Levels Of Water Stress Research Articles

Emerging Materials in Photo-bio catalytic systems for Futuristic Wastewater Treatment

By the end of the year 2040, the water stress score reveals that 33 countries including the middle east and developed countries like Singapore and San Marino would be facing high levels of water stress. A critical issue that has to be addressed in the coming decades would be sustainable water management. Water’s abundance makes it an ideal universal solvent for cleaning and flushing. This incorporates numerous natural and anthropogenic activities that have imparted pollution which highly affects the quality of water. Though remediation process is available they are slow, hence sophisticated reactors are employed to speed up the treatment process more sustainably and effectively. Several different designs of bioreactors are being developed to treat diverse categories of wastewater and their effluents. The most recent ones are the coupling of photocatalysis and bioreactors. The combined advantages of nanoparticles to be highly oxidizing and non-selective while that of micro-organisms to be economical and sustainable couples these different techniques in one system. Although such system possesses challenges such as lack of process knowledge, design limitation, and characteristic differences, but do have several advantages when considering their applications in the treatment of wastewater and emerging pollutants. In this study, cotton processing wastewater has been treated by a coupled photo-catalytic bioreactor containing nanoparticles and algal biomass for 15 days, and >80% COD removal efficiency was noted by the microalgae Chlamydomonas sp whereas maximum removal of 88% and 84% COD was observed by using Titanium dioxide, and Palladium doped tungstate under solar light and visible light source respectively. An effort is made to delineate the efficiency, limitations, and future readiness of these systems for the abatement of priority pollutants (with emphasis on cotton processing wastewater). A timely investigation of such emerging technologies promotes progress, provides theoretical insights, and deciphers principles for future application of this technology for wastewater treatment.

Exploring the relationship between leaf water potential, defoliation, and grape berry physical properties of Merlot (Vitis vinifera L.) grapevine

The aim of this study was to examine the impact of leaf water potential and defoliation treatments on the physical properties of grape berries. The research was conducted over two consecutive years (2019-2020) using ‘Merlot’/41B graft combination grapevines grown in the Chateau Kalpak vineyards located in Tekirdağ, Şarköy. The experiment involved four distinct water stress levels (S0, S1, S2, and S3), which were determined based on leaf water potential measurements. These stress levels were subjected to different irrigation levels. Additionally, defoliation treatments were applied, including Control (C), Full Window (FW), Right Window (RW), and Left Window (LW). The results showed that the effects of water stress and defoliation treatments on berry physical properties were statistically insignificant. However, in the second year of the study, the FW treatment was observed to have led to changes in the desired direction for grapevines. This was likely due to the cumulative decrease in water reserves caused by reduced precipitation over multiple years, making the effects of FW treatment more prominent. Moreover, the study found that both current and past vegetation period conditions influence vine production year, leaf water potentials (Ψleaf), and stress levels. Finally, the data revealed that berry weight and % dry weight increased with higher stress levels.

A deep neural network with electronic nose for water stress prediction in Khasi Mandarin Orange plants

Water stress is a significant environmental factor that hampers plant productivity and leads to various physiological and biological changes in plants. These include modifications in stomatal conductance and distribution, alteration of leaf water potential & turgor loss, altered chlorophyll content, and reduced cell expansion and growth. Additionally, water stress induces changes in the emission of volatile organic compounds across different parts of the plants. This study presents the development of an electronic nose (E-nose) system integrated with a deep neural network (DNN) to detect the presence and levels of water stress induced in Khasi Mandarin Orange plants. The proposed approach offers an alternative to conventional analytical methods that demand expensive and complex laboratory facilities. The investigation employs the leaf relative water content (RWC) estimation, a conventional technique, to evaluate water stress induction in the leaves of 20 plants collected over a span of 9 days after stopping irrigation. Supervised pattern recognition algorithms are trained using the results of RWC measurement, categorising leaves into non-stressed or one of four stress levels based on their water content. The dataset used for training and optimising the DNN model consists of 27 940 samples. The performance of the DNN model is compared to traditional machine learning methods, including linear and radial basis function support vector machines, k-nearest neighbours, decision tree, and random forest. From the results, it is seen that the optimised DNN model achieves the highest accuracy of 97.59% in comparison to other methods. Furthermore, the model is validated on an unseen dataset, exhibiting an accuracy of 97.32%. The proposed model holds the potential to enhance agricultural practices by enabling the detection and classification of water stress in crops, thereby aiding in water management improvements and increased productivity.

Biochemical and physiological mechanisms allowing olive trees to survive and produce under water stress conditions

The beneficial properties of olive (Olea europaea L.) edible fruits and their oil play an important part in our diet. Severe summer conditions, including low rainfall, excessive heat load and high daily irradiance, characterize arid and semiarid regions where olive is produced. Although it is highly aggravated by other stresses, water stress is usually the most critical during summer-time. Under severe water stress conditions, a cultivar of any olive tree needs specific biochemical and physiological mechanisms in order to survive and be productive. It is well-known that these water stress resistance mechanisms generally act simultaneously. Nevertheless, water stress adaptability not only integrates the water stress resistance concept (i.e., escape, avoidance and/or tolerance to water stress) but also the recovery capacity. All of them play a major role in plants’ growth and survival, especially when plants are continuously exposed to repeated events of water stress and adequate water levels during their lifetime. Water stress, heat and high irradiance, especially in association with each other, also damage plant functions. As a result, different resistance mechanisms are adopted by plants. This review summarizes each of these mechanisms.

Germination ecology and seedling growth of invasive Ageratum species and allied native Adenostemma lavenia

AbstractThe success of invasive plants can be better understood by comparing their traits with closely related native species. This study compared germination ecology and seedling growth of invasive Ageratum houstonianum and Ageratum conyzoides with co‐occurring and allied native Adenostemma lavenia. Seeds were germinated under a different light (12 h photoperiod/complete dark), temperatures (low: 25°C/15°C day/night, and high: 30°C/20°C), and different levels of water stress (−0.1, −0.25, −0.5, −0.75, and −1 MPa). Seedlings were grown to determine biomass allocation, relative growth rate (RGR), plant height, and number of leaves. The seed mass and size of native A. lavenia were higher than those of invasive species. Seeds of all species were positively photoblastic. At low temperature and in all levels of water stress, all measured parameters except mean germination time were the highest in A. houstonianum. However, at high temperature, there was no significant difference in germination percentage between A. houstonianum and A. lavenia. No germination of A. conyzoides and A. lavenia was recorded beyond −0.5 MPa water potential, but seeds of A. houstonianum germinated up to −0.75 MPa. A. houstonianum had higher root mass fraction, root‐to‐shoot ratio, and number of leaves than the other two species. Stem mass fraction and the height of seedling were highest in A. conyzoides. The RGR was 1.6 times higher in invasive Ageratum species than the native species; it was slightly higher in A. houstonianum than in A. conyzoides. Overall, the results suggest that germination traits and seedling growth performance can be used as predictors of a species' invasiveness.

Drivers of chaparral photosynthetic rate reduction under modern drought conditions

Terrestrial vegetation communities are experiencing rapid and novel changes to photosynthetic rates under the changing climate. Chaparral, a semi-arid shrubland ecosystem of the Southwestern United States and Northern Mexico, is projected to experience substantial increases in aridity and stochastic precipitation. This study identifies the primary meteorological drivers of photosynthesis for three widespread chaparral shrub species—Adenostoma sparsifolium, Adenostoma fasciculatum, and Ceanothus perplexans—from 2019 to 2021. Monthly leaf-level carbon exchange rates, water potentials (WPs), and meteorological conditions were collected for each species. Average monthly primary productivity (n = 25) demonstrated vapor pressure deficit (VPD) as a significant limit to photosynthetic rates for A. sparsifolium and A. fasciculatum. VPD was also the most influential predictor of WP for all three species. These results suggest increasing atmospheric dryness as a key predictor for reduction in chaparral primary productivity, particularly for deeply-rooted, resprouting species. There are additional indications that VPD could exacerbate drought-related mortality for C. perplexans and A. sparsifolium by pushing WP to novel extremes. This study concludes that atmospheric dryness, across 3 years of differing soil water stress levels, was consistently a substantial physiological limitation for three common, chaparral species. Although this experiment occurred over a limited window and cannot assess climatic response trends, acute increases in air temperature and VPD within the region would exacerbate photosynthetic limitation for these species and may contribute to declining primary productivity in broader chaparral ecosystems.

Functional adjustment under lethal drought and physiological memory to water stress of two phylogenetically close and coexisting conifers

Forest die-off can primarily affect the least drought-tolerant species and mortality be modulated by physiological legacies left by drought. To characterize the functional response and physiological memory to water stress of two phylogenetically and functionally close conifers with current contrasting field mortality and regeneration dynamics, we conducted a drought experiment in which seedlings were driven to death. Both species exhibited isohydric behavior with small hydroscapes. Yet, hydraulic performance, osmotic adjustment and gas exchange dynamics under rising water stress consistently showed that Pinus pinea was more resistant to drought than Pinus pinaster. Under water stress, P. pinaster exhibited greater water use efficiency, but higher photochemical damage and more constrained photosynthetic and stomatal conductance dynamics than P. pinea. Xylem conductivity loss under water stress and the wilting point were lower in P. pinea. Osmotic potential at full turgor decreased in P. pinea but it increased in P. pinaster with increasing water stress below a water potential threshold. Consequently, lethal water stress levels were higher for P. pinea than for P. pinaster. Synergistically, cumulative water stress induced physiological legacies curtailing carbon uptake and hydraulic performance in both species. Negative physiological legacies left by memory to water stress in plants, might explain delayed tree mortality years after drought. The functional responses to drought characterized agree with current field demographic dynamics under climate change in mixed evergreen forests where more drought-tolerant taxa like P. pinea are replacing formerly dominated P. pinaster stands.

Responses of different invasive and non-invasive ornamental plants to water stress during seed germination and vegetative growth

Biological invasions represent a major threat to natural ecosystems. A primary source of invasive plants is ornamental horticulture, which selects traits related to invasiveness. This study evaluated the responses to water stress during germination and vegetative growth of six species used as ornamental or medicinal plants. Three of them are recognised as invasive weeds in many world areas. Seeds were exposed to increasing concentrations of polyethylene glycol (PEG) mimicking drought stress, and young plants in the vegetative growth stage were subjected to two levels of water stress. Results indicated that in the absence of stress in control conditions, the most competitive species were those reported as weeds, namely Bidens pilosa L., Oenothera biennis L., and Centaurea cyanus L., the last regarding germination velocity. Under stress, only two species, Limonium sinuatum (L.) Mill. and C. cyanus, maintained germination at –1 MPa osmotic potential, but in the recovery experiment, an osmopriming effect of PEG was observed. The most tolerant species during growth were two natives in the Mediterranean region, L. sinuatum and Lobularia maritima (L.) Desv., both accumulating the highest proline concentrations. The sixth species studied, Echinacea purpurea (L.) Moench., proved to be more susceptible to stress in the two developmental stages. This study reveals that the most significant traits associated with invasiveness were related to germination, especially in the absence of stress.

Monitoring of Groundwater in a Limestone Island Aquifer Using Ambient Seismic Noise

The limestone islands of Malta face high levels of water stress due to low rainfall over a small land area and a high population density. We investigate an innovative, cost-effective approach to groundwater monitoring in an island environment by computing auto- and cross-correlations of ambient seismic noise recorded on short-period and broadband seismic stations. While borehole readings give accurate site-specific water level data of the groundwater across the islands, this technique provides a more regional approach to quantitative groundwater monitoring. We perform the moving window cross-spectral method to determine temporal changes in seismic velocity (δv/v). Comparison of the δv/v with groundwater levels from boreholes and precipitation shows comparable patterns. We find that the variations of the δv/v from auto-correlations are more pronounced than the cross-correlation, and that short-period seismic stations are also sensitive. The δv/v signal deteriorates at longer interstation distances, presumably because paths traverse complex geology. We conclude that changes in the groundwater level found beneath very small islands, even as small as 3 km2, can be detected seismically. Low-cost, easy-to-deploy seismic stations can thus act as an additional tool for groundwater monitoring, especially in places with limited natural water reservoirs, like rivers and lakes, and infrastructure.

Assessing the climate change adaptability of sustainable land management practices regarding water availability and quality: A case study in the Sorraia catchment, Portugal

In Mediterranean catchments, such as the Sorraia catchment in Portugal, it is expected that climate change will increase drought stress and the deterioration of water quality in reservoirs. Sustainable land management (SLM) practices are seen as an adaption measure for those problems, but the effectiveness on improving climate change impacted water availability and quality on catchment scale is still poorly understood. Therefore, this study aims to evaluate the effectiveness of SLM practices in adapting the impacts of climate change on water availability and quality of the Montargil and Maranhão reservoirs in the Sorraia catchment. A well-calibrated Soil Water Assessment Tool model is used to simulate four scenarios (2041–2071 and 2071–2100; representative climate pathways 4.5 and 8.5), to investigate the effects of climate change on total phosphorus load (TP) in streams, reservoir volume, irrigation use and water exploitation index (WEI). Results showed that WEI will not exceed any water stress level while reservoir water quality will worsen. In particular since the TP load in streams flowing into the reservoirs increases and the volume decreases, it is likely that the existing P limitation for eutrophication will be counteracted. Nevertheless, tested SLM practices were able to decrease the TP load in those streams and increase the reservoir volume under future climates. Overall, this study shows that the SLM practices are effective in adapting to the climate change effects regarding reservoir water quality, without worsening the water availability; thus, it is a promising tool that should be investigated further for application by e.g. local land-users and decision makers.

Effect of foliar application of different concentrations of salicylic acid on Washington navel orange trees under water stress

BackgroundA field experiment was performed from 2021 to 2022 on 10-year-old Washington navel orange trees (Citrus sinensis) budded on sour orange rootstock (Citrus aurantium) under sandy loam soil conditions in the region of Belbeis—El Sharkia Governorate, Egypt. This study was carried out to increase water use efficiency, maximize water utilization and determine the most effective treatment of Washington navel orange trees by using different concentrations of salicylic acid (control, 250, 500, and 750 ppm) under some levels of water stress (100, 75 and 50% of estimated crop water requirement).ResultsIn this scenario, the water use efficiency increased with 750 ppm of salicylic acid under 75% of the estimated crop water requirement, which produced 2.27 and 3.09 kg of fruit for each cubic meter of irrigation water in the first and second seasons, respectively. In addition, using salicylic acid treatment with 750 ppm under 75% of the estimated crop water requirement had a high economic return through increasing water unit return, while using less water irrigation amount by 25% at the same time, which reached 9.06 and 12.38 EGP per every cubic meter of irrigation water in the first and the second seasons, respectively.ConclusionIn summary, the data cleared that the irrigation water quantity could reduce by 25% while maintaining the production and the possibility of increasing it by using salicylic acid with the highest concentration. Thus, we recommend applying the treatment of the estimated crop water requirement with 75% combined with salicylic acid 750 ppm to Washington navel orange trees budded on sour orange rootstock to gain a high economic return.

The Role of Regular and Nano-Chitosan in some Indicators of Vegetative and Root Growth of Tecoma stans (L.) Seedlings Under Different Levels of Water Stress

A factorial experiment was conducted with three factors, the first using three levels of water stress (50, 75 and 100%) of the field capacity value, the second spraying seedlings of Tecoma stans (L.) Juss. ex Kunth with regular chitosan in three concentrations (0, 150 and 300 mg.L-1), and the third spraying seedlingsat with nano-chitosan in three concentrations (0 and 150 and 300 mg.L-1). arithmetic mean of the coefficients was compared. Statistically according to Duncan’s Multiple Range Test. The results of the single effect of water stress showed the superiority of the seedlings that were treated with light water stress treatment by (100%) of the field capacity value, as well as the single effect of the regular and nano-chitosan biofertilizer, the superiority of the seedlings that were treated with a concentration of (300 mg.L-1) in the increase in the height of the seedlings, the increase in the diameter of the main stem of the seedling, main root length and root volume in the increase in the height of the seedlings, the increase in the diameter of the main stem of the seedling, main root length and root volume.

Intercropping millet with low-density cowpea improves millet productivity for low and medium N input in semi-arid central Senegal

Cereal-legume intercropping has been traditionally practiced across West Africa by farmers and provides resilience of agriculture to climate variability. Intensification of these extensive intercropping systems in order to meet future food demand is critical. This study aims at evaluating the agronomic performance of the intensification of millet-cowpea intercropping with low cowpea density, and its variation with climate variability, using an on-station experiment in Bambey, Senegal. Two trials (irrigated vs rainfed) were set up to compare millet sole- and inter-cropping with a grain and a fodder variety of cowpea, in 2018 and 2019. Two levels of fertilization were tested: 0 kg(N) ha−1 and 69 kg(N) ha−1. The two cropping years were contrasting and water stress around flowering and/or during grain filling (indicated by the Fraction of Transpirable Soil Water) was higher in 2019 than in 2018 in the rainfed experiment. In both experiment and for all treatments, land equivalent ratio (LER) in the intercropping was 1.6 and 1.4 for grain and biomass respectively. Millet aboveground biomass was significantly higher in intercropping than in sole cropping in the irrigated experiment but not in the rainfed experiment. In the rainfed experiment, the interaction between cropping system and year was significant, so that millet aboveground biomass was greater in intercropping than in sole cropping in 2018 (year of lower water stress) but not in 2019 (year of higher water stress). The effect of fertilization on millet aboveground biomass did not significantly interact with cropping system (sole vs intercrop). For grain yield, fertilization interacted significantly with the cropping system in the irrigated trial: the benefits of intercropping on millet grain yield were greater with 69 kg(N) ha−1 than with 0 kg(N) ha−1. This significant interaction could not be observed in the rainfed trial, potentially due to water stress. These results show that the level of water stress (related here to the year and to the rainfed or irrigated experiment) and that of fertilization modulate the performance of millet-cowpea intercropping in the semi-arid context of Senegal. Overall, fertilization had a stronger effect on millet grain yield than intercropping. The two strategies (intercropping and mineral fertilization) can be complementary to achieve sustainable intensification of cropping system in semi-arid areas of West Africa.

Determination of Enzyme Activity and Vitamin Content of Moringa Oleifera Lam. in Response to Glutathione and Biofertilizer under Water Stress

The study was carried out in the canopy belongs to the Horticulture and Landscape Department - College of Agriculture - University of Kerbala in pots with a capacity of 28 kg during the spring growing season 2021 to know the effect of spraying with glutathione, biofertilizer (Algacell) under different water stress levels on the effectiveness of some enzymes and the content of some vitamins of Moringa Oleifera plant. The study was designed as a factorial experiment according to the randomized complete block design (R.C.B.D), as the study included three factors: glutathione with three concentrations (0, 100, 200) mg.L−1 and biofertilizer (Algacell) at two levels (0 and 10) ml. L−1 and water stress with three levels of field capacity (60%, 50%, 40%), and the averages were compared using Dunkin’s multinomial test at a probability level of 0.05. Most of the vegetative growth characteristics were the spraying treatment at a concentration of 200 ml. L−1 achieved the highest rates in terms of (the activity of the enzyme catalase, the activity of the dismutase enzyme, the activity of the peroxidase enzyme, the concentration of ascorbic acid), which reached (2.75%, 28.622%, 6.005 mg.gm−1, 7.561%, 0.377 units.gm−1, 11.777 gm−1, 0.990 gm−1, 275.444 mg.gm−1), respectively, followed by the spray treatment with a concentration of 100 ml. L−1, while the comparison treatment recorded fewer concentrations, while the bio-fertilizer (Algacell) did not achieve a significant difference in all the studied traits, while the water stress treatment excelled at the level of 40% of the field capacity in the traits (the activity of the catalase enzyme, the activity of the dismutase enzyme, the activity of the peroxidase enzyme, the concentration of ascorbic acid, the concentration of α-Tocopherol) which gave respectively (0.446 gm−1, 13.222 gm−1, 1.133 gm−1, 294.167 mg.gm−1, 257.83 μg.gm−1), and the effect of the double and triple interaction between the treatments was similar to their single effects in improving most of the studied traits.

The Effect of Dry Farming and Water Stress under Subsurface Drip Irrigation System on Water and Rice Productivity

A field experiment was carried out during the 2020 season at the College of Agricultural Engineering/ University of Baghdad, Al-Jadriya to evaluate the effect of dry farming when applying water stress under the subsurface drip irrigation system on water productivity and rice yield. The experiment was conducted with three levels of irrigation water stress when 10, 20 and 40% of the available water was depleted and in three dimensions between drip lines 10, 15 and 20 cm. The experiment was designed according to a randomized complete block design, according to the split plot design, with three replications. Determine the depth of irrigation water depending on the moisture depletion of the soil, the results showed a difference in the depth of water according to the moisture depletion, which amounted to 900 mm. Season-1 treatment for 10% depletion and decreased to 10 and 16.6% when 20 and 40% of the prepared water was depleted, respectively. The intervention between drip lines and irrigation treatments led to a significant increase in grain yield when using a distance of 10 cm and irrigation when 10% of the available water was depleted. There were no significant differences in grain yield at I10 despite the difference in the distance between the drip lines. The efficiency of field and crop water use and the profitability of water outperformed I10.

Moringa Leaf Extract Mitigates the Adverse Impacts of Drought and Improves the Yield and Grain Quality of Rice through Enhanced Physiological, Biochemical, and Antioxidant Activities.

Agriculture, around the globe, is facing great challenges including the need to increase the production of nutrient-dense food and to withstand climate change's impact on water and soil conservation. Among these challenges, drought stress is considered the most overwhelming danger for the agriculture sector. Organic plant growth ingredients are frequently used to enhance the growth and production of field crops cultivated in normal and unfavorable conditions. The present study was designed to explore whether leaves extracted from various landraces of Moringa could play a defensive role against drought stress in rice. Seedlings were grown under three water conditions, i.e., normal conditions (control; 100% field capacity), moderate (75%), and severe drought (50%). Leaf extracts obtained from four Moringa landraces were used as foliar spray at the tillering, panicle initiation, and grain filling stages of cultivating rice plants. The levels of water stress negatively influenced photosynthetic pigment synthesis, gas exchange traits, antioxidant activities, and yield and grain quality parameters. Leaf extracts, at the rate of 3%, from all the landraces significantly enhanced the biochemical, physiological, and yield-related attributes of rice plants under normal and unfavorable growth conditions. Particularly, leaf extract from the Faisalabad landrace was the most effective biostimulant to increase photosynthetic (8.2%) and transpiration (13.3%) rates, stomatal conductance (8.3%), chlorophyll a (15.9%) and b (9.7%) contents, and carotenoids (10.4%) as compared to water spray. The maximum photosynthesis rate was observed at 14.27 µmol CO2 m-2 s-1 via application of leaf extract from the Faisalabad landrace followed by the DG Khan (13.92 µmol CO2 m-2 s-1) and Multan (13.9 µmol CO2 m-2 s-1) landraces, respectively. Improved grain yield (25.4%) and grain quality (an increase of 10.1% in amylose with a decrease of 2.8% in amylopectin) in rice plants along with enzymatic activities such as catalase (21.2%), superoxide dismutase (38.6%), and ascorbate peroxidase (24.3%) were observed at the peak after application of leaf extract from the Faisalabad landrace. The maximum grain yield of 53.59 g per plant was recorded when using Faisalabad landrace leaf extract and the minimum (40 g) using water spray. It is concluded from the findings of the current experiment that leaf extract from the Faisalabad landrace possesses higher biostimulant potential than other landraces and can be applied to mitigate the adverse impacts of drought stress with higher productivity and improved grain quality of rice.

Selection of Drought-Tolerant Pasture Species under Varying Soil and Moisture Conditions in Bauchi State, Nigeria

Livestock production is an agricultural system that serves as humanity’s protein and calorie source. Its production is the main economic stay for some people and a complementary source for others. However, land misappropriation and draught constrain the sustainable production of pasture for feeding livestock. Further aggravated by farmer/herder clashes and wetlands extinction. The need for an experiment for the selection of the best pasture species in the Sudan Savannah region that can thrive well under diverse soil textures and moisture status becomes imperative. This trial was conducted in the screen house of Babcock University, objectively to test the performances of Sorghum almum, Andropogon gayanus, Brachiaria mulato and Centrosema pascuorum under Sand, Sandy Clay Loam, and Sandy Loam textures and four water regimes: 100%, 75%, 50%, and 25%. Standard agronomic recommendations were practised throughout the experiment. Data collected included plant height, fresh and dry shoot and root weights, number of leaves, and leaf length. Data generated were analyzed using ANOVA. According to the results, Sandy Loam soil (Soil type from Gamawa) was the best for supporting all the pasture species, followed by Sandy Clay Loam (Soil type from Zaki). S. almum outperformed other pasture species significantly irrespective of soil textural type and water stress level treatments, followed by B. mulato. For water levels; 100% and 75% had the most promising biomass outcome. Based on the results, a 75% water regime which represents 25% deficit of the actual crop water requirement is recommended for the production of the tested pastures in the area.

Accurate estimation of sorghum crop water content under different water stress levels using machine learning and hyperspectral data.

This study investigates the effects of different water stress levels on spectral information, leaf area index (LAI), and the performance of three machine learning (ML) algorithms in estimating crop water content (CWC) of sorghum. The results show that the spectral reflectance of sorghum varies with growth stage and irrigation treatment, but consistent patterns are observed for each treatment. The LAI of sorghum gradually increased throughout the growth stages, with the most significant variation observed during the flowering stage. In this study, three machine learning-based regression models, namely, extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM), were utilized to estimate sorghum CWC using hyperspectral measurements. Recursive feature elimination (RFE) method was used to select the optimal spectral reflectance wavelengths for the ML models, and principal component analysis (PCA) was used to reduce the dimensionality of the hyperspectral data. The results indicated that the RF model achieved the highest R2 (0.90) and lowest of RMSE (56.05) value using selected wavelengths, while the XGBoost model demonstrated superior accuracy and reliability in estimating CWC using dimensionality-reduced hyperspectral data (r = 0.96, RMSE = 45.77). Also, the study highlights the importance of vegetation index (VI) in CWC estimate. Some VIs, such as NDVI and MSAVI, performed poorly, while others, such as CL_Rededge and EVI, performed better. The study provides valuable insights into the effects of water stress levels on spectral information, LAI, and the performance of ML algorithms in estimating the CWC of sorghum. The findings have significant implications for precision agriculture, as accurate and reliable estimates of CWC can help farmers optimize irrigation and fertilizer applications, leading to improved crop yields and resource efficiency.

Influence of sustained deficit irrigation and foliar kaolin application on almond kernel composition

Deficit irrigation and kaolin foliar application are agronomic practices that have been demonstrated to improve productivity and physiological response in almond trees but there is no consistent information on the effects on the kernel composition. The objective of this study was to evaluate the effect of different Sustainable Deficit Irrigation (SDI) strategies and kaolin application on some physicochemical composition of the cv Ferragnès almond (Prunus dulcis (Mill.) D.A. Webb). A randomized block design with five treatments was developed: non-irrigation (NI), non-irrigation with foliar kaolin application (NI+K), full irrigation (FI), and two levels of SDI receiving 70% and 35% of evapotranspiration (SDI75 and SDI35). Pomological parameters, volatile profile and oil composition were analyzed. SDI effect on kernel weight was reduced against full irrigation (FI) but substantially improved in comparison with the rainfed treatments (NI and NI+K). Irrigation treatments showed a lower volatile compounds concentration in comparison with rainfed treatment. The fatty acid composition of the oil was significantly affected, with all the irrigated treatments having higher oleic acid contents than the rainfed treatments, and therefore an expected increased shelf life. Kaolin application had no positive effects on the non-irrigated trees, other than an apparent increase in the total volatiles, a tendency also observed in the NI. Moderate water stress levels (SDI35) improved the synthesis of tocopherols compared to NI, FI and SDI70, which could be related to the adaptation of the almond tree to drought. SDI35 is therefore regarded as a very interesting approach, with significant improvements in comparison with non-irrigated trees, and a clear saving on water against full irrigation without significant pomological and chemical alterations.

Regional Water Stress Forecasting: Effects of Climate Change, Socioeconomic Development, and Irrigated Agriculture—A Texas Case Study

Climate change, socioeconomic development, and irrigation management are exacerbating water scarcity in many regions worldwide. However, current global-scale modeling approaches used to evaluate the impact of these factors on water resources are limited by coarse resolution and simplified representation of local socioeconomic and agricultural systems, which hinders their use for regional decision making. Here, we upgraded the irrigation water use simulation in the system dynamics and water environmental model (SyDWEM) and integrated it with the water supply stress index (WaSSI) ecosystem services model. This integrated model (SyDWEM-WaSSI) simulated local socioeconomic and agricultural systems to accurately assess future water stress associated with climate change, socioeconomic development, and agricultural management at subbasin levels. We calibrated the integrated model and applied it to assess future water stress levels in Texas from 2015 to 2050. The water stress index (WSI), defined as the ratio of water withdrawal to availability, was used to indicate different water stress levels. Our results showed that the integrated model captured changes in water demand across various sectors and the impact of climate change on water supply. Projected high water stress areas (WSI > 0.4) are expected to increase significantly by 2050, particularly in the Texas High Plains and Rolling Plains regions, where irrigation water use was projected to rise due to the impact of climate change. Metropolitan areas, including Dallas, Houston, Austin, and San Antonio, were also expected to experience increased domestic water demand, further exacerbating water stress in these areas. Our study highlights the need to incorporate socioeconomic planning into water resources management. The integrated model is a valuable tool for decisionmakers and stakeholders to evaluate the impacts of climate change, socioeconomic development, and irrigation management on water resources at the local scale.