Deficit Irrigation Research Articles

Drought alters the physiological quality of runner-type peanut seeds during seed formation

Sub-optimal water supply during crop development, especially during peak flowering and pod filling, affects the quality of the produced seeds, generally resulting in poor seed quality. The goals of this study were to identify the acquisition pattern of physiological components in peanut seeds as well as to assess the impact of drought during peanut seed development on its physiological quality. The research was conducted at the USDA-ARS National Peanut Research Laboratory in Dawson, GA for three consecutive years (2019, 2020, and 2021) using field conditions under two water regimes, well-watered control and drought stress. Rainout shelters were used to prevent rain in the drought-stressed block for 30 d, starting 80 d after planting. The well-watered block received supplemental irrigation when soil water potential reached -40 kPa. Peanut pods from the cultivar Georgia-06G were harvested at 2500 growing degree days, and the peanut maturity profile board was used to classify the pods into different maturity classes. Germination, vigor, desiccation tolerance (DT), and longevity tests were performed on seeds from each maturity class and both water regimes. The acquisition pattern for the physiological components of seed quality was developed for seeds grown under well-watered and drought conditions. Maximum germination occurred in ‘brown 1’ and ‘brown 2’ under drought and well-watered conditions, respectively. Both water regimes reached maximum vigor in the 'brown 1'; however, under well-watered conditions, vigor had a rapid decline after ‘brown 1’ while under drought stress, the decline in vigor was slower. Maximum DT was achieved between ‘orange’ and ‘brown 1’ under drought conditions, whereas under well-watered conditions, maximum DT was achieved between ‘brown 2’ and ‘black 1’. Seeds from immature classes had lower capacity to be stored compared with mature seeds. Overall, drought stress promoted greater physiological quality in the peanut seeds than the well-watered treatment. Maximum physiological quality was achieved in the transition from ‘orange’ into ‘brown 1' under drought conditions, and in the transition from ‘brown 2’ to ‘black 1’ class under well-watered conditions. Also, drought stress preserved seed quality for a longer period.

Effect of potassium application on maize to sandy soil under deficit irrigation conditions

Maize is widely growth in arid and semi-arid region where, drought is common and a limiting factor for crop production. Potassium plays a key role in enhancing plant growth under drought condition. The objective of this study is to determine the effect of K fertilization with and without NP on maize growth grown in sandy loam soil under adequate and deficit irrigation conditions. The following treatments were investigated in pot experiment: (1) control with no fertilizer application (C); (2) 128 kg N + 328 kg P2O5 ha-1 (NPK0); (3) 128 kg N + 328 kg P2O5 ha-1 + 152.5 kg K2O ha1 (NPK1); (4) 128 kg N + 328 kg P2O5 ha-1 + 305 kg K2O ha-1 (NPK2); and 128 kg N + 328 kg P2O5 ha-1 + 457.5 kg K2O ha-1 (NPK3). Treatments were investigated under adequate and deficit soil moisture content. Each pot filled with 3.5 kg air-dry soil and seeded with maize and pots were watered according to the treatments. The results indicated that plant growth and nutrient uptake were significantly reduced under water stress condition. The application of NP increased plant growth and nutrient uptake and further were increased with K application. K application also enhanced plant tolerance to deficit soil moisture condition. In addition, K enhanced nutrient uptake and leaf chlorophyll content. Based on the results, it can be concluded that application of NP for maize was not adequate to achieve the highest plant growth, unless it is combined with K application. In addition, K application enhances plant tolerance to water stress.

TiO2 NPs as a Promising Strategy for Crop Conservation Resulting from Deficit Irrigation in Fragaria × ananassa Cv. Camarosa

ABSTRACT Nanoparticle-based methods can compensate for yield and quality loss of crops affected by drought. The current study, performed in a factorial experiment based on a completely randomized design, addressed to evaluate the effect of titanium dioxide nanoparticles (TiO2 NPs) at 0, 10, 20, and 30 mg L−1 under three irrigation regimes (full irrigation, partial root drying (PRD), and sustained deficit irrigation (SDI)) on Fragaria × ananassa cv. Camarosa. Results revealed that the PRD stress had more adverse effects on F. ananassa cv. Camarosa than SDI stress. Assessment of the behavior of TiO2 NPs in this study elucidated that mean productivity, yield stability index, and fruit number in plants grown under full irrigation increased when treated with 10 mg L−1 TiO2 NPs. Under the deficit irrigation, including PRD and SDI, all levels of TiO2 NPs mitigated mean productivity and yield stability index by ameliorating the fruit number and water use efficiency (WUE) and decreasing transpiration. Flowering and fruit set times were reduced by TiO2 NPs and deficit irrigation while their periods were enhanced by ones. It seems that when the strawberry was exposed to TiO2 NPs exhibited approximately drought tolerance. These nanoparticles ameliorated photosynthesis and mineral uptake and allocated dry matter to the root. These alterations can contribute to crop production in deficit irrigation strategies.

Alfalfa potassium and phosphorus uptake and use efficiencies as impacted by irrigation technology, deficit irrigation, and alfalfa cultivar

AbstractAs competition for limited water resources in the western United States and other arid and semiarid regions intensifies, there is a need to provide alfalfa (Medicago sativa) growers with knowledge of how water‐optimizing practices impact alfalfa nutrient use. The objective of this research was to evaluate how three water management strategies, and their interactions, influence alfalfa K and P concentration, uptake, uptake efficiency, and internal use efficiency. Alfalfa cultivars, deficit irrigation, and irrigation technologies were tested at two sites in Utah during 2020–2021. A single drought‐tolerant (DT) cultivar (‘Ladak II’) was compared to a conventional alfalfa cultivar specific to each location. Four irrigation rates (100%, uniform reductions of 25% and 50%, and a targeted reduction of ∼50%) were nested within five pivot irrigation technologies. Few alfalfa K and P nutrient dynamics responded to the interactions of cultivar and rate or technology. Nutrient responses to the irrigation technologies were strongly associated with the technology effect on alfalfa yield such that uptake efficiency was sometimes greater with low‐elevation sprinkler technologies. The K and P responses to deficit irrigation were most pronounced at the uniform or targeted 50% irrigation rate. Alfalfa cultivar had the least impact on alfalfa K and P dynamics, and the DT cultivar never improved uptake or efficiencies. These results indicate that few adjustments in K and P management may be needed with the three water optimization approaches evaluated in this study. The most notable is that K and P fertilizer input can likely be reduced with severe deficit irrigation.

Potential of sustained deficit irrigation to enhance biological and nutritional quality of pomegranate fruit during storage

BackgroundWhile water availability is important for quality at harvest, it also continues to influence the quality of pomegranates during storage. Reducing the amount of irrigation, in addition to water saving has different effects on bioactive compounds of pomegranate during storage time. This study was conducted to determine the influence of irrigation level on fruit quality changes during storage period of two commercial Iranian pomegranate cultivars (‘Shishecap’ and ‘Malas-Yazdi’). Sustained deficit irrigation (SDI) was applied to plants that received 75% (moderate stress) or 50% (severe stress) of their normal water requirement. A control group received 100% of their water requirement.ResultsAt harvest time and during storage period, fruit weight loss and some biochemical traits such as fruit total soluble solids (TSS), titratable acidity (TA), pH, total phenolic compounds (TPC), total anthocyanins content (TAC), antioxidant activity and vitamin C were measured in pomegranate fruits. Also, the quantity of the produced product was also measured at the time of harvesting. Results indicated that control fruits exhibited more weight loss than those produced under water deficit during the storage period in both years. According to results, fruit TSS, TAC, and antioxidant activity significantly increased during storage period but fruit TA and vitamin C significantly decreased throughout storage period. Also, reduction in irrigation level resulted in a decline in the yield.ConclusionsThis study revealed a crucial link between irrigation level and the quality of pomegranate fruits, despite a reduction in the yield. This included affecting weight loss and the content of bioactive compounds, both at harvest and during storage.

Combined application of silica nanoparticles and brassinolide promoted the growth of sugar beets under deficit irrigation

Silica nanoparticles (SiNPs) and brassinolide (BR) have been used as nano-fertilizer and growth regulator, respectively to enhance crop tolerance to abiotic stress. However, it is unclear whether a combination of the two (BR+SiNPs) is more beneficial than single application of BR or SiNPs to improve the growth of deficit-irrigated sugar beets. In this study, a two-year (2022-2023) field experiment was conducted to investigate the effects of foliar spraying of water (CK), SiNPs, BR, and BR+SiNPs on the antioxidant defense, photosynthetic capacity, dry matter accumulation, nutrient uptake, and yield of sugar beets under full irrigation (100% of crop evapotranspiration (ETc), W1) and deficit irrigation (60% ETc, W2). The results showed that compared with the application of BR or SiNPs, the application of BR+SiNPs could enhance the antioxidant defense, osmoregulation, and photosynthesis of the full-irrigated and deficit-irrigated sugar beet leaves, and ultimately improved the water status, growth, and yield of sugar beet plants. There was no significant difference in the net revenue (NR) between BR+SiNPs treatment and CK under W1 conditions. However, the NR of the BR+SiNPs treatment increased by 27.0% (p < 0.05) compared with that of CK under W2 conditions, and there was no significant difference in NR between BR+SiNPs and SiNPs treatments. A comprehensive evaluation using entropy weight combined with technique for order preference by similarity to ideal solution method found that under deficit irrigation condition, spraying SiNPs could improve the growth of sugar beet, increase the TY, NR, and water use efficiency, and reduce costs compared with spraying BR+SiNPs. Therefore, foliar spraying of SiNP on deficit-irrigated sugar beets can be used to improve sugar beet growth and reduce the potential economic losses caused by deficit irrigation.

Assessing grapevine water status through fusion of hyperspectral imaging and 3D point clouds

Mild to moderate and timely water deficit is desirable in grape production to optimize fruit quality for winemaking. It is crucial to develop robust and rapid approaches to assess grapevine water stress for scheduling deficit irrigation. Hyperspectral imaging (HSI) has the potential to detect changes in leaf water status, but the robustness and accuracy are restricted in field applications. The varied leaf orientations can significantly affect how light interacts with the plant, ultimately influencing the reflectance properties. This study focused on developing an approach for detecting grapevine water status using HSI and 3D data. Leaf orientation parameters derived from 3D point clouds were integrated with spectral signatures to address the spectral variance caused by variations in leaf orientation. A water status assessment model was developed based on multiblock partial least squares (MBPLS) to estimate midday leaf water potential (ΨL) using spectral signatures and leaf orientation parameters. HSI and 3D point clouds of selected leaves were captured simultaneously in a vineyard during the 2021 growing season, and ΨL was measured as the ground truth to assess the model performance. Mean spectral reflectance was derived from the hyperspectral images, while leaf orientation parameters were extracted from 3D point cloud data. The dataset was split randomly into 70% training/calibration and 30% test datasets. The test result shows that the model estimated the ΨL with R2 = 0.89, RMSE=0.12 MPa and MAE=0.09 MPa. The leaf orientation parameters derived from 3D point clouds had a contribution of 6.25% in estimating ΨL. Moreover, it acted as an enhancing component that explained the spectral variance caused by variations in leaf orientation and improved the interpretation of the underlying relationship between spectral reflectance and vine water status.

Effects of deficit irrigation on potato yield and water productivity in northern Ethiopia

Effects of deficit irrigation on potato yield and water productivity in northern Ethiopia

Impact of regulated deficit irrigation on the dynamics of quality changes in processing tomato fruits during ripening

Quality is a key factor restricting the development and economic benefits of the tomato processing industry, and improving the quality of tomatoes has become a hotspot in the development of the tomato processing industry in Xinjiang. Regulated deficit irrigation (RDI) is an abiotic means of crop yield and quality control widely used for crop yield and quality improvement. This study aimed to investigate the impact of RDI on the dynamics of quality changes in processing tomato fruits during ripening via a 2-year (2022–2023) filed experiment with five water irrigation treatments in Xinjiang, China. The results showed that compared with conventional irrigation, regulated deficit irrigation significantly saved 315–1260 m3 ha−1 irrigation water. Mild RDI increased the single fruit weight and fruit hardness by 0.15 % and 3.29 kg cm2, respectively, thus improved the yield and storage and transportation quality of processed tomatoes. Moderate RDI increased the contents of soluble solid, soluble sugar and lycopene in fruit to 0.6 %, 0.56 % and 3.53 μg/g, respectively, therefore significantly improved the nutritional quality and flavor quality of processed tomato. Ultimately, a comprehensive evaluation using a coupled Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model, taking into account the appearance, nutrition, flavor, and storage and transportation indexes of processed fruits, concluded tha W1 treatment is a sustainable water management approach that balances yield and quality. Therefore, the optimal deficit irrigation model for processing tomato fruits in Xinjiang was recommended to be the W1 treatment, whereas the W2 treatment was considered as an alternate model. The study supported the large-scale development of the tomato processing industry in Xinjiang and the implementation of effective water-saving farming.

Enhancing growth and tolerance traits in pepper (Capsicum annuum L.) through water-saving irrigation practices

Due to their intensive cultivation, horticultural crops are particularly susceptible and vulnerable to the detrimental effects of drought stress, necessitating significant water inputs for optimal growth and yield. Accordingly, water-saving irrigation strategies, i.e., Partial Root zone Drying (PRD) and Regulated Deficit Irrigation (RDI) emerge as pivotal tools for bolstering the resilience of the horticultural sector. The current study aims to evaluate the impact of PRD and RDI strategies on pepper (Capsicum annuum L.) growth, and physio-biochemical attributes under semi-controlled greenhouse conditions. Research findings revealed pronounced enhancements in stem length under both irrigation strategies, with PRD exhibiting superior effects on shoot fresh and dry biomass (increases of 57.2% and 61.1%, respectively) compared to full irrigation. At the physiological level, PRD and RDI induced a significant reduction in stomatal conductance in pepper plants relative to full irrigation, while maintaining leaf water potential and relative water content. Biochemically, plants subjected to PRD and RDI methods exhibited significant accumulation of free proline, particularly pronounced with PRD (approximately 115.9% increase compared to full irrigation). Furthermore, Chl a and carotenoid concentration significantly increased under PRD, indicating sustained photosynthetic functionality. Comparatively, PRD appears as the more effective technique, offering the potential to conserve agricultural water about 50 without compromising growth parameters, while simultaneously enhancing tolerance traits in C. annuum. Nonetheless, further investigations on other traits across diverse soil types, climates, and cultivars under field conditions are imperative to ascertain the broader applicability of PRD and optimize its implementation.

Economic Analysis of Dairy Farming under Drought Prone Area in Maharashtra State of India

Background: Dairy farming is a cornerstone of the rural economy in India. Maharashtra, particularly its drought-prone districts, is critical in this sector. Despite challenges posed by erratic monsoons and limited irrigation, dairy farming remains a viable strategy for economic stability in these regions. The aim of this study was to examine the financial aspects of dairy enterprises, focusing on socio-economic characteristics, economic viability and constraints faced by farmers. Methods: The study employed a multistage stratified random sampling method. Key analytical tools included average and percentage calculations, BEP analysis and a Cobb-Douglas production function. Additionally, Garrett’s ranking technique was used to ascertain constraints in dairy farming, while the MOTAD model assessed profitability and risk. Result: The findings reveal that crossbred cow milk production is more lucrative than buffalo milk production, despite its higher average total expenditure per lactation. Break-even analysis confirmed profitability for both types of milk producers. Key determinants of milk production, such as green fodder, concentrate and labour, suggest areas for efficiency enhancements. Farmer-identified constraints include high feed costs, insufficient veterinary services and water scarcity. Utilizing the MOTAD model, the study recommends integrating dairy farming with crop cultivation to maximize returns, mitigate risks and enhance overall farm resilience in challenging environmental conditions.

Effect of Delayed Irrigation at the Jointing Stage on Nitrogen, Silicon Nutrition and Grain Yield of Winter Wheat in the North China Plain.

Water scarcity is a key limitation to winter wheat production in the North China Plain, and it is essential to explore the optimal timing of spring irrigation to optimize N and Si uptake as well as to safeguard yields. The aim of this study was to systematically study the effect mechanism of nitrogen and silicon absorption of winter wheat on yield under spring irrigation and to provide a scientific basis for optimizing irrigation strategy during the growth period of winter wheat. In this experiment, the winter wheat 'Heng 4399' was used. Five irrigation periods, i.e., 0 d (CK), 5 d (AJ5), 10 d (AJ10), 15 d (AJ15), and 20 d (AJ20) after the jointing stage, were set up to evaluate the nitrogen (N) and silicon (Si) absorption and grain yield (GY). The results showed that delayed irrigation for 5-10 days at the jointing stage had increased the GY. With the delay of irrigation time, the N/Si content of the entire plant at the maturity period increased first and then decreased; among that, the maximum N contents appeared in AJ15 and AJ5 in 2015 and 2020, respectively, while the Si concentrations appeared in AJ5 and AJ10 in sequence. Compared with AJ15 and AJ20, the N accumulation of vegetative organs in AJ5 increased by 3.05~23.13% at the flowering stage, 14.12~40.12% after the flowering stage, and a 1.76~6.45% increase in the N distribution rate at maturity stage. A correlation analysis revealed that the GY was significantly and positively correlated with the N/Si accumulation at the anthesis and N translocation after the anthesis stage. In conclusion, under limited irrigation conditions, delaying watering for 5 to 10 days at the jointing stage can improve the nitrogen and silicon absorption and nutrient status of wheat plants and increase wheat yield.

Two Genotypes of Tomato Cultivated in Gobi Agriculture System Show a Varying Response to Deficit Drip Irrigation under Semi-Arid Conditions

Water-saving irrigation is of extraordinary importance for tomato production in semi-arid areas of northwest China. For this purpose, we conducted a two-season trial in a solar greenhouse of two tomato genotypes named ‘181’ and ‘Mao Fen 802’ and cultivated with substrate, under four irrigation regimes, i.e., well-watered (WW), low (LWD, 80% WW), moderate (MWD, 60% WW) and high (HWD, 40% WW) water deficit. The substrate water content of WW treatment was 75%θf to 90%θf (where θf is the field capacity). The study results showed that the single fruit weight and yield of tomato were significantly declined with an increasing water deficit degree. Compared to WW treatment, the fruit weight and yield were decreased about 34.45% and 20.35% for ‘181’ and ‘Mao Fen 802’ under HWD treatment, respectively. Conversely, water deficit treatment led to an obvious promotion of WUE and showed an upward trend as the water deficit level increased. In addition, compared to WW treatment, the water deficit significantly decreased the total flavonoids of the ‘181’ tomato by 24.4–93.1%, whereas there was no significant impact on that of ‘Mao Fen 802’. Nonetheless, different individual polyphenols were increased by suitable deficit irrigation for two tomato cultivars. Gallic acid, 3,4-dihydroxybenzoic acid, and naringin of ‘181’tomato were increased by 128.4–195.2%, 8.6–43.7%, and 31–73-fold, respectively, under water deficit compared to WW treatment. Further, under water deficit treatment, p-coumaric acid, benzoic acid, and 3,4-dihydroxybenzoic acid of ‘Mao Fen 802’ were increased by 36.2–49.2%, 59.1–189.7%, and 36.3–106.4% compared to WW treatment. As the main carotenoid component, the lycopene content of tomato fruit exhibited a significant rise of 7.84–20.02% and 20.55–32.13% for ‘181’ and ‘Mao Fen 802’ under three degrees of water deficit compared to WW treatment. Linear regression showed a significantly positive relationship between irrigation amounts and yield, and total polyphenols, whereas there was a significantly negative relationship between irrigation amounts and WUE, and total carotenoids. Based on correlation and PCA, WW and LWD, and MWD and HWD, were gathered together for ‘181’, while LWD, MWD, and HWD, were gathered, and only WW scattered for ‘Mao Fen 802’, along the PC1 direction. It was proposed that ‘Mao Fen 802’ was more sensitive to water deficit than the ‘181’ tomato. In conclusion, water deficit is conductive to water-saving cultivation of the greenhouse tomato and the tomato genotypes, and water deficit level is a key factor necessary for consideration.

Harvesting Rainwater and Utilizing for Supplemental Irrigation to Enhance Crop Productivity under Rainfed Conditions: A Case Study of North Eastern Ghats Zone of Odisha

Rainwater harvesting-cum-supplemental irrigation is an important strategy to enhance crop water productivity under rainfed conditions. This study was conducted to assess efficacy of farm pond in harvesting rainwater and utilizing for irrigation to okra-radish cropping sequence during 2018-19 and 2019-20 at Phulbani, Odisha. In this study, runoff harvested from a catchment area of 0.5 ha and stored in farm pond was quantified. Also, seepage and evaporation losses from the farm pond were determined along with computation of area that could be irrigated from the stored water. Three irrigation treatments were considered, namely, T1 – life-saving irrigation to okra and one protective irrigation of 5 cm to radish, T2 –life-saving irrigation to okra and two protective irrigations of 5 cm each to radish, T3 – control without any protective irrigation. Rainwater harvesting potential of the study areavariedfrom8.3% to 8.9% of rainfall. Evaporation and seepage losses from the pond varied from30.6% to27.4% and from18.21% to 17.4% during 2018 and 2019, respectively. About 26.35% and 24.8% of the harvested rainwater was utilized for providing life saving irrigations to 0.4 ha cropped area during Kharif and Rabi seasons in 2018 and 2019, respectively. Treatment T2 consisting of one life saving irrigation to okra and two irrigations to radish resulted in the highest okra equivalent yield (OEY) of 10,156 kg ha-1 and 10,228 kg ha-1during 2018 and 2019, respectively. Crop water productivity was found to be the highest, i.e.,0.63 and 0.632 kg m-3 during 2018 and 2019, respectively for treatment T2. Therefore, pond water can be used for providing life-saving irrigation to the vegetable crops, which resulted in higher returns due to increased crop yields. It will also be possible for the farmers to go for the second crop in Rabi season.

Assessment of CROPWAT 8.0 model accuracy under deficit irrigation scheduling: A sustainable path toward smart water supply

ABSTRACT As the world confronts mounting challenges to water security, efficient irrigation becomes ever more critical. Escalating water scarcity challenges necessitate innovative smart irrigation solutions. This study investigates the potential of integrating deficit irrigation (DI) with the CROPWAT 8.0 model for sustainable and water-productive irrigation. This research evaluated the model's accuracy in generating DI schedules at 70% field capacity (FC) (T1) compared to schedules derived from frequency domain reflectometry (FDR) soil moisture sensors at 70% FC (T2). The results demonstrated economic viability and strong accuracy for T1 with consistently lower values of mean absolute error (3.6165 and 4.3987) and root mean square error (4.4447 and 5.5055) while compared to T2 across two years. In addition, T1 achieved significant water savings (43.47 and 45.16%) alongside higher water productivity (8.11 and 8.22 kg m−3), respectively, for both the years compared to full irrigation (FI). These findings highlight CROPWAT 8.0 model–driven DI scheduling as a promising smart irrigation approach for tackling water scarcity, offering economic benefits to farmers while promoting water security.

Innovation in Agriculture Advantages of a Remote Irrigation Monitoring and Control System

Globally, the irrigation of crops is the largest consumptive user of water. Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. This necessitates the development of irrigation practices that are more efficient in the use of water but do not compromise crop quality and yield. Precision irrigation already achieves this goal, in part. The goal of precision irrigation is to accurately supply the crop water need in a timely manner and as spatially uniformly as possible. However, to maximize the benefits of precision irrigation, additional technologies need to be enabled and incorporated into agriculture. This Search discusses how Advantages of a remote irrigation monitoring and control system irrigation management will enable significant advances in increasing the efficiency of current irrigation approaches. From the literature review, it is found that precision irrigation can be applied in achieving the environmental goals related to sustainability. The demonstrated economic benefits of precision irrigation in field-scale crop production is however minimal. It is argued that a proper combination of soil, plant and weather sensors providing real-time data to an adaptive decision support system provides an innovative platform for improving sustainability in irrigated agriculture. The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil–plant–atmosphere system while considering operational limitations and agronomic objectives in arriving at optimal irrigation decisions. It is concluded that significant improvements in crop yield and water savings can be achieved by incorporating model predictive control into precision irrigation decision support tools. Further improvements in water savings can also be realized by including deficit irrigation as part of the overall irrigation management strategy. Nevertheless, future research is needed for identifying crop response to regulated water deficits, developing improved soil moisture and plant sensors, and developing self-learning crop simulation frameworks that can be applied to evaluate adaptive decision support strategies related to irrigation.

Evaluation Tolerant of Four Melon Genotypes in Early Growth Stage under Normal and Drought Stress Conditions

Plant breeding initiative in semi-arid and arid area are primarily focused on developing genotypes at early growth stage under normal conditions and keeping them steady during drought stress conditions. Therefore, four melon genotypes responses to drought stress were evaluated in this study during early growth stage. Two treatments for irrigation rates (Full Irrigation= 100%) and (Deficit Irrigation= 50%) were carried out in randomized complete block design (RCBD) with three biological replications in vermiculite culture in greenhouse in the research farm of faculty of agriculture at Sohag university in Egypt during season 2023. Young plants (45 days old plants) were utilized, and phenotypic traits 1º Leaf Score Tolerance, 2º Leaf Score Tolerance, Flowers Numbers, Vine Length, Green Leaves and Brown Leaves Numbers per vine were calculated by comparing differences in drought stress compared to control to identify tolerant and susceptible genotypes. The findings demonstrated that, in all estimated traits under drought stress conditions, there was significant variation between the studied four melon genotypes. whereas, the best results for all the studied traits were produced under normal conditions. Additionally, the highest significant positive correlation was found between 1º Leaf Score Tolerance and 2º Leaf Score Tolerance (0.966*) under normal conditions, and between Vine Length and Green Leaves Numbers per vine (0.999**) under drought stress conditions. Furthermore, the highest significant negative correlation was observed between 2º Leaf Score Tolerance and Flowers Numbers (-0.974*) and Flowers Numbers and Green Leaves Numbers per vine (-0.960*) under normal conditions, and between Vine Length and Brown Leaves Numbers per vine (-0.974*) and Green Leaves Numbers per vine and Brown Leaves Numbers per vine (-0.981*) under drought stress conditions. Besides, Euclidean heatmap clustering analysis grouped studied genotypes according to their response to normal and drought stress conditions, indicating that, the studied melon genotypes offer high potential for particular breeding purposes. These results have produced helpful framework for breeding strategies in the future under drought stress conditions. Conversely, detailed studies are crucial to predict drought stress tolerance performance in novel breeding strategies.

Long-term potato response to different irrigation scheduling methods using saline water in an arid environment

Crops’ water requirement is generally higher than the annual average precipitation in arid environments characterized by scarce freshwater resources. While using saline water for irrigation can help sustain agriculture in water-stressed regions, several challenges arises concerning productivity and soil salinization. However, adoption of efficient irrigation techniques such as drip irrigation, irrigation scheduling, and deficit irrigation can help optimize water productivity and mitigate salinity problems in irrigated agriculture. In southern Tunisia, potato is considered among the main cultivated horticultural crops due to its high economic value while it is considered as a crop sensitive to salinity. This crop (cv. Spunta) was the subject of long-term studies (2002–2020) conducted during the fall period in the arid region of Médenine. The crop response to full and deficit irrigation with saline water was assessed for several seasons under contrasting climatic conditions. Scheduling using the soil water balance (SWB) method consisted of the total and/or partial replacement of accumulated crop evapotranspiration (ETc), as derived from climatic data and crop coefficients. The impact of decreasing amounts of irrigation waters on crop yield and soil salinity with waters having a salinity ranging between 3 and 7 dS m−1 was evaluated. Results showed improvements in yield (30% to 37%) obtained with the SWB strategy under actual farming conditions, supporting the use of this strategy for irrigation. Appropriate scheduling also seems to be a key element in saving water (15%–22%) and in reducing risks of soil salinization. In the dry environment of southern Tunisia, optimum supply seems to correspond to a replacement of 100% to approximately 70%–80% of ETc. Applying such irrigation levels resulted in a lower salinity buildup in the root zone and higher crop water productivity. Natural salt leaching seems to be more effective under a more humid soil profile. Yield decreases and soil salinity increases almost linearly (r2 = 0.60) with decreasing irrigation water amounts. Future work should focus on the integration of management practices when using saline water. Investigating the relationship and interaction between irrigation amounts, cultivar, fertilizer supply, and salt leaching will help in resolving productivity and environmental issues.

Improving soil moisture prediction with deep learning and machine learning models

Reliable soil moisture (SM) data is critical for effective water resources management, yet its accurate measurement and prediction remain challenging. This study was conducted to develop a deep learning regression network for sub-hourly SM prediction and compare its performance with traditional machine learning models, including the eXtreme gradient boosting (XGB), light gradient-boosting (LGB), cat boosting (CB), random forest (RF), k-nearest neighbors (kNN), and long short-term memory (LSTM) models. Sub-hourly SM, electrical conductivity (EC), soil temperature (ST), and weather parameters were collected during research experiments conducted for two years (2020–2021 and 2021–2022) at the Tropical Research and Education Center (TREC), University of Florida. A network of SM sensors and a weather station were installed at the experimental site with 24 plots of green beans and sweet corn under full and three deficit irrigation treatments with three replications. Model performance metrics such as coefficient of determination (r2) and global performance indicator (GPI) were used to evaluate the performance of the models. Results showed that all MLs and DL models performed more than satisfactorily in simulating SM of green beans and sweet corn plots. The testing average r2 and GPI of MLs were 0.83 and 0.02 (green beans) and 0.85 and 0.02 (sweet corn). However, XGB and LGB models outperformed the remaining ML and DL models. The testing r2 and GPI of XGB were 0.86 and 0.014 for green beans, whereas 0.88 and 0.015 for sweet corn. The r2 and GPI values for the LGB were 0.85 and 0.014 for green beans, while 0.88 and 0.015 for sweet corn. Even though DL model took longer and resources to be trained, its performance was not as accurate as that of XGB and LGB models. However, the performance of DL was better than the LSTM model. The r2 and RMSE of the LSTM model were 0.68 and 0.02cm 3 cm-3 for green beans and 0.75 and 0.02cm 3 cm-3 for sweet corn, respectively. Whereas the r2 and RMSE of DL were 0.84 and 0.015cm 3 cm-3 (green beans) and 0.85 and 0.02 cm 3 cm-3 (sweet corn). The ML and DL models performed better in simulating SM of sweet corn plots than green beans. Overall, these results confirmed that the ML and DL models could be alternative tools for SM prediction for agricultural fields, with potential applications for irrigation scheduling and water resources management.

The Efficiency of Different Supplementary Irrigation Techniques After Nickel-Titanium Rotary System in Endodontic Retreatment

Objective: To assess the efficiency of XP-Endo Finisher file (XPFF), EDDY, and diode laser as supplementary irrigation activation techniques following nickel-titanium rotary files in the endodontic retreatment. Methods: 48 mandibular premolars were collected. Each root canal was shaped and filled with EndoSequence BC sealer and gutta percha. After 14 days, endodontic retreatment was performed using D-Race instruments. Then, 48 samples were assigned into 4 groups (n=12) as control, diode laser, EDDY, and XPFF according to the supplementary irrigation methods. After the irrigation procedure, all samples were visualized under a stereomicroscope. The remaining root filling material was scored and compared statistically using Kruskal-Wallis and Post-hoc pairwise comparison tests. Results: In all thirds, there was a significant difference between the diode laser and control groups. The amount of remaining filling material in the diode laser group was significantly lower than in the control group. When the other groups were compared, a significant difference was observed only between the diode laser and XPFF groups in the coronal third. Conclusion: No supplemental method could eliminate the root obturation material. The diode laser can be used in addition to nickel-titanium rotary retreatment systems to improve the removal of gutta percha and bioceramic sealer.