LNP of 39.5 cm, 29.0cm, and 6.9 were recorded from 50%ETc treatment respectively. The highest average bulb weight (BW), bulb diameter (BD), and bulb height (BH) were 117.9gr, 6.4, and 5.7 cm recorded from 100%ETc treatment respectively. In contrast, the minimum average BW, BD, and BH were 79.9gr, 4.8, and 5.0cm recorded from 50%ETc respectively. The highest PH, LH, and LNP of onions were 51.9cm, 40.6cm, and 10.1 respectively recorded from RSM treatments. In contrast, the minimum PH, LH, and LNP of onions were 41.5cm, 31.1cm, and 7.5 respectively, recorded from WPM treatments. Similarly, the highest mean BW, BH, and BD 106.2gr, 5.8cm, and 6.0cm were obtained from the treatments of RSM respectively. In contrast, the lowest mean BW, BH, and BD 100.7gr, 5.0cm, and 5.3cm were obtained from NM treatments respectively. The interaction effects of DI and mulch showed that the onion yield at 100%ETc with RSM was 7.5% higher than that at 100%ETc with NM and 15.1% higher than the yield at 100%ETc with PM. The highest BW, BH, and BD of the onion 121.8 gr, 6.2, and 6.8 were obtained when the onions received 100%ETc and mulched with RS while the lowest average BW, BH, and BD of the onion were 77.3gr, 4.6cm and 4.1cm were obtained from 50%ETc with NM treatment combination. These results showed that RSM with 75%ETc improves onion yield and yield components.

Transcriptome-Based Weighted Gene Co-Expression Network Analysis Reveals the Photosynthesis Pathway and Hub Genes Involved in Promoting Tiller Growth under Repeated Drought–Rewatering Cycles in Perennial Ryegrass

Drought stress, which often occurs repeatedly across the world, can cause multiple and long-term effects on plant growth. However, the repeated drought–rewatering effects on plant growth remain uncertain. This study was conducted to determine the effects of drought–rewatering cycles on aboveground growth and explore the underlying mechanisms. Perennial ryegrass plants were subjected to three watering regimes: well-watered control (W), two cycles of drought–rewatering (D2R), and one cycle of drought–rewatering (D1R). The results indicated that the D2R treatment increased the tiller number by 40.9% and accumulated 28.3% more aboveground biomass compared with W; whereas the D1R treatment reduced the tiller number by 23.9% and biomass by 42.2% compared to the W treatment. A time-course transcriptome analysis was performed using crown tissues obtained from plants under D2R and W treatments at 14, 17, 30, and 33 days (d). A total number of 2272 differentially expressed genes (DEGs) were identified. In addition, an in-depth weighted gene co-expression network analysis (WGCNA) was carried out to investigate the relationship between RNA-seq data and tiller number. The results indicated that DEGs were enriched in photosynthesis-related pathways and were further supported by chlorophyll content measurements. Moreover, tiller-development-related hub genes were identified in the D2R treatment, including F-box/LRR-repeat MAX2 homolog (D3), homeobox-leucine zipper protein HOX12-like (HOX12), and putative laccase-17 (LAC17). The consistency of RNA-seq and qRT-PCR data were validated by high Pearson’s correlation coefficients ranging from 0.899 to 0.998. This study can provide a new irrigation management strategy that might increase plant biomass with less water consumption. In addition, candidate photosynthesis and hub genes in regulating tiller growth may provide new insights for drought-resistant breeding.

ESTIMATION OF SUGARCANE YIELD USING MULTI-TEMPORAL SENTINEL 2 SATELLITE IMAGERY AND RANDOM FOREST REGRESSION

Abstract. Advancements in remote sensing techniques have greatly enhanced crop monitoring and yield estimation, with spectral vegetation indices (VIs) serving as a key component. Our study investigates the use of Sentinel-2 data, notable for its red-edge bands, in estimating sugarcane yield in Ethiopia's Awash Basin. Utilizing 22 VIs from S2 imagery, our approach combines Random Forest (RF) regression with the Recursive Feature Elimination (RFE) algorithm to improve the accuracy of sugarcane yield predictions. The results demonstrate the superior performance of the RF-RFE method over traditional RF with full datasets and Stepwise Multiple Regression (SMR). Particularly, VIs focusing on the red-edge spectral bands of S2 - such as NDVIre1n, NDVIre2n, NDVIre3n, NDRE1 and NDRE2 - were crucial in enhancing prediction precision. These indices from the red-edge and NIR narrow bands consistently influenced yield estimations in both the Wonji-Shoa and Metehara estates. The study underscores the critical role of the RFE algorithm in optimal variable selection, reinforcing earlier findings that precise variable choice can substantially boost model accuracy. The enhanced performance of the RF model when paired with the RFE algorithm was evident, emphasizing the importance of variable selection in accurate yield predictions. Employing the Out-of-Bag RMSE (OOB_RMSE) error estimate for evaluation, we observed variations in OOB_RMSE performance with different RF parameters, identifying the ntree value of 500 as optimal for the studied regions. The RF-RFE model’s estimations showed lower errors and higher correlation coefficients, proving its efficacy over a full dataset approach, which faced challenges with traditional VIs' saturation. Our findings align with earlier studies, highlighting the efficiency of S2’s red-edge bands in diverse estimation tasks and a shift towards using freely available broadband images like S2, over hyperspectral imagery, due to reduced data redundancy and processing costs. In conclusion, our findings reveal that RF regression, particularly when integrated with the RFE algorithm, is a powerful tool in remote sensing applications. The S2 imagery is optimal VIs, predominantly from the red-edge bands, exhibit significant potential for sugarcane yield estimations. The impressive results of the RF-RFE method, evident in metrics like MAE, MAPE, RMSE, Mean percentage, and R2, advocate its invaluable role in sugarcane yield prediction, highlighting its potential for optimizing irrigation management strategies and broad-spectrum agricultural planning.

Stratified substrates enhance water storage and distribution between irrigation events

AbstractThe specialty crop industry requires copious amounts of water to meet production needs; however, current substrates are highly porous to mitigate risks and are subsequently inefficient with regard to water use. Therefore, more sustainable soilless substrates are needed to ensure the future success/profitability of the horticultural industry, especially as finite fresh water sources become limiting. Substrate stratification (i.e., vertically layering unique substrates atop one another) provides opportunities to augment an existing system by maintaining substrate porosity, while strategically redistributing the air‐ and water‐filled pores, retaining more water when applied, and controlling vertical water distribution. The aim of this research was to further understand the complex stratified systems of hydraulics. Herein, the hydraulic properties of individual substrate components were measured and modeled using HYDRUS 1 d. Furthermore, matric tensions and volumetric water content (VWC) were measured continuously under two different irrigation schedules (single [1×] and cyclic applications [3×]) for 15 days with a fully established Dianthus barbatus ‘Amazon Neon Purple’ crop. The results showed that screened bark particles have more pore homogeneity assessed by steep declines in VWC with small changes in water potential. Moreover, HYDRUS 1 d modeling demonstrated that stratified substrates have more uniform hydraulic gradients (difference in moisture content from the top to the bottom of the substrate profile; 21%) present in the container profile when compared to non‐stratified systems (45%). Non‐stratified upper layers experienced greater diurnal tension fluctuations under single irrigation than in cyclic applications. Stratifying substrates resulted in a significant reduction in these fluctuations in the top layer when compared to non‐stratified systems. Additionally, when both substrate (stratifying) and irrigation (cyclic) management strategies are implemented, tension fluctuations can be even further reduced, and hydraulic gradients become more uniform due to improved moisture infiltration and distribution.

Climate-smart deficit irrigation and nutrient management strategies to conserve energy, greenhouse gas emissions, and the profitability of fodder maize seed production

The present irrigation and nutrient management practices could stabilize crop yields, but the huge energy consumption and GHG emissions put pressure on environmental quality. Therefore, climate-smart irrigation and nutrient management strategies are essential for sustainable fodder maize seed production systems. To address this research gap, climate-smart irrigation and nutrient management strategies were evaluated to reduce the environmental impact, increase profitability, reach carbon neutrality, and to achieve sustainable development goals such as improving energy productivity (SDG 7) and reductions in CO2 emissions (SDG 13) by 2030 to achieve global climate goals. The results from this study revealed that direct renewable resources were the major contributors to overall carbon (72.37%) and energy (24.77%) consumptions. Moderate irrigation at 50% depletion saved 19.11% energy and 26.11% carbon inputs by conserving water, fossil fuels, and manpower and was found to be more energy efficient (21.5% higher), less energy intensive (42.36 MJ US$−1), and with the lowest carbon footprint (0.34 kg CE kg−1 grain) over full irrigation. The adequate nutrients (Nitrogen 120: Phosphorus 60: Potassium 40 + Zinc 20 kg ha−1) resulted in improved energy use efficiency (6.24), carbon efficiency (16.02), and overall biomass yield (13.29 t ha−1). Therefore, the combination of climate-smart 50% deficit irrigation and adequate nutrients had a higher energy profitability (6.69), carbon output (86 486 kg ha−1), carbon efficiency (18.11), and carbon sustainability index (17.11). In conclusion, fodder maize seed production in semi-arid environments is economical, sustainable, energy efficient, and environmentally beneficial when using climate-smart 50% deficit irrigation and adequate nutrients.

Phenology, gas exchange, biomass accumulation, and irrigated rice yield under alternative irrigation managements

AbstractIn Brazil, rice production is predominantly concentrated in the South region, employing a continuous flood irrigation system throughout the crop cycle. However, this irrigation management strategy in the tropical region contributes to low water‐use efficiency owing to adverse climatic conditions. Furthermore, with climate change projections indicating reduced water availability, the study aims to investigate the impact of alternative irrigation management strategies on the phenological development, gas exchange, biomass accumulation, and productivity of tropical irrigated rice. Three alternative irrigation management approaches—intermittent flood irrigation with aeration (IFA), intermittent flood irrigation throughout the growth cycle (IFC), and intermittent flooding up to the flowering stage (IFF)—were compared with the traditional continuous flood irrigation throughout the growth cycle. Phenological data, gas exchange, growth, and productivity dynamics were subject to analysis, providing overarching insights into management practices. Notably, irrigation management exhibited no influence on the vegetative phase of the crop. The implementation of intermittent flood irrigation facilitated a reduction in water supply without compromising the physiological performance of tropical irrigated rice. Strategies promoting judicious water utilization, such as IFA and IFC, can be readily integrated into the cultivation of tropical irrigated rice without detriment to grain yield or harvest index.

Water use efficiency of grape tomatoes subjected to different types of substrates, methods of conduction and irrigation management strategies

Water use efficiency of grape tomatoes subjected to different types of substrates, methods of conduction and irrigation management strategies

Reducing cadmium accumulation and increasing grain yield with proper timing of flood irrigation in the second season of ratoon rice

Context or problemThe second season of ratoon rice (ratoon crop, RC) exhibits a high risk of cadmium (Cd) contamination in grains, requiring effective irrigation management strategies to reduce its grain Cd concentration. Objective or research questionThis study aimed to determine the crucial growing period for Cd accumulation and provide irrigation recommendations for reducing grain Cd concentrations with limited water input in the ratoon season. MethodsA two-year field experiment was conducted in Hubei province, central China. The entire growth duration of RC was divided into three short periods: from harvest of the main crop (HM) to initial heading of RC (IH), from IH to full heading of RC (FH), and from FH to maturity of RC (MR). During each growth period of RC, two water regimes (flooded and rainfed) were established. Therefore, there were a total of eight water treatment combinations in this experiment, using a randomized complete block design. Two hybrid varieties were planted in this study. ResultsAcross years, varieties and treatments, the grain Cd concentration of RC ranged from 27.8 to 314.1 µg kg−1, with 37.5% of rice samples exceeding the national food safety standard for Cd (200 µg kg−1). RC grown under continuous flooding conditions produced the lowest grain Cd concentration and highest grain yield. Compared with rainfed conditions, maintaining flooded conditions from HM to IH, from IH to FH, and from FH to MR resulted in decreases of 28.4%, 62.7%, and 12.0% in grain Cd concentration and decreases of 25.5%, 49.9%, and 16.3% in total Cd accumulation at maturity, respectively. RC took up the most Cd during the period from IH to FH under rainfed conditions; however, maintaining flooded conditions reduced Cd uptake by 95.4% during this period. Moreover, flooding from IH to FH had the most positive impact on the grain yield of RC, with an increase of 8.1% compared with rainfed conditions. ConclusionsMaintaining flooded conditions from initial to full heading for 15–18 days was not only effective in reducing grain Cd concentration but also beneficial for improving grain yield in the ratoon season. Implications and significanceThis study clarified the effects of water management during different growing periods on Cd accumulation and grain yield in the ratoon season. We emphasized the necessity of flooding during heading period to control Cd accumulation in RC grains, especially in areas with limited water resources and high soil Cd concentration.

Optimizing Water Use Efficiency and Yield of Wheat Crops through Integrated Irrigation and Nitrogen Management: A Comprehensive Review

Achieving sustainable agricultural productivity is critical due to the rising worldwide demand for food and the growing scarcity of water. This comprehensive review investigates the complex interrelations where integrated irrigation and nitrogen management are used as a strategic method to improve wheat crop yields and water use efficiency (WUE). The study synthesizes current research findings, methodologies, and technological advancements related to optimizing water and nitrogen inputs in wheat cultivation. A number of factors can affect WUE in wheat, including climate, soil, crop management practices, and genetic factors. There are a number of irrigation and nitrogen management practices that can be used to improve WUE in wheat, including deficit irrigation, mulching, and split applications of nitrogen fertilizer. The review underscores the significance of tailored irrigation and nitrogen management strategies in mitigating water stress, reducing nutrient runoff, and promoting sustainable agricultural practices. Insights from this comprehensive analysis aim to guide policymakers, agronomists, and farmers in making informed decisions for optimizing wheat production while conserving water resources and minimizing environmental impact. Future research on WUE can help to ensure that wheat production remains sustainable in the face of future challenges such as climate change and water scarcity.

Participatory mapping of irrigation schemes in Tanzania, Mozambique and Zimbabwe and their value for multi-level learning

This paper analyses the capacity of participatory mapping as a multi-level learning process to identify and overcome current barriers to productivity within small-scale irrigation schemes. The analysis is based on thirteen smallholder irrigation schemes in Tanzania, Mozambique, and Zimbabwe, where farmers, project officers and other key stakeholders participated in informal mapping teams to map the schemes. Critically, participatory mapping translated problems generally known by stakeholders into problems that were publicly known, making their resolution a shared responsibility. Hence, problems identified at both the scheme and plot levels led to immediate responses by the farmers, irrigator organizations, and government departments, boosting farmers’ agency and confidence and renewing their sense of scheme and plot ownership. It is important that irrigation agencies prioritize participatory processes and the use of informal networks to improve farmers’ understanding of their resource and management challenges and to build their sense of ownership and responsibility for effective management of irrigation schemes.

Evapotranspiration and Yield Impact Tools for More Water-Use Efficient Alfalfa Production in Desert Environments

Drought and climate change have decreased water availability for agriculture, especially in the desert of southwestern USA. Efficiency enhancements in irrigation management aimed at conserving water are key to adjust to limits in water supply, improve profitability and sustainability of alfalfa production in arid and semiarid areas. This study intended to conduct a field-scale analysis to develop yield and ET estimation tools for the effective use of irrigation water in a desert alfalfa production system. Extensive data collection and trials were carried out over three years in nine fully irrigated commercial alfalfa fields in the low deserts of California. The seasonal crop water consumption measured using the residual of energy balance method varied from 1381 mm to 1596 mm across the experimental sites and crop seasons. Variable seasonal dry mater (DM) yields ranged from 23.01 Mg ha−1 to 29.90 Mg ha−1. The results indicated that the first five cuttings each year were the most productive cuttings with a mean DM value ranged between 3.29 (cut 1) and 4.21 (cut 4) Mg ha−1 but declined in later cuttings. An average annual water productivity (WP) value of 17.0 kg ha−1 mm−1 was determined across the sites varying from 15.5 to 18.9 kg ha−1 mm−1. The findings suggested that one may lose up to 1.44 Mg ha−1 alfalfa yields with moderate summer deficit irrigation strategies, using 40% less water applied than full irrigation practices over the summer period of July–September. A more severe summer water deficit, with no irrigation event over the summer period of July–September may result in a potential water savings of 0.234–0.246 (ha·m) ha−1 and 19–21% seasonal yield losses in the desert environment. This study describes the seasonal yield pattern, the crop water use-production function, and the crop coefficient values for various harvest cycles over the crop season. These tools may assist farmers to quantify water savings and estimate yield losses for more accurate and effective irrigation management strategies to meet water conservation objectives and for the resiliency of alfalfa production in the desert region.

Intermittence in irrigation management and nitrogen optimize yield and water use efficiency in baby lettuce

Aim of the study: To evaluate the influence of irrigation management strategies and nitrogen (N) on baby lettuce growth, yield, and water use efficiency in a protected environment. Area of study: Botucatu, SP, Brazil. Material and methods: The experiments were conducted in two consecutive cycles, and the treatments corresponded to the combination of irrigation management strategies with N doses. Irrigation strategies comprised 3 possibilities: continuous irrigation (Cont); intermittent irrigation with three irrigation pulses at one-hour intervals (Int1); and intermittent irrigation with irrigation depth split and applied at 7:00, 11:00, and 15:00 h (Int2). Two N doses were evaluated, 100 and 130 kg/ha of N, applied in daily fertigation according to the irrigation management strategies. Main results: Intermittent irrigation strategies (Int1 and Int2) promoted the highest vegetative growth, increased leaf water content, and increased total yield (49.55 and 55.30; 46.83 and 49.50 t/ha) and marketable yield (46.77 and 52.44; 45.11 and 47.17 t/ha) in the first and second cycles, respectively, in addition to optimizing water use efficiency. The N dose of 130 kg/ha increased the total yield (51.61 t/ha), marketable yield (48.98 t/ha), and water use efficiencies of total yield (53.60 kg/m³) and marketable yield (50.88 kg/m³) only in the first crop cycle. Research highlights: The use of intermittence in irrigation management proved to be more efficient in obtaining high yields and maximized the efficiency of use of water as a factor of production.

Optimizing crop production water footprints in the face of water scarcity: a combined experimental and simulation study of wheat in Zimbabwe

Abstract The optimization of water footprints in crop production is critical, given that agroecosystems currently account for more than 70% of global freshwater use. To achieve this, crop growth models provide insights into the impact of various crop and irrigation management strategies on both crop productivity and water use. This study evaluated the capability of the AquaCrop model in simulating wheat yields, crop water use, and water footprints in the Middle-Manyame Sub-Catchment, Zimbabwe. The model was calibrated and validated using experimental data collected from field experiments. Simulation experiments were conducted to assess the impact of early and late planting, drip and sprinkler irrigation techniques, and no mulch, organic mulch, and synthetic mulch options on the water footprint (WF). The AquaCrop model accurately simulated soil water content, crop water use, crop biomass, and grain yield. Simulation runs showed that early planting reduced WFblue and WFgreen by 25 and 4%, respectively. The lowest consumptive WF was observed with drip irrigation and synthetic mulching. The greatest decline in WFblue and WFgreen (52 and 11%) was simulated under early planting, using drip irrigation and synthetic mulching. Overall, the study highlights the importance of efficient crop and irrigation management practices to reduce water footprints in agroecosystems.