Drought Levels Research Articles

Studying the Combined Impact of Salinity and Drought Stress-Simulated Conditions on Physio-Biochemical Characteristics of Lettuce Plant

Water scarcity and increasing salinity stress are significant challenges in the farming sector as they often exacerbate each other, as limited water availability can concentrate salts in the soil, further hindering plant growth. Lettuce, a crucial leafy vegetable with high nutritional value, is susceptible to water availability and quality. This study investigates the growth and development of lettuce plants under water scarcity and varying levels of salinity stress to identify effective strategies for reducing water consumption while maintaining or improving plant productivity. Field experiments were designed to simulate three drought levels (50, 75, and 100% of class A pan evaporation) and three salinity stress levels (control, 1500, and 3000 ppm NaCl), assessing their impact on lettuce’s morphological and biochemical parameters. The combination of reduced water supply and high salinity significantly hindered growth, underscoring the detrimental effects of simultaneous water deficit and salinity stress on plant development. Non-stressed treatment enhanced nitrogen, phosphorus, and potassium contents and progressively decreased with the reduction in water supply from 100% to 50%. Interestingly, higher salinity levels increased total phenolic, flavonoid, and antioxidant activity, suggesting an adaptive stress response. Moreover, antioxidant activity, evaluated through DPPH and ABTS assays, peaked in plants irrigated with 75% ETo, whether under control or 1500 ppm salinity conditions. The Yield Stability Index was highest at 75% ETo (0.95), indicating robust stability under stress. The results indicated that lettuce could be cultivated with up to 75% of the water requirement without significantly impacting plant development or quality. Furthermore, the investigation demonstrated that lettuce could thrive when irrigated with water of moderate salinity (1500 ppm). These findings highlight the potential for reducing water quantities and saline water in lettuce production, offering practical solutions for sustainable farming in water-scarce regions.

THE IMPACT OF SEED SIZE ON INITIAL DROUGHT STRESS RESILIENCE AND YIELD IN WHEAT CULTIVATION

Wheat yield is affected severely by drought in this era of changing climate patterns, including high temperatures and altered precipitation patterns. Drought is among the most challenging environmental stressors, limiting wheat cultivars' growth, productivity, and performance. The current study was conducted during the rabi season 2022 at the Research Area, Department of Agronomy, University of the Punjab, Lahore, Pakistan. Therefore, the present study evaluated the potential of diverse seed sizes to advance wheat crop growth, development, and yield when subjected to different drought levels. The study comprised two experiments. The first was a lab experiment that included different drought levels (DL), DL0: 0.0 bar, DL1: -2 bar, DL2: -4 bar, and DL3: -6 bar (drought levels were induced by solutions of PEG-6000 at different concentrations) and three wheat seed size classes, i.e., bold grain (>38 g), medium grain (<33 g), and small grain (<25 g). In the field experiment, drought stress levels were DL0 (regular irrigation), DL1 (first irrigation at 30 days), DL2 (first irrigation at 45 days), and DL3 (first irrigation at 60 days). Seed sizes included W1 (bold >38 g), W2 (medium <33 g), and W3 (small <25 g). Drought severity increased with DL1 to DL3. The outcomes of the field experiment revealed that varying levels of drought stress and seed size classes significantly affected parameters such as emergence time, growth traits, biomass allocation, tiller count, plant height, and grain and biomass outcomes. Bold seeds contributed to higher biomass and grain yield, while severe drought decreased yields. Notably, the Harvest Index was affected, indicating bold seeds allocate more biomass to grains. In conclusion, proper seed size selection, favouring bold seeds, can enhance resilience to drought, benefiting wheat cultivation in water-scarce regions.

Exploring the adaptive mechanisms and strategies of various populations of Sporobolus ioclados in response to arid conditions in Cholistan desert

This study explored the drought resistance mechanisms of different populations of Sporobolus ioclados (Poaceae), locally known as “Sawri,” “Drabhri” and “Dhrbholi” native to Africa and the Indian Subcontinent. These populations were grown in conventional nursery practices at Khawaja Fareed Government College in Rahim Yar Khan, Pakistan, and subsequently subjected to four distinct levels of drought within carefully monitored experimental settings. The experiment was conducted in a two-factorial design involving populations and drought treatments and was repeated three times. The physiological and morphological responses of S. ioclados, including plant height, number of roots, root length, flag leaf area, stomatal features, proline concentration and nitrogen content, displayed significant variability in response to the imposed drought stress. Drought resulted in increases in proline concentration and nitrogen content. The number of roots decreased, while the length and width of the stomata increased in various populations. A combination of advanced statistical techniques, such as ANOVA, PCA, HCA, and DFA, provided a comprehensive understanding of the mechanism of plant adaptation and the extent of population diversity within the species. The Yazman and Nwab Wala populations exhibited the highest rates of photosynthesis and stomatal conductance, while S. ioclados demonstrated notable drought tolerance at the T4 level of drought stress. A negative correlation was found between proline levels, nitrogen contents, and photosynthesis, suggesting that proline has a protective role in drought. The diverse adaptation strategies indicated by S. ioclados populations have revealed the potential of this species for afforestation and climate change mitigation in dry environments.

Drought Analysis in Ketapang District using the Keetch-Byram Drought Index Method

Ketapang Regency is one of the areas in West Kalimantan that is prone to drought. Drought can trigger forest and land fires. In this research, the Keetch-Byram Drought Index (KBDI) method was used to determine the level of drought in Ketapang Regency. The KBDI method relies on annual rainfall accumulation, daily rainfall, and maximum air temperature. The KBDI values obtained were correlated with the number of hotspots using Pearson correlation. This research was conducted throughout 2018-2022. Based on the monthly average KBDI value, the highest drought in Ketapang Regency occurred in August and September, while the lowest drought occurred in December and January. In terms of the annual average, the highest drought occurred in 2019. During the ENSO phenomenon in 2019, the El Niño phase experienced higher drought than the La Niña phase and normal years. In the El Niño phase, drought levels reach high to extreme categories. The correlation value between annual KBDI and the number of hotspots is 0.88, indicating a solid relationship. An increase in the KBDI value will be followed by an increasing number of hotspots.

Monitoring of Vegetation Drought Index in Laibin City Based on Landsat Multispectral Remote Sensing Data

Due to the impact of global warming, drought has caused serious damage to China’s ecological environment and social status. This article selects Laibin City in the Guangxi Zhuang Autonomous Region as the research area, utilizing multispectral remote sensing data as the data source and Landsat series image data for relevant preprocessing. It calculates the monthly normalized vegetation index (NDVI) and surface temperature (LST) data for Laibin City. Based on the ecological environment and surface coverage conditions of the research area, the ratio vegetation index (RVI), normalized vegetation moisture index (NDWI), temperature vegetation drought index (TVDI), and conditional vegetation temperature drought index (VTCI) were selected to calculate and invert the drought monitoring results of Laibin City. The drought monitoring results were obtained and overlaid with the vegetation area map to generate the vegetation drought monitoring results of Laibin City. Based on the climate, geography, and ecological characteristics of the monitored area in Laibin City, a specific analysis will be conducted to develop an appropriate TVDI index drought level, and generate vegetation drought level result maps for Laibin City in 2021, 2022, and 2023. Then, a detailed analysis of the vegetation drought situation in Laibin City is conducted according to time and space. Among them, in the past three years, the vegetation areas in Laibin City have experienced drought seasons mostly in summer and autumn. The interannual drought is mainly mild drought, and the proportion of areas with mild drought shows a relatively stable trend. In conclusion, TVDI proves to be a valuable tool for monitoring vegetation drought in Laibin City, offering insights for efficient water resource management strategies.

Drought Management in Batam using Combined NDVI-TCT Algorithm to Create a Classification Level Map

Drought constitutes a significant natural disaster with profound implications for agricultural productivity, economic stability, and ecological balance. Batam is one of the cities experiencing a high level of drought. At the end of 2022, Batam is actually on the verge of drought. The purpose of this study is to find out information on the distribution of potential for drought in Batam and the dominant factors affecting the potential for drought occurred using NDVI and TCT algorithms. This research employed remote sensing and GIS techniques, using Landsat 8 images to acquire parameters from NDVI, TCT, and Rainfall data, which are then processed through scoring and overlaying. The final step was to validate the vegetation index parameter by taking the coordinates. The final result is a map of the potential for drought in Batam, consisting of 5 classes of potential for drought. The area with a very low potential for drought was located mostly in Sagulung, with an area of 2.661,89 Ha. The areas with low potential for drought were mostly located in Nongsa, Batam Center, Batu Ampar, Bengkong, Lubuk Baja, and Batu Aji, with an area of 7.175,22 Ha. The areas with a very high potential for drought were mostly located in Galang, Bulang, and Belakang Padang, with an area of 19.744,76 Ha. The area with moderate potential for drought was mostly located in Sungai Beduk, with an area of 22.122,71 Ha. The areas with high potential for drought were mostly located in Galang and Bulang, with an area of 35.663,89 Ha. It is concluded from the results of this research that the collective classification of high and very high drought potential levels covers up to 64% of the entire research area.

Evaluation of Water Quality and Scarcity Issues for Sustainable Water Management Strategy in Twin Cities of Rawalpindi/ Islamabad, Pakistan.

Today's water world is pebbledashed with two main trepidations of water security/ scarcity, which need in-depth elaboration. Developing countries are particularly facing the impacts of water contamination and scarcity but lack the required impetus and technical infrastructure, thus necessitating swift actions to evaluate the effects of water security/ scarcity on the environment and water resources. In this study, an effort has been made to assess the water security/ scarcity situation in the twin cities of Rawalpindi/ Islamabad, elucidating the water quality/ quantity parameters in the Rawal Lake reservoir in Pakistan by analysing the contamination. The samples were collected/ tested during spring/ monsoon seasons to analyse temporal/fluvial impacts on water discharge. The results were compared with Pakistan's and WHO's drinking water standards before and after the water treatment. Almost all the testing parameters of the raw water samples from the Rawal Lake reservoir feeding streams exceeded the standard limits or fell close to the upper threshold limits, suggesting that this water was unsuitable for drinking without extensive treatment and an efficient distribution system. The contamination, untreated sewage disposal, non-regulated water utilisation, drawdown and supply/ demand gaps are the grave factors causing the water security/ scarcity in the capital/ twin cities of Islamabad/ Rawalpindi. Pakistan has already entered the water scarcity threshold of 1014 m3/ person/ annum in 2018, reduced from water availability of 5260 m3/ person/ annum in 1950 and will likely reach a drought level by 2050 due to increased population and reduced water resources. The study proposes an organisational implementation model for catchment-level river management to ensure good quality of water, construction of 5-10 small dams, and the provision of water from Terbella Dam suggested as the long-term strategy to prevent water scarcity.

Using ensemble learning method and binary decision tree algorithm for drought intensity level classification

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

Applicability of Remote Sensing Techniques in Drought Predicting: A Case Study in Ben Tre Province, Vietnam

Background: Drought poses significant threats to ecosystems, agriculture and the environment, including reduced crop yields, habitat degradation and increased risk of forest fires and soil erosion. In addressing this issue, remote sensing technology (RST) has emerged as a valuable tool for studying and monitoring drought phenomena, offering advantages over traditional research methods. Methods: This study focuses on the application of RST, specifically utilizing Landsat satellite images, to calculate drought indices and develop drought maps for the Ben Tre province in Vietnam. The research involved the analysis of Landsat satellite images collected between 2000 and 2020, using various drought indices such as TCI, VCI, SAVI and WSVI. Result: By employing these indices, the study was able to classify the levels of drought and generate a drought map for the study area. The findings revealed that the coastal regions encompassing Thanh Phu, Ba Tri and Binh Dai districts face a high risk of drought during the dry season.

β values obtained by linear regression models of morpho-physiological and biochemical variables as novel drought stress estimators in Capsicum annuum varieties

Capsicum annuum varieties are highly sensitive to drought. Under water stress conditions, these can show yield losses of up to 70 %. Due to the above, this work proposes a novel approach to obtain estimators of drought stress based on linear regression models for morpho-physiological and biochemical variables in jalapeño pepper (C. annuum cv. jalapeno M), bell pepper (C. annuum cv. california wonder), and serrano pepper (C. annnuum cv. serrano tampiqueno). Jalapeno pepper plants were grown for 69 days under permanent water deficit conditions at 40, 60, 80 % and 100 % of field capacity (FC) (100 % FC as control). Throughout the crop cycle, we monitored the plant's height and weight, basal stem diameter, transpiration, photosynthesis, stomatal conductance, NDVI, and proline. This monitoring allowed us to obtain linear regression models from the accumulated values for these variables, from which the slope values (β) were used as estimators of drought stress using the interval estimation method, in the same way, this method was used to estimate water status in bell pepper and serrano pepper. For bell pepper, drought levels of 40, 60, 80 and 100 % FC were imposed for 12 days and serrano pepper 60 and 100 % FC for 63 days. The results showed that this method can be used to estimate drought stress in jalapeno pepper for all the irrigation levels through photosynthesis and NDVI and can be applied for bell pepper and serrano pepper using stem diameter and plant height, and in the case of serrano pepper, NDVI showed adequate results. Also, this work establishes the relationship between the jalapeno pepper responses (morpho-physiological and biochemical) to drought stress during vegetative, flowering, and fruiting stages through a Principal Component Analysis (PCA). The PCA found that interaction among morphological, physiological, and biochemical responses change concerning the phenological stage of the plant. The results suggested several direct and inverse relationships between the variables and showed that drought can be described by stomatal conductance during any phenological stage of the crop. In parallel, the proline content, NDVI and plant height can also describe drought stress during the vegetative and flowering stages. This research is the first to apply this methodology to drought stress estimation in jalapeno, bell pepper, and serrano pepper cultivation. The results could significantly contribute to precision agriculture, sensor development, and water management.

How do drought and heat affect the response of soybean seed yield to elevated O3? An analysis of 15 seasons of free-air O3 concentration enrichment studies.

The coincidence of rising ozone concentrations ([O3]), increasing global temperatures, and drought episodes is expected to become more intense and frequent in the future. A better understanding of the responses of crop yield to elevated [O3] under different levels of drought and high temperature stress is, therefore, critical for projecting future food production potential. Using a 15-year open-air field experiment in central Illinois, we assessed the impacts of elevated [O3] coupled with variation in growing season temperature and water availability on soybean seed yield. Thirteen soybean cultivars were exposed to a wide range of season-long elevated [O3] in the field using free-air O3 concentration enrichment. Elevated [O3] treatments reduced soybean seed yield from as little as 5.3% in 2005 to 35.2% in 2010. Although cultivars differed in yield response to elevated [O3] (R), ranging from 17.5% to -76.4%, there was a significant negative correlation between R and O3 dosage. Soybean cultivars showed greater seed yield losses to elevated [O3] when grown at drier or hotter conditions compared to wetter or cooler years, because the hotter and drier conditions were associated with greater O3 treatment. However, year-to-year variation in weather conditions did not influence the sensitivity of soybean seed yield to a given increase in [O3]. Collectively, this study quantitatively demonstrates that, although drought conditions or warmer temperatures led to greater O3 treatment concentrations and O3-induced seed yield reduction, drought and temperature stress did not alter soybean's sensitivity to O3. Our results have important implications for modeling the effects of rising O3 pollution on crops and suggest that altering irrigation practices to mitigate O3 stress may not be effective in reducing crop sensitivity to O3.

Quantifying the effects of direct human activities and climate change on the spatial propagation of hydrological drought in the Yellow River Basin, China

The spatio-temporal evolution and propagation of flood and drought events are important in predicting their occurrences. This study attempted to investigate into the spatial propagation characteristics of hydrological droughts and their dynamics by identifying the spatial propagation probability (PP) and propagation time (PT) of different drought levels in the Yellow River Basin (YRB), China, based on copula functions and conditional probability. Then, the effects of direct human activities and climate change on the hydrological drought propagation were quantified by comparing the propagation characteristics of hydrological drought under observed and natural runoff. Results indicated that: (1) overall, the propagation of hydrological drought in the YRB showed a generally decreasing trend in PP and an increasing trend in PT with the increase of distance, presenting a gradually attenuating propagation along the river channel, the spatial propagation process of hydrological drought is similar to the domino effect; (2) when extreme hydrological drought occurred in the area represented by the Tangnaihai station located in the upstream basin, the probability of downstream areas experiencing moderate to severe hydrological drought showed an approximately decreasing trend along the river channel, with the PP of the observed sequence being slightly less than the natural sequence and the fluctuation of the hydrological drought propagation being more apparent; (3) taking 1986 as the dividing year, the average relative contribution rates of direct human activities to the changes in drought PT in spring, summer, autumn, and winter were 39.7%, 62.9%, 55.3%, and −67.2%, respectively, indicating a significant regulatory effect of reservoirs on hydrological drought propagation. In general, this study provided new insights into the spatial propagation mechanism of hydrological drought and offered a promising pathway for drought early warning and mitigation.

Drought risk management in agriculture: A copula perspective on crop diversification

AbstractDrought events are a major cause of large crop yield losses with implications for food security and farmers’ incomes. Growing multiple crops simultaneously during a cropping season is a well‐known on‐farm risk management strategy to cope with these drought risks. However, the effectiveness of this crop diversification under different severity levels of drought and how this effectiveness is influenced by the crop composition is unclear. This article provides new methodological and empirical insights to assess the effectiveness of such diversification, in particular to cope with extreme drought. We apply and evaluate nested Archimedean copulas and elliptical copulas to assess simultaneous farm‐level yield losses of different cash crops in German agriculture (winter wheat, winter barley, winter rapeseed, sugar beet, and grain maize) under different drought severity levels (N = 249,756; regionally pooled farm‐level crop‐yield pairs, 1995–2019). We show that on‐farm crop diversification contributes to cope with drought risks, but its effectiveness varies considerably across regions, crop pairs, and drought severity. Our results underline that cropping system diversification alone is often not sufficient to cope with drought risks, but that the right crop combinations are needed. For example, during a severe drought (one in 20 years event), 26.4% of farmers in eastern Germany suffered simultaneous yield losses of at least 20% in winter wheat and winter barley, while 19.1% of farmers in eastern Germany suffered simultaneous yield losses of at least 20% in winter wheat and sugar beet. Farmers should therefore be encouraged to grow crops with more diverse phenological requirements throughout the year.

METEOROLOGICAL DROUGHT RISK ASSESSMENT USING SPI NUMERICAL MODEL: A CASE STUDY OF HELMAND RIVER BASIN, AFGHANISTAN

Meteorological droughts, which result from insufficient precipitation, can cause significant economic damage. While preventing meteorological droughts is impossible, their harmful effects can be reduced through close monitoring. This study aims to evaluate the meteorological drought in the Helmand River Basin using the Standardized Precipitation Index (SPI) model. The hydrometeorological data used for this analysis were collected from the Ministry of Energy and Water (MEW) in Afghanistan. The precipitation data collected from MEW covers a 40-year period from 1979 to 2021. The SPI analysis of precipitation shows that 1990, 1991, and 1992 were moderately wet, while 1982, 1983, 1995-1998, 2005, 2014, and 2015 were nearly normal. However, moderately dry conditions were observed in 2000, 2001, 2018, and 2021. Among the sampled stations, Waras and Gardez consistently had low drought levels, while Tarnak, Shila-i-charkha, and Khwabgah stations experienced moderate-level drought. Meanwhile, Lashkargah and Adraskan stations exhibited relatively high levels of drought. In conclusion, this research on the HRB, using the SPI method, has provided valuable knowledge for understanding drought dynamics in the region. The findings underscore the importance of conducting region-specific analyses, the necessity of implementing sustainable water management strategies, and the global significance of addressing drought as a pressing environmental challenge.

Health vulnerability mapping for drought: a case study in a predominantly rural, agricultural state

Abstract Drought is considered among the most devastating climate hazards impacting civilizations, including human health, throughout history. It causes cumulative damages based on the five generally categorized meteorological, hydrological, agricultural, socioeconomic, and ecological droughts. Reducing damages at the local, regional, and global levels requires a better understanding of human (health) vulnerability to drought. While there are different studies to distinguish and measure vulnerabilities for the five aforementioned conditions, there is minimal effort to identify vulnerabilities to health impacts from drought. Our study aims to develop an analysis of vulnerability for Nebraska based on the established health effects associated with drought. We considered vulnerability as the interaction between exposure to drought and different sensitivity measures for a timespan, including the highest drought levels in the 21st century. To calculate the total sensitivities, we extracted ten initial variables and applied two well-known methods of dimensionality reduction and (Weighted) Additive Overlays of percentile-ranked values. The result showed the inadequacy of the former method for our study. We also grouped the sensitivity variables into socioeconomic, environmental, and water-related intervention categories and developed related intensity maps showing different spatial patterns. We calculated the drought exposure levels by adding the intensity, duration, and frequency of drought over the study period (2012–2016) and developed total vulnerability maps to determine the ten most vulnerable counties, of which nine are rural. The resulting three intervention category maps can help related experts find priority areas within Nebraska, and the final vulnerability maps can help distinguish the areas of concern for general state-wide planning. While the results and some sensitivity variables are unique to Nebraska, the provided framework and the inclusion of two different methods can guide other regions in similar studies.

Polyploidy and environmental stress response: a comparative study of fern gametophytes.

Climate change is rapidly altering natural habitats and generating complex patterns of environmental stress. Ferns are major components of many forest understories and, given their independent gametophyte generation, may experience unique pressures in emerging temperature and drought regimes. Polyploidy is widespread in ferns and may provide a selective advantage in these rapidly changing environments. This work aimed to understand whether the gametophytes of allopolyploid ferns respond differently to climate-related physiological stress than their diploid parents. The experimental approach involved a multifactorial design with 27 treatment combinations including exposure to multiple levels of drought and temperature over three treatment durations, with recovery measured at multiple timepoints. We measured Chl fluorescence from over 2000 gametophytes to evaluate stress avoidance and tolerance in diploid and polyploid species. Polyploids generally showed a greater ability to avoid and/or tolerate a range of stress conditions compared with their diploid counterparts, suggesting that polyploidy may confer enhanced flexibility and resilience under climate stress. Overall, these results suggest that polyploidy may provide some resilience to climate change in mixed ploidy populations. However, all species remain susceptible to the impacts of extreme drought and heat stress.

Spatio-temporal forecasting for the US Drought Monitor

Abstract The US Drought Monitor is the leading drought monitoring tool in the United States. Updated weekly and freely distributed, it records the drought conditions as geo-referenced polygons showing one of six ordered levels. These levels are determined by a mixture of quantitative environmental measurements and local expert opinion across the entire United States. At present, forecasts of the Drought Monitor only convey the expected direction of drought development (i.e. worsen, persist, subside) and do not communicate any uncertainty. This limits the utility of forecasts. In this paper, we describe a Bayesian spatio-temporal ordinal hierarchical model for use in modelling and projecting drought conditions. The model is flexible, scalable, and interpretable. By viewing drought data as areal rather than point-referenced, we reduce the cost of sampling from the posterior by avoiding dense matrix inversion. Draws from the posterior predictive distribution produce future forecasts of actual drought levels—rather than only the direction of drought development—and all sources of uncertainty are propagated into the posterior. Spatial random effects and an autoregressive model structure capture spatial and temporal dependence, and help ensure smoothness in forecasts over space and time. The result is a framework for modelling and forecasting drought levels and capturing forecast uncertainty.

Interaction impact of drought stress, nutrient-deficient water, and seed-borne pathogen (Alternaria alternata) on germination and vigor of two tomato varietiesination and vigor of two tomato varieties

Tomato (Solanum lycopersicum) is considered one of the leading vegetable plants in the world. This study evaluated the germination and vigor capabilities of ‘Marmande’ and ‘Kecskeméti Jubileum’ varieties under different conditions, including drought stress, nutrient-deficient water, and the effect of seed-borne disease caused by Alternaria alternata when prime and non-prime with salicylic acid. The experiment was conducted in the laboratory in 2023 at Agricultural and Food Sciences and Environmental Management Faculty of University of Debrecen. Results indicated that the ‘Kecskeméti Jubileum’ variety exhibited a superior strength to ‘Marmande’ in the seedling’s dry weight, seedling growth rate, and vigor index under nutrient-deficient water. Nevertheless, when applying levels of drought, the ‘Marmande’ variety had a higher viability rate of 62.5% in comparison with another variety, and the germination rate of the two tomato varieties is at 85.5% in 5% concentration but decreased progressively when exposed to a higher drought concentration of 10%. When using 3 ml of salicylic acid during germination stages, the seedling vigor index of ‘Marmande’ shows a greater index at 165 compared to ‘Kecskeméti Jubileum’, just 108 under the infection of Alternaria alternata. The results of the examination of drought stress, and the effect of Alternaria alternata, one cause of seed-borne pathogens, showed that the percentage germination and vigor ability of the ‘Marmande’ variety performed better than ‘Kecskeméti Jubileum’ under the same conditions.

Probability-Based Propagation Characteristics from Meteorological to Hydrological Drought and Their Dynamics in the Wei River Basin, China

Understanding the propagation characteristics and driving factors from meteorological drought to hydrological drought is essential for alleviating drought and for early warning systems regarding drought. This study focused on the Weihe River basin (WRB) and its two subregions (the Jinghe River (JRB) and the middle reaches of the Weihe River (MWRB)), utilizing the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) to characterize meteorological and hydrological drought, respectively. Based on Copula theory and conditional probability, a quantification model for the propagation time (PT) of meteorological–hydrological drought was constructed. The dynamic characteristics of PT on annual and seasonal scales were explored. Additionally, the influences of different seasonal meteorological factors and underlying surface factors on the dynamic changes in PT were analyzed. The main conclusions were as follows: (1) The PT of meteorological–hydrological drought was characterized by faster propagation during the hot months (June–September) and slower propagation during the cold months (December to March of the following year); (2) Under the same level of hydrological drought, as the level of meteorological drought increases, the PT of the drought shortens. The propagation thresholds of meteorological to hydrological drought in the WRB, the JRB, and the MWRB are −0.69, −0.81, and −0.78, respectively. (3) In the dynamic changes in PT, the WRB showed a non-significant decrease; however, both the JRB and the MWRB exhibited a significant increase in PT across different drought levels. (4) The influence of the water and heat status during spring, summer, and winter on PT was more pronounced, while in autumn, the impact of the basin’s water storage and discharge status was more significant in the JRB and the MWRB.

TaMYB44-5A reduces drought tolerance by repressing transcription of TaRD22-3A in the abscisic acid signaling pathway.

TaMYB44-5A identified as a transcription factor negatively regulates drought tolerance in transgenic Arabidopsis. Drought can severely reduce yields throughout the wheat-growing season. Many studies have shown that R2R3-MYB transcription factors are involved in drought stress responses. In this study, the R2R3-MYB transcription factor MYB44-5A was identified in wheat (Triticum aestivum L.) and functionally analyzed. Three homologs of TaMYB44 were isolated, all of which localized to the nucleus. Overexpression of TaMYB44-5A reduced drought tolerance in Arabidopsis thaliana. Further analysis showed that TaMYB44-5A reduced the sensitivity of transgenic Arabidopsis to ABA. Genetic and transcriptional regulation analyses demonstrated that the expression levels of drought- and ABA-responsive genes were downregulated by TaMYB44-5A, and TaMYB44-5A directly bound to the MYB-binding site on the promoter to repress the transcription level of TaRD22-3A. Our results provide insights into a novel molecular pathway in which the R2R3-MYB transcription factor negatively regulates ABA signaling in response to drought stress.