Maximize Water Use Research Articles

Optimizing water use efficiency in maize (Zea mays L.) production through deficit irrigation in Gazhen-Fuafuat Kebele, Northwest Ethiopia

Ethiopia's dominant maize production relies on rain, but growing water scarcity challenges dry season irrigation efforts. This necessitates smarter irrigation techniques to maximize water use efficiency. This study optimizes water use efficiency in maize production through deficit irrigation in Gazhen-Fuafuat kebele, Fogera woreda, Ethiopia. A field experiment was conducted during the 2019/20 dry season, comparing four irrigation levels: 55%, 70%, 85%, and 100% of crop water requirements (ETc). Findings revealed that while higher irrigation levels generally enhanced plant growth and grain yield, irrigation water use efficiency was optimized at 70% ETc. Deficit irrigation at 55% ETc proved to be suboptimal, leading to significant reductions in crop growth and grain production. Conversely, applying 70% ETc resulted in a 30% reduction in irrigation water use without compromising yield. Compared to full irrigation, deficit irrigation at 85% ETc, 70% ETc, and 55% ETc resulted in yield reductions of 8%, 13.5%, and 33.1%, respectively. However, these reductions were accompanied by water savings of 15%, 30%, and 45%, respectively, leading to corresponding increases in water use efficiency of 8%, 23.4%, and 21.9%. These results suggest that deficit irrigation practices can be effectively employed to improve water use efficiency in maize production, especially in the study area facing water scarcity. This study provides valuable insights into the potential of deficit irrigation to improve maize production in Ethiopia while conserving water resources. Therefore, by implementing deficit irrigation strategies and supporting farmers with appropriate training and resources, Ethiopia can enhance its agricultural productivity and ensure food security in the face of increasing water scarcity.

Techno-economic study for photovoltaic battery-free irrigation systems in an arid area for olive fields in Western West Al Minya, Egypt

Due to rain scarcity, artificial irrigation became an environmentally critical application for crop production. Proper irrigation is essential to maximize water use efficiency and plant biomass. Using clean energy sources is currently a trend that is sweeping the globe. To achieve this, we propose a solar-powered irrigation system. This study considers alternative irrigation systems using photovoltaic solar systems to pump water from deep wells for new land reclamation, whereas groundwater is the only source. The main objective is to evaluate various PV-powered pumping systems in Egypt's Western West Al Minya area. Two systems were nominated by considering the annual savings: the conventional irrigation Diesel system and a Photovoltaic (PV) battery-free irrigation system. The second system requires isolated pipes so solar radiation does not affect water temperature and avoids damage to plant roots. The 192 kW PV system was sized to operate a 60 KW water pumping system, with a required area of 1920 m2 for implementation. Direct irrigation using PV systems proved the best economical solution since it incurs the fewest costs of $0.015/m3 for 100–120 m well depth, compared with $0.073/m3 from the conventional system. As a result, the proposed PV-pumping system reduced the overall system cost by around 80% concerning the conventional system.

Pre - Extension Demonstration of Alternate Furrow Irrigation for Better Water Management Technologies at Dugda District

The agricultural sector is the main consumer of fresh irrigation water so any effort to improve WUE in this sector gets a lot of attention so, raising WUE through improved of modern irrigation techniques and increasing the capacity of soil output complementary to make better employ of irrigation water and saving water for other uses. The aim of this study was to demonstrate the most effective water-saving techniques and improve the water use efficiency of irrigated onions under limited agricultural water availability for better water management technologies. The treatment consists of conventional furrow irrigation and alternate furrow irrigation method with full crop water requirement in three replications on two farmers. Crop water requirement was estimated using actual daily climatic data. The result showed that conventional furrow irrigation method was the highest bulb yield and yield components when compared to alternate furrow irrigation method. Alternate furrow irrigation method produced total yield of 18.73 t/ha which was not significantly different with that obtained under every furrow irrigation (220.6 Qt/ha). It was also found that yield reduction may be low compared to the benefits gained by diverting the saved water to irrigate extra cultivated land. The result showed that decreasing WP with increased irrigation water from 50% crop water requirement (ETc) from alternate furrow irrigation (5.68 kg m-3) to conventional furrow irrigation 100% Etc (3.6 kg m-3). Increasing water deficit from 100 to 50% ETc led to an increase of onion WP up to 75%. For increasing marketable bulb yield of onion under no water stress scenario, irrigation of onion with conventional furrow irrigation methods could be used. However, under limiting irrigation water resource condition, irrigation of onion could be done with alternate furrow irrigation method to maximize water use efficiency of onion for similar agro-ecology and soil type.

Effect of deficit irrigation and partial rootzone drying on the water consumptive use, growth and yield of faba bean (vicia faba L.) in a gypsiferous soil

Iraq’s farming sector is under increasing pressure to improve water use productivity as a result of the recent drought, environmental concerns regarding sustainable river ecosystems, and government policies on water metering and allocations. To cope with scarce supplies, deficit irrigation, and partial rootzone drying, defined as the application of water below full crop-water requirements, is an important tool to achieve the goal of reducing irrigation water use. It is necessary to develop new irrigation scheduling approaches, not necessarily based on full crop water requirement, but ones designed to ensure the optimal use of allocated water. These two methods of irrigation are one way of maximizing water use efficiency (WUE) for higher yields per unit of irrigation water applied: the crop is exposed to a certain level of water stress either during a particular period or throughout the whole growing season. The expectation is that any yield reduction will be insignificant compared with the benefits gained through diverting the saved water to irrigate other crops. This paper reviews the yield response of the faba bean (Vicia faba L.). The deficit of irrigation on gypsiferous soils is not known. A field experiment was carried out to study the effect of deficit irrigation and partial drying of the root system on the growth and yield of the bean Randomized Complete Blocks (RCBD) design in gypsiferous soil in the fields of the College of Agriculture- Tikrit University, which is located on Latitude 49° 40ʹ 34˝ North and Longitude 40° 38ʹ 43˝ East At an altitude of 129 m above sea level. The study included seven treatments of full irrigation, deficit irrigation, 25, 50 %, and fixed, alternating partial drying. The seeds of the Barcelona variety were sown for the season on 16/10/2021 and harvested on 2/4/2022. The results showed that the full irrigation treatment gave the highest water consumption use of 635 mm, while the alternative partial root drying decreasing 50% gave the lowest water consumption use of 245 mm and gave the highest crop water use efficiency of 2.0 kg m-3. Treatment full irrigation gave the highest seed yield of 5186.3 kg.ha-1, While the 50% deficit irrigation treatment gave the highest dry weight of the root system, which was 25.6 gm.plant-1.

Maximizing Water Use Efficiency (WUE), Land Utilization Efficiency (LUE) and Competitive Indices of Maize and Soybean Crops Through Intercropping Pattern with Straw Mulching

Maximizing Water Use Efficiency (WUE), Land Utilization Efficiency (LUE) and Competitive Indices of Maize and Soybean Crops Through Intercropping Pattern with Straw Mulching

Machine Learning based Precision Agriculture Model for Farm Irrigation to Optimize Water Usage

The food demand is ever increasing each year and to meet this demand precision agricultural approach using machine learning tools play an important role. Precision irrigation systems integrate cutting-edge technologies, such as sensors, controllers, data analytics and internet, to achieve sustainability in agriculture and maximize water use so as to improve crop production while minimizing water wastage and climate impact. The main purpose of this article is to find out the precise water requirements for a particular area of the land by using soil moisture sensors. These sensors provide real-time data that is transmitted to a central control unit, which utilizes data driven algorithms to analyze moisture levels in the soil and controls the water supply. Furthermore, the model developed offers remote monitoring and control capabilities, enabling farmers to access and manage the system from anywhere using mobile or web application. This feature allows farmers to remotely adjust irrigation schedules, receive real-time alerts and notifications, and track water consumption, promoting convenient and efficient management of water resources. Thus by using effective water management techniques such as precision irrigation, controlling the water quality, will accomplish optimizing water usage and intern optimizes the yield.

Gelatinous fibretracheids as an escape mechanism for the physiological drought phenomenon

Abstract Alchornea sidifolia is a tree species used in the regeneration of degraded forest environments and which grows in both non-flooded and flooded soils. We compared the wood anatomy of trees growing under both conditions in Atlantic Forest remnants in the state of Rio de Janeiro, Brazil, to understand intraspecific aspects of the adaptation of tropical woody species to these conditions. Trees from permanently flooded soils showed wider, shorter, and less frequent vessel elements; wider fibretracheids, with a greater proportion of the gelatinous type; and a lower frequency of radial parenchyma, but with longer strands of axial parenchyma. These results indicate that A. sidifolia trees growing in permanently flooded sites do not show water deficit and that the species is capable of maximizing water use in this growth condition. This conclusion may be directly related to the greater proportion of gelatinous fibretracheids in flooded trees and is contrary to what was expected for wood anatomy of trees under physiological drought.

The Tree-Crop Remote Sensing of Evapotranspiration Experiment (T-REX): A Science-Based Path for Sustainable Water Management and Climate Resilience

Abstract Water scarcity threatens agriculture in California. During the last two decades, historically severe droughts have led to severe water shortages. Under projected changes in climate, droughts of greater severity and duration will exacerbate this situation. California produces 80% of the world’s almonds, which require consistent water supplies for irrigation. Almonds are the most commonly grown crop in California, covering nearly 1.4 million acres over about 8,000 farms. In response to these challenges, almond growers are considering a myriad of management strategies to save water and mitigate climate change. The Tree-Crop Remote Sensing of Evapotranspiration Experiment (T-REX) aims to identify water and orchard management opportunities to maximize water use efficiency and carbon sequestration in almonds and other woody perennial tree crops. The project combines satellite, uncrewed aerial vehicles, and proximal sensing technologies to retrieve key variables used to model surface fluxes and biophysical properties. We aim to advance our understanding of water management and cultural practices on water–carbon relationships in tree-perennial agroecosystems. Through new methods, such as evapotranspiration-based irrigation scheduling, even a modest 10% decrease in almond orchard irrigation across the state equates to about a third of the water in Lake Oroville, California’s second-largest reservoir, at average levels. From a carbon perspective, almond orchards could sequester 8% of the state’s current greenhouse gas emissions by transitioning toward climate-smart practices. As such, the almond industry is uniquely positioned to curb water use and contribute to climate change mitigation while maintaining economic viability of almond production. An overview of initial results related to evapotranspiration observational and modeling uncertainty and carbon sequestration potential are presented in this article.

Precision Agriculture Model for Farm Irrigation using Machine Learning to Optimize Water Usage

The food demand is ever increasing each year and to meet this demand precision agricultural approach using machine learning tools play an important role. Precision irrigation systems integrate cutting-edge technologies, such as sensors, controllers, data analytics and internet, to achieve sustainability in agriculture and maximize water use so as to improve crop production while minimizing water wastage and climate impact. The main purpose of this article is to find out the precise water requirements for a particular area of the land by using soil moisture sensors. These sensors provide real-time data that is transmitted to a central control unit, which utilizes data driven algorithms to analyze moisture levels in the soil and controls the water supply. Furthermore, the model developed offers remote monitoring and control capabilities, enabling farmers to access and manage the system from anywhere using mobile or web application. This feature allows farmers to remotely adjust irrigation schedules, receive real-time alerts and notifications, and track water consumption, promoting convenient and efficient management of water resources. Thus by using effective water management techniques such as precision irrigation, controlling the water quality, will accomplish optimizing water usage and intern optimizes the yield.

State of the Art and New Technologies to Recycle the Fertigation Effluents in Closed Soilless Cropping Systems Aiming to Maximise Water and Nutrient Use Efficiency in Greenhouse Crops

Inappropriate fertilisation results in the pollution of groundwater with nitrates and phosphates, eutrophication in surface water, emission of greenhouse gasses, and unwanted N deposition in natural environments, thereby harming the whole ecosystem. In greenhouses, the cultivation in closed-loop soilless culture systems (CLSs) allows for the collection and recycling of the drainage solution, thus minimising contamination of water resources by nutrient emissions originating from the fertigation effluents. Recycling of the DS represents an ecologically sound technology as it can reduce water consumption by 20–35% and fertiliser use by 40–50% in greenhouse crops, while minimising or even eliminating losses of nutrients, thereby preventing environmental pollution by NO3− and P. The nutrient supply in CLSs is largely based on the anticipated ratio between the mass of a nutrient absorbed by the crop and the volume of water, expressed as mmol L−1, commonly referenced to as “uptake concentration” (UC). However, although the UCs exhibit stability over time under optimal climatic conditions, some deviations at different locations and different cropping stages can occur, leading to the accumulation or depletion of nutrients in the root zone. Although these may be small in the short term, they can reach harmful levels when summed up over longer periods, resulting in serious nutrient imbalances and crop damage. To prevent large nutrient imbalances in the root zone, the composition of the supplied nutrient solution must be frequently readjusted, taking into consideration the current nutrient status in the root zone of the crop. The standard practice to estimate the current nutrient status in the root zone is to regularly collect samples of drainage solution and determine the nutrient concentrations through chemical analyses. However, as results from a chemical laboratory are available several days after sample selection, there is currently intensive research activity aiming to develop ion-selective electrodes (ISEs) for online measurement of the DS composition in real-time. Furthermore, innovative decision support systems (DSSs) fed with the analytical results transmitted either offline or online can substantially contribute to timely and appropriate readjustments of the nutrient supply using as feedback information the current nutrient status in the root zone. The purpose of the present paper is to review the currently applied technologies for nutrient and water recycling in CLSs, as well as the new trends based on ISEs and novel DSSs. Furthermore, a specialised DSS named NUTRISENSE, which can contribute to more efficient management of nutrient supply and salt accumulation in closed-loop soilless cultivations, is presented.

IMPROVING CROPS BY IRRIGATION MANAGEMENT AND SOIL CONDITIONERS: A REVIEW

Deficit irrigation strategies would require an accurate assessment of growth stage-specific stress tolerances for vegetable crops and optimal water management supported by advanced irrigation systems; i.e., able to promptly cope with crop water requirements at sensitive phenological stages However, in semiarid environments, the fulfillment of leaching requirements significantly limits the possibility of applying deficit irrigation criteria and reduces the WUE in irrigated vegetable production. The adoption of methods to control the level of plant water stress (using soil tensiometers or other soil water sensors or calculation of water balance) can reduce the amount of water applied to the crop up to 53%. Use of subsurface drip irrigation has progressed from being a novelty used only in experimental fields to an accepted method of irrigation for both tree and vegetable crops mentioned that subsurface drip irrigation on lettuce, tomato and sweet corn (Z. mays) has significantly increased yield and WUE in all these crops. Subsurface drip irrigation may increase WUE in semiarid environment under saline conditions by increasing yield. Our research goal is to suggest a framework could be utilized from natural and synthetic materials that could be used as soil and/or plant conditioners to maximize water use efficiency under drought conditions

Study on the Optimization of Multi-Objective Water Resources Allocation in the Henan Yellow River Water Supply Zone

With the continuous growth in the global population, rapid socioeconomic development, and the impacts of factors like climate change, we are facing increasingly severe challenges regarding water scarcity. The scientific and rational allocation of water resources has become a key factor in ensuring sustainable development. The Henan Yellow River water supply zone occupies a crucial position in the socioeconomic development of Henan Province. Currently, there is a shortage of water resources with relatively low utilization rates. To alleviate the contradiction between water supply and demand, a study on the optimization of water resources (with p = 90%) for the years 2025 and 2030 was conducted. In this study, we constructed a multi-objective optimization model with the objectives of maximizing economic benefits, minimizing total water shortage, and maximizing water use efficiency. The second-generation non-dominated sorting genetic algorithm (NSGA-II) was utilized to solve this model. The results indicate that by 2025, the optimized allocation of water resources will correspond to 17.663 billion m3, reducing the average water shortage rate in the research area to 9.69%. By 2030, the optimized allocation of water resources will further increase to 18.363 billion m3, bringing down the average water shortage rate to 8.34%. Concurrently, the supply structure of the research area will significantly improve after optimization. This is manifested through an increase in the proportion of surface water supply and a substantial rise in the proportion of supply from other water sources, while the proportion of groundwater supply noticeably decreases. These research findings can serve as a reference for the rational utilization and distribution of water resources in the future and can also offer insights for optimizing water resource allocation in other regions.

Economic value of virtual water with the approach of maximizing the productivity of irrigation water

Abstract The increasing use of water and the decrease in average rainfall along with climate change have caused the reduction of water resources in arid and semi-arid regions. In addition, despite the consumption of more than half of these resources in the agricultural sector, a rate between 0 and 15% of the price of the products has always been received from the farmers. Considering the concept of virtual water and the water content of products in the form of green water, blue water and gray water, the present research has calculated the economic value of virtual water of agricultural products with the approach of maximizing water use efficiency. The investigated sample includes eight cities (counties) of Sanmenxia, Jiaozuo, Nanyang, Shangqiu, Puyang, Luohe, Luoyang and Kaifeng and six agricultural products (wheat, barley, potato, rapeseed, tomato and corn). A fuzzy dynamic programming model has been used to evaluate the objective function. The results showed that the maximum and minimum economic value of water content (sum of surface and groundwater) of the products were estimated for Kaifeng and Shangqiu regions equal to 1.16 and 0.86 Yuan/m3, respectively.

Reducing Deep Percolation Losses Using a Geotextile Layer at Different Soil Depths and Irrigation Levels for Lettuce Crop (Lactuca sativa L. var. capitata) (Limor)

Due to rising food demand and the limitation of water resources, achieving water security is essential. The lettuce crop is affected when grown under limited water supplies as it produces small heads, especially during the late growing stage. For this reason, it is important to maximize water use efficiency and crop productivity. Two successive experiments were conducted during 2021 and 2022 to reduce losses via deep percolation using a geotextile layer at different soil depths under different irrigation levels of the lettuce crop (Lactuca sativa L. var. capitata). This study aims to reduce water losses due to deep percolation and improve crop growth and yield parameters for iceberg lettuce under subsurface drip irrigation in sandy loam soil conditions. In order to achieve these aims, different amounts of irrigation (100, 80, and 60% of crop evapotranspiration “ETc”) and a geotextile layer at different soil depths (20, 30, and 40 cm from the soil surface) were used. The results revealed that the use of a geotextile layer with 20 and 30 cm depths significantly improved irrigation application efficiency and noticeably increased soil water content in the root zone. The observed results during both seasons showed that geotextile layers at 20, 30, and 40 cm depths under irrigation of 100% ETc significantly increased vegetative growth characteristics (plant height, head diameter, head circumference, head volume, plant fresh weight, and leaf area) and crop productivity compared to the control (without geotextile). In particular, the geotextile layer at a 30 cm depth under irrigation of 100% of ETc was the most statistically effective treatment in this study, with yield values of 69.3 and 67.5 t ha−1 in the two seasons, respectively. However, the treatments of geotextile layers at 20 and 30 cm depths under irrigation of 80% of ETc also recorded statistically effective results for crop growth parameters and yield in this study. In general, geotextiles can be used at different depths as an irrigation management practice to reduce deep percolation in the field.

Multiobjective optimization of regional irrigation and nitrogen schedules by using the CERES-Maize model with crop parameters determined from the remotely sensed leaf area index

Using crop models to develop reasonable irrigation and nitrogen schedules (INSs) is critical for achieving high yields and maximizing water use efficiency (WUE) and nitrogen use efficiency. However, the INSs developed based on crop parameters determined through field experiments have low robustness at the regional scale. Remote sensing data indicate the growth conditions of regional crops, and representative regional crop parameters can be determined using remote sensing data. The objective of the present study was to develop a regional INS by adopting a crop model with crop parameters calibrated using the remotely sensed leaf area index (LAI). First, the crop parameters of a field-scale crop model were calibrated on the basis of field-scale trial data for four summer maize growing seasons. Sensitive crop parameters at the regional scale were then identified using an assimilation algorithm based on the remotely sensed LAI. The rationality of using the remotely sensed LAI for determining regional crop parameters was demonstrated by simulating regional maize growth. Finally, a regional-scale crop model was developed and coupled with a multiobjective genetic algorithm to optimize the regional INS for different typical-rainfall years. The results indicated that the regional-scale crop model was more accurate than was the field-scale crop model in simulating the regional LAI, plant height, soil water content, and yield and the corresponding RMSE decreased by 0.50 m2/m2, 0.15 m, 0.02 cm3/cm3, 344.11 kg/ha. Compared with the INSs currently used by farmers, the optimized INS was associated with a marginally higher irrigation quantity (average increase of 2.66%) but a significantly lower nitrogen application rate (average decrease of 31.6%). The crop yield, WUE, and partial factor productivity for nitrogen were 6.35–12.51%, 2.64–10.41%, and 61.8–66.2% higher, respectively, in different typical-rainfall years when using the optimized INS than when using an unoptimized INS. The results of this study indicate that a regional INS established on the basis of regional crop model parameters estimated using remote sensing data can aid irrigation and nitrogen application scheduling.

Maximizing Water Use Efficiency in Rice Farming: A Comprehensive Review of Innovative Irrigation Management Technologies

Rice is a water-guzzling crop cultivated mostly through inefficient irrigation methods which leads to low water use efficiency and many environmental problems. Additionally, the export of virtual water through rice trading and the looming water crisis poses significant threats to the sustainability of rice production and food security. There are several alternative rice production methods to improve water use efficiency. These include aerobic rice, direct-seeded rice (DSR), alternate wetting and drying (AWD), saturated soil culture (SSC), drip-irrigated rice, a system of rice intensification (SRI), and smart irrigation with sensors and the Internet of Things (IoT). However, each method has its own advantages and disadvantages. For example, drip-irrigated rice and IoT-based automated irrigation are not feasible for poor farmers due to the high production costs associated with specialized machinery and tools. Similarly, aerobic rice, drip-irrigated rice, and the SRI are labor-intensive, making them unsuitable for areas with a shortage of labor. On the other hand, DSR is suitable for labor-scarce areas, provided herbicides are used to control weeds. In this article, the suitability of different water-saving rice production methods is reviewed based on factors such as climate, soil type, labor, energy, and greenhouse gas emissions, and their prospects and challenges are evaluated. Additionally, the article examines how cultural practices, such as seed treatment, weed control, and nutrition management, contribute to enhancing water use efficiency in rice production.

Carbon fluxes associated with fog in an elfin cloud forest in Anaga (Tenerife, Canary Islands)

The role of fog in the relict laurel forests of the Macaronesia is still not fully understood and it is even more relevant in the Canary Islands, where precipitations are rather scarce and summers are dry. Eddy covariance CO2 exchange (FCO2) measurements in a “brezal de tejo” elfin cloud forest in Tenerife (Canary Islands), over a four-weeks period during the wet season, showed that the vegetation can sustain a carbon assimilation rate in an environment of fog, leading to higher median water use efficiency values (19.5 μmol mg−1 ≤ WUE ≤ 68.3 μmol mg−1) than during no-fog periods (WUE = 1.8 μmol mg−1), being highest under thick fog (WUE = 68.3 μmol mg−1). Median FCO2 values across the day were slightly greater under foggy versus no-fog conditions during the study period. These increments were more prominent under a low light environment, especially in the morning, thus highlighting the important difference between cloud immersion versus high clouds. A greater proportion of light diffusivity due to fog may enhance carbon assimilation, although additional concomitant factors may intervene during thick fog conditions. Also, net carbon assimilation was initiated earlier under foggy conditions. During cloud immersion and depleted light, the maximal CO2 exchange, FCO2_max, diurnal values were higher than those observed when fog was absent. Additionally, FCO2_max remained high (FCO2_max ≈ 13 μmol m−2 s−1) for large vapour pressure deficit conditions (VPD > 0.6 kPa). All this is indicative of a profligate water use strategy of the vegetation, presumably due to low stomatal control. Fog was present during 36.9 % of the time and, as a consequence, the estimated mean daily settling flux of water droplets was 1.186 mg m−2 s−1. For the entire period measured, the cumulative settling flux was 1.30 mm compared to the 97.6 mm of rainfall and the 36.6 mm of throughfall, and the canopy was wet at least 33.3 % of the time. The results suggest that such an anisohydric behaviour of the vegetation permits a continuous growth with maximal water use efficiency, while the frequent presence of fog and wetting of the canopy would minimize the risk of cavitation associated with such non-conservative water use response.

Almond Tree Adaptation to Water Stress: Differences in Physiological Performance and Yield Responses among Four Cultivar Grown in Mediterranean Environment.

Maximizing water use efficiency, yield, and plant survival under drought is a relevant research issue for almond-tree-growing areas worldwide. The intraspecific diversity of this species may constitute a valuable resource to address the resilience and productivity challenges that climate change poses to crop sustainability. A comparative evaluation of physiological and productive performance of four almond varieties: 'Arrubia', 'Cossu', 'Texas', and 'Tuono', field-grown in Sardinia, Italy, was performed. A great variability in the plasticity to cope with soil water scarcity and a diverse capacity to adapt to drought and heat stresses during fruit development were highlighted. The two Sardinian varieties, Arrubia and Cossu, showed differences in water stress tolerance, photosynthetic and photochemical activity, and crop yield. 'Arrubia' and 'Texas' showed greater physiological acclimation to water stress while maintaining higher yields, as compared to the self-fertile 'Tuono'. The important role of crop load and specific anatomical traits affecting leaf hydraulic conductance and leaf gas exchanges efficiency (i.e., dominant shoot type, leaf size and roughness) was evidenced. The study highlights the importance of characterizing the relationships among almond cultivar traits that affect plant performance under drought in order to better assist planting choices and orchard irrigation management for given environmental contexts.

Managing Drought Risk on Lentil Using Deficit Irrigation in Arid Zones

Grain legumes (pulses) are important crops for global food security, especially in developing countries. They also play an important role in enhancing sustainability through intensification and diversification of agricultural production systems. Meanwhile, the deficit irrigation strategy is one of the most important options for reducing water losses and maximizing water use efficiency in arid zones. A 2-year field experiment was conducted in the Agricultural Research Station, Higher Education Complex of Saravan during the growing seasons of 2018 and 2019. The experiment was split plot based on a randomized complete block design (RCBD) with four replications. The main plots included four levels of irrigation (60, 80, 100, and 120%). Subplots were two different landraces from Iran for lentil crop (Baluchestan and Kurdestan). The results revealed that the effect of deficit irrigation was significant on grain yield, biological yield, harvest index, and water use efficiency. Apart from the landraces, with increasing water consumption, the grain yield of control treatment (100%) grew by 107% in comparison to 60% irrigation treatment, but this elevation was not significant at 120% level in comparison to the control treatment. Further, 120% irrigation treatment led to reduction in water use efficiency. The highest water use efficiency (2.9 kg ha-1 mm-1 ) was obtained in 80% irrigation treatment with 10% reduction in grain yield compared with control treatment. The highest harvest index was observed in the interaction of Baluchestan zones × 80% water treatment (0.24). Although the interaction of Baluchestan landrace × 80% water treatment had 10% grain yield lower than control treatment, its biological yield decreased by 27% compared to control treatment, which eventually led to 20% rise of the harvest index. Thus, our study revealed that deficit irrigation was a useful method to protect the water resources and could be used in cultivation of other plants in arid zones.

Maximizing Water Use Efficiency for Faba Bean crop by using Leaky irrigation under El-Baharia Oasis Condition

Maximizing Water Use Efficiency for Faba Bean crop by using Leaky irrigation under El-Baharia Oasis Condition