Plant Water Stress Research Articles

Adopting a strategic approach to dormant seeding and initial soil water management for rainfed lentil agroecosystems

The initial soil water (ISW) content and dormant seeding management (DSM) also resulted in better use of precipitation and escape from the heat and drought stresses in late spring and early summer. However, the effect of initial soil water content under DSM as an adaptation option on crop yield has not been fully evaluated, especially in developing countries. We aimed to assess sowing date and ISW on yield of lentil cultivars in 37 selected locations representing six arid and semi-arid agro-climates in Iran. We utilized the SSM-Legume model to quantify the sensitivity of lentil production to ISW and sowing date. Our results showed that the ISW creates the early appearance of stress on late-sown lentil, while DSM1 (dormant seeding around 20 December) of lentil conserved higher soil water throughout the crop growth period. On the other hand, DSM1 and short cycle cultivar explored a higher amount of soil water and thus increasing the productivity. Hence, to minimize the effect of soil water stress in lentil rainfed agroecosystems, the best management combination of a short-cycle cultivar, DSM1, and an ISW ranges from 32 up to 52 mm produced the highest grain yield over all studied agro-climate types (779–605 kg ha−1) due to lower plant water stress. Improving total production can be especially effective in arid and semi-arid areas. These results can offer advice to farmers and decision-makers in enhancing rainfed lentil production in arid and semi-arid agroecosystems by managing soil water and DSM.

Malt Barley Yield and Quality Response to Crop Water Stress Index

Malt barley is a crucial irrigated crop in the semi-arid Western United States, where the states of Idaho, Colorado, Wyoming, and Utah account for 92% of the irrigated production acreage and 30% of total U.S. production. In this region, spring malt barley’s seasonal evapotranspiration ranges from 400 to 650 mm, and competition for limited water supplies, coupled with drought, is straining regional water resources. This study aimed to investigate the use of canopy temperature for deficit irrigation scheduling of malt barley. Specifically, the objectives were to use data-driven models to estimate well-watered (TLL) and non-transpiring (TUL) canopy temperatures, correlate the crop water stress index (CWSI) with malt barley yield and quality measures, and assess the applicability of CWSI for malt barley irrigation scheduling in a semi-arid climate. A 3-year field study was conducted with five irrigation treatments relative to estimated crop evapotranspiration (full, 75%, 50%, 25%, and no irrigation) and four replicates each. Continuous canopy temperature measurements and meteorological data were collected, and a feedforward neural network model was used to predict TLL, while a physical model was used to estimate TUL. The neural network model accurately predicted TLL, with a strong correlation (R2 = 0.99), a root mean square error of 0.89 °C, and a mean absolute error of 0.70 °C. Significant differences in calculated season-average CWSI were observed between the irrigation treatments, and relative evapotranspiration, malt barley relative yield, test weight, and plump kernels were negatively correlated with the season-average CWSI, while seed protein was positively correlated. The relationship between daily CWSI and fraction of available soil water was well described by an exponential decay function (R2 = 0.72). These results demonstrate the applicability of data-driven models for computing CWSI of irrigated spring malt barley in a semi-arid environment and their ability to assess plant water stress and predict crop yield and quality response from CWSI.

Changes in ecosystem carbon sequestration and influencing factors from a ’Past-Future’ perspective: A case study of the Tarim River

Amid global warming and intensified human activities, the carbon sequestration (CS) capacity of terrestrial ecosystems faces significant pressure. Ecological Water Conveyance (EWC) projects, by altering land use patterns, have become a key approach to addressing this issue. Therefore, the critical question this study aims to solve is how to enhance regional CS by optimizing EWC measures, based on understanding the relationship between land use changes and CS. To address this, we propose an integrated framework that couples the PLUS-InVEST-OPGD models, adopting a ’past-future’ perspective to explore the relationship between CS and land use changes in the context of EWC. The study found that during the historical period (2000–2020), CS in the Tarim River (TR) area exhibited a pattern of ’ first increasing, then stabilizing.’ Between 2000 and 2010, the total CS increased by 3.5 × 10^6 Mg, accompanied by an expansion of forested areas along the riverbanks and within national parks. However, from 2010 to 2020, the total CS increased by only 0.3 × 10^6 Mg, with forested areas along the riverbanks and within national parks remaining relatively stable. Under three future development scenarios—Natural Increase (NIS), Farmland Protection (FPS), and Ecological Protection (EPS)—CS differences between NIS and FPS are minimal at 0.01 × 10^6 Mg, as both continue existing EWC policies without optimization, with NIS following natural growth and FPS prioritizing farmland preservation. In contrast, the EPS, which introduces optimized EWC strategies to limit urban expansion and enhance ecological sustainability, results in a significant CS increase of approximately 1.1 × 10^6 Mg, with farmland areas also expanding. Through single factor and interactive detection analyses, we found that potential evapotranspiration and annual average groundwater depth play crucial roles in vegetation restoration in arid regions, as EWC helps maintain groundwater levels, reducing plant water stress and supporting vegetation growth, while managing evapotranspiration ensures that the water provided through EWC is efficiently utilized for ecosystem recovery and CS. Under the current EWC model and prevailing climate and human activity conditions, the CS capacity of ecosystems appears to stabilize. To further enhance the region’s CS potential, optimizing EWC strategies is essential. It is recommended to construct a ’surface’ water conveyance network through engineering measures, in addition to the existing ’linear conveyance’ model, to improve water resource utilization efficiency. The findings of this study offer valuable insights not only for the TR region but also for other arid inland river basins worldwide, providing a replicable framework for ecological restoration and water management.

Assessment of Critical Environmental Risk Zones Around Wetlands in Colombo, Sri Lanka, Using Satellite Remote Sensing and Multi-criteria Decision Tools

Colombo, Sri Lanka’s commercial capital, is recognized as one of the first 18 global sites that were awarded the Ramsar Wetland City accreditation, and is a prime example of the intersection between urbanization and wetland conservation. Thus, this study aims to conduct an environmental risk assessment that can provide insights into the changes in biophysical properties driven by urbanization over the 2000–2020 period. The study used Geographical Information Systems and a remote sensing approach to assess critical environmental risk zones around urban freshwater lakes in the Colombo district of Sri Lanka, including Thalangama, an environmental protection area experiencing sub-urbanization. Satellite data (2000–2020) were employed, and spectral indices, including NDVI, NDBI, NDWI, NDMI, RVI and LST, were calculated. Intersecting areas with multiple risk factors were determined, and distances from these zones to lakes were calculated to generate spatially explicit risk maps using inverse distance weighting. The building density has consistently increased from 2000 to 2020 in all three sites, with ‘very high’ density areas expanding notably. NDVI reveals a gradual increase in ‘very high’ categories until 2015. Plant-water stress analysis shows significant water stress in 2015, and water body areas have decreased after 2010 in all the sites. Multi-criteria assessment identifies critical environmental risk zones around urban lakes, indicating high vulnerability to environmental damage and degradation. Overall, the study emphasizes the importance of leveraging data and risk analysis to inform decision-making processes in environmental management. By doing so, policymakers can enhance the effectiveness of conservation measures and promote the long-term sustainability of natural resources.

TRANSCRIPTIONAL ANALYSIS OF SOYBEAN (Glycine max) GENES RELATED TO WATER DEFICIT

ABSTRACT The soybean crop has been gaining worldwide prominence, being widely disseminated due to its various forms of use in different segments. Genetic and environmental factors are decisive in the quality of this culture. A feature related to the environmental factor that has gained prominence is the water deficit. Molecular events are initiated by the perception of water stress, involving a complex genetic network. Studies in recent decades have already identified some genes related to water stress in plants, it is known that the dehydration-responsive element binding protein (DREB) plays an important role in the response to water deficit. Therefore, this work aimed to analyze the expression of genes related to water deficit in soybean. For the analysis of gene expression, leaves of soybean (Glycine max (L.) Merrill), cultivar M9144 RR, submitted to the following treatments were used: 25V25R – plants subjected to water deficit throughout the cycle, being irrigated with 25% of ETpc and 100V100R – plants that did not experience water deficit, being irrigated with 100% of ETpc throughout the cycle. The quantification of the relative expression of the genes GmDREB1 and GmDREB5 showed that the water stress suffered by the cultivar was greater in the reproductive stage. Keywords: Transcription factors, development stages, gene expression.

Global influence of soil texture on ecosystem water limitation

Low soil moisture and high vapour pressure deficit (VPD) cause plant water stress and lead to a variety of drought responses, including a reduction in transpiration and photosynthesis1,2. When soils dry below critical soil moisture thresholds, ecosystems transition from energy to water limitation as stomata close to alleviate water stress3,4. However, the mechanisms behind these thresholds remain poorly defined at the ecosystem scale. Here, by analysing observations of critical soil moisture thresholds globally, we show the prominent role of soil texture in modulating the onset of ecosystem water limitation through the soil hydraulic conductivity curve, whose steepness increases with sand fraction. This clarifies how ecosystem sensitivity to VPD versus soil moisture is shaped by soil texture, with ecosystems in sandy soils being relatively more sensitive to soil drying, whereas ecosystems in clayey soils are relatively more sensitive to VPD. For the same reason, plants in sandy soils have limited potential to adjust to water limitations, which has an impact on how climate change affects terrestrial ecosystems. In summary, although vegetation–atmosphere exchanges are driven by atmospheric conditions and mediated by plant adjustments, their fate is ultimately dependent on the soil.

Identification of drought-salinity combined stress in tomato plants by vegetation indices

A major issue in several farming areas of the Mediterranean basin consists of drought and salinity stress. This stress is mainly due to a steady exposition of warm daily temperature and heatwaves, moreover with inevitable irrigation with saline water. Therefore, detecting the stress is essential to minimise significant yield loss and preserve agricultural sustainability. In this context, remote and proximal sensing can play a crucial role in allowing fast, not destructive, extensive, and reliable assessment of crop status. In this work, the effectiveness of several multispectral indices in detecting salinity and water stress in tomato plants, grown under controlled green-house conditions, was investigated. Three different classifiers (fine tree model, linear discriminant model, and linear support vector machines model) were used to verify whether, and the extent to which, the adopted multispectral indices can be adopted to identify a stress condition of the tomato plants. In the experimental campaign, the stress occurrence on tomato plants was assessed on the base of a set of ecophysiological measurements, such as transpiration, stomatal conductance, and photosynthesis rate. Obtained results showed that a classification model based on linear support vector machines, exploiting the combination of Photochemical Reflectance Index and the Chlorophyl Index, can detect drought and salinity stress in tomato plants with an accuracy higher than 94%.

Thermographic Analysis of Green Wall and Green Roof Plant Types under Levels of Water Stress

Urban green infrastructure (UGI) plays a vital role in mitigating climate change risks, including urban development-induced warming. The effective maintenance and monitoring of UGI are essential for detecting early signs of water stress and preventing potential fire hazards. Recent research shows that plants close their stomata under limited soil moisture availability, leading to an increase in leaf temperature. Multi-spectral cameras can detect thermal differentiation during periods of water stress and well-watered conditions. This paper examines the thermography of five characteristic green wall and green roof plant types (Pachysandra terminalis, Lonicera nit. Hohenheimer, Rubus tricolor, Liriope muscari Big Blue, and Hedera algeriensis Bellecour) under different levels of water stress compared to a well-watered reference group measured by thermal cameras. The experiment consists of a (1) pre-test experiment identifying the suitable number of days to create three different levels of water stress, and (2) the main experiment tested the suitability of thermal imaging with a drone to detect water stress in plants across three different dehydration stages. The thermal images were captured analyzed from three different types of green infrastructure. The method was suitable to detect temperature differences between plant types, between levels of water stress, and between GI types. The results show that leaf temperatures were approximately 1–3 °C warmer for water-stressed plants on the green walls, and around 3–6 °C warmer on the green roof compared to reference plants with differences among plant types. These insights are particularly relevant for UGI maintenance strategies and regulations, offering valuable information for sustainable urban planning.

Improving yield and irrigation water productivity of green beans under water stress with agricultural solid waste-based material of compacted rice straw as a sustainable organic soil mulch

AbstractThis research aimed at water saving in irrigation by applying deficit irrigation using two strategies, standard drip and partial root drying (PRD), while applying organic and plastic mulch over two growing seasons of green beans. A field experiment was conducted in 2022 and 2023, using four irrigation treatments supplying 100% of the irrigation requirement (IRg), 75% IRg, 50% IRg, and 50% IRg—PRD, and four soil mulching treatments: uncovered soil (UC), plastic mulch (PM), rice straw mulch (RSM), and compacted rice straw mulch (CRSM). The combined effect of deficit irrigation strategies and soil mulching showed that the maximum irrigation water productivity (IWP) of 5.56 kg m−3 was achieved under 50% IRg—PRD & CRSM for both growing seasons, followed by 50% IRg—PRD & RSM and 50% IRg—PRD & PM, with 5.19 and 4.96 kg m−3, respectively. The highest yield of 8936 kg ha−1 was achieved with 50% IRg—PRD & CRSM, followed by 8914 kg ha−1 and 8898 kg ha−1 with 100% IRg & CRSM and 75% IRg & CRSM, respectively. The lowest yield of 6009 kg ha−1 was obtained with 50% IRg & UC. The highest soil moisture content was observed under 100% IRg & CRSM. The application of organic mulches was found to be particularly effective in conserving soil moisture due to enhanced infiltration, improved retention capacity, and suppression of weed growth, ultimately fostering optimal crop development and higher yield. The results of soil temperature variations beneath soil mulches showed that CRSM is effective in alleviating plant water stress, lowering the temperature below the cover and reducing water loss through evaporation from the soil surface. The combination of 50% IRg—PRD & CRSM produced plants with enhanced plant height, fresh and dry weight, leaf area, pod length, and green bean weight, as well as the highest vegetative growth indices. Generally, the organic mulching increased soil temperature, soil moisture, IWP, and green bean production.

Mapping critical soil moisture thresholds of water stress for global grasslands

The critical soil moisture threshold (SMth) of plant water stress distinguishes whether vegetation is in an energy-limited or water-limited regime. Accurate quantification of SMth for grasslands holds significant implications for drought monitoring and efficient grassland management. However, our understanding of SMth within global grasslands remains limited. In this study, we investigated the relationship between SMth and environmental factors and mapped the global SMth for grasslands based on the estimated SMth across FLUXNET sites. Firstly, SMth was identified and estimated for 18 distinct grassland sites. Then, the factors significantly affecting SMth were investigated and the global SMth for grasslands was predicted using an empirical linear model. Our results showed that SMth was significantly positively correlated with mean annual soil moisture (SM), mean annual precipitation (PRE), and maximum annual LAI (LAImax), while negatively correlated with vapor pressure deficit (VPD) and shortwave radiation (RAD). These factors collectively constrain SMth well, with the coefficient of determination of 0.79. The estimated mean SMth for global grasslands from 2000 to 2021 is 27.8%, with a range from 1.3% to 55.2%. The SMth values are lower in the northern hemisphere than that in the southern hemisphere. The highest values of SMth, exceeding 40.0%, are mainly distributed in Brazil, Peru, Southern Europe, New Zealand and the Tibetan Plateau. In contrast, the lowest values, failing below 20.0%, are mainly distributed in Northern Canada, Greenland, Central African Savannah and Kazakhstan. The SMth is markedly lower in the arid region than that in the tropical and temperate regions. The quantified SMth in this study could provide a direct way to determine whether and to what extent grasslands are subjected to water stress, which would greatly facilitate the study of drought or water stress effects on vegetation growth for grassland ecosystems.

Untangling the environmental drivers of gross primary productivity in African rangelands

Precipitation variability is forecast to increase under climate change but its impacts on vegetation productivity are complex. Here, we use generalised additive models and remote sensing-derived datasets to quantify the effect of precipitation amount, distribution, and intensity on the gross primary productivity of dry rangelands across sub-Saharan Africa from 2000 to 2019 and differentiate these effects from other variables. We find that total precipitation is the primary driver of productivity, but that more variable rainfall has a small negative effect across vegetation types and rainfall regimes. Temperature and soil nitrogen also have strong effects, especially in drier rangelands. Shrublands and grasslands are more sensitive to environmental variability than savannas. Our findings support a model in which the main constraints on productivity are maintenance of soil moisture and minimisation of plant water stress. This highlights the risks of climate warming and increasing variability for productivity in water-limited grass and shrublands but suggests savannas may have greater resilience in Africa.

Stomatal and Non-Stomatal Leaf Responses during Two Sequential Water Stress Cycles in Young Coffea canephora Plants

Understanding the dynamics of physiological changes involved in the acclimation responses of plants after their exposure to repeated cycles of water stress is crucial to selecting resilient genotypes for regions with recurrent drought episodes. Under such background, we tried to respond to questions as: (1) Are there differences in the stomatal-related and non-stomatal responses during water stress cycles in different clones of Coffea canephora Pierre ex A. Froehner? (2) Do these C. canephora clones show a different response in each of the two sequential water stress events? (3) Is one previous drought stress event sufficient to induce a kind of “memory” in C. canephora? Seven-month-old plants of two clones (’3V’ and ‘A1’, previously characterized as deeper and lesser deep root growth, respectively) were maintained well-watered (WW) or fully withholding the irrigation, inducing soil water stress (WS) until the soil matric water potential (Ψmsoil) reached ≅ −0.5 MPa (−500 kPa) at a soil depth of 500 mm. Two sequential drought events (drought-1 and drought-2) attained this Ψmsoil after 19 days and were followed by soil rewatering until a complete recovery of leaf net CO2 assimilation rate (Anet) during the recovery-1 and recovery-2 events. The leaf gas exchange, chlorophyll a fluorescence, and leaf reflectance parameters were measured in six-day frequency, while the leaf anatomy was examined only at the end of the second drought cycle. In both drought events, the WS plants showed reduction in stomatal conductance and leaf transpiration. The reduction in internal CO2 diffusion was observed in the second drought cycle, expressed by increased thickness of spongy parenchyma in both clones. Those stomatal and anatomical traits impacted decreasing the Anet in both drought events. The ‘3V’ was less influenced by water stress than the ‘A1’ genotype in Anet, effective quantum yield in PSII photochemistry, photochemical quenching, linear electron transport rate, and photochemical reflectance index during the drought-1, but during the drought-2 event such an advantage disappeared. Such physiological genotype differences were supported by the medium xylem vessel area diminished only in ‘3V’ under WS. In both drought cycles, the recovery of all observed stomatal and non-stomatal responses was usually complete after 12 days of rewatering. The absence of photochemical impacts, namely in the maximum quantum yield of primary photochemical reactions, photosynthetic performance index, and density of reaction centers capable of QA reduction during the drought-2 event, might result from an acclimation response of the clones to WS. In the second drought cycle, the plants showed some improved responses to stress, suggesting “memory” effects as drought acclimation at a recurrent drought.

Abiotic stress responses in crop plants: A multi-scale approach

Population stress has compelled the whole world to think about increasing, protecting, and finding ways to develop the best plant species for assured productivity in spite of all environmental odds. In addition to climate change, fluctuations in nature and human activities pose serious environmental degradation, threatening global food security through physical stress in the environment. Significant environmental constraints on agricultural yield worldwide include salt stress, water deficiency stress, nutritional imbalances (including mineral toxicity and deficiencies), and temperature extremes. Abiotic factors, such as agronomic factors, climatic factors, and nutrient availability in the soil, influence crop yield. Plants initiate and develop various possible stress mechanisms for their survival, which can be molecular, cellular and physiological. Abiotic stress has a high impact on crop growth and productivity, either in single forms or in combined forms. For example, drought stress causes a decrease in leaf area, plant height, and crop development. Cold stress reduces plant development and crop efficiency, resulting in productivity loss. Salinity stress not only contributes to water stress in plants, but it can also adversely influence cytosolic metabolism, cell development, membrane function, and increase reactive oxygen species (ROS) generation. Higher concentrations of CO2 could potentially improve global precipitation, resulting in increased rainfall, which can adversely affect crop development. Crops under excessive water stress have a lower percentage of amylose but a higher crude protein content. This in turn, affects the quality and quantity of crop production by hindering seed germination and causing growth damage due to the combined effects of higher osmotic potential and ion toxicity. In response to abiotic stress, plants evolve a variety of escape-avoidance and tolerance mechanisms, which include physiological adaptation and integrated cellular or molecular responses. Therefore, the main purpose of the current review paper is to investigate the effect of abiotic stress on morpho-physiological, biochemical and molecular activities in various crops. Moreover, we concentrate on crop inter-relativity with abiotic stress to react to and adapt to for survival, which can be a basic roadmap for the selection of species or the development of new tolerant species in the future.

Water stress in plants of the Asteraceae family: a bibliometric analysis

The Asteraceae family is one of the most diverse, with more than 23,000 species distributed globally, with sunflowers and chamomile as members. In Brazil, Asteraceae stand out for their diversity, in addition to their great economic and ecological importance. In recent years, the cultivation of several species of the family has increased due to their medicinal, ornamental and food potential, driven mainly by incentives from institutions such as EMBRAPA. Given the above, the present study analyzes the academic literature on Asteraceae using bibliometric methods through the Scopus platform. The results showed an annual growth of 4.15% in publications on "Asteraceae" and "water deficit" between 1990 and 2023, with a significant increase from 2017 onwards. It is concluded that research on Asteraceae and deficit water sector is expanding, with strong collaboration between researchers. However, there is a need for studies on control systems to develop sustainable management strategies, essential to face climate challenges and promote the resilience of Asteraceae.

Growth-promoting rhizobacteria improve physiological variables in lemon balm, Melissa officinalis L., subjected to water stress

Climate change has caused droughts in regions that previously did not have water issues, affecting the production of medicinal plants grown in small-scale agricultural units. Plants such as lemon balm, Melissa officinalis L., are sensitive to water stress, which reduces their yield. One alternative to mitigate water stress is the use of plant growth-promoting rhizobacteria (PGPR). However, in the high tropics of Colombia, the use of these microorganisms is not common due to a lack of knowledge about how they can improve water absorption and increase the yield of medicinal plants. This study aimed to determine the effect of native PGPR on lemon balm plants subjected to water stress conditions using a completely randomized design with six treatments and four replications. Applications of Bacillus cereus and Bacillus amyloliquefaciens were made, and the plants were subjected to two water levels (field capacity and 50% field capacity). Physiological variables of stomatal conductance, chlorophyll content, and fluorescence were measured at the end of the experiment. Bacillus cereus significantly improved growth parameters such as number of leaves (115.00±34.71), fresh weight of root (5.51±3.07 g) and shoot (8.32±4.27), Bacillus amyloliquefaciens increased stomatal conductance (401.3 μmol H2O m2 s1) in water-stressed plants. These results suggest that the use of native PGPR considerably improves the growth and development parameters of lemon balm plants and provides a viable alternative for farmers to enhance yield and resistance to water stress conditions.

Evaluation technologies for assessing drought tolerance of Kimchi cabbage seedlings using hyperspectral imaging and principal component analysis

Conventionally, methods for evaluating the tolerance of kimchi cabbage have primarily relied on visual inspection. The development of evaluation criteria based on hyperspectral imaging may help address the problem of decision-making errors arising from visual inspection. However, to evaluate the tolerance of kimchi cabbage using hyperspectral imaging, not only are hyperspectral big data processing and sophisticated exponential model development required, but also real-time evaluation technology with high field usability. This study presents an evaluation method for extracting vegetation information from hyperspectral data, logically analyzing the extracted data, validating the developed model, and ensuring field utility. The red-edge band between 680 and 700 nm is for evaluating the drought tolerance of Kimchi cabbage. The proposed method allows for assessing the drought tolerance of Kimchi cabbage seedlings within a range of 1 to 30, using a robust index with a variance of approximately 2.25 and a sensitivity index with a variance of around 8.4. Since the proposed nonlinear drought tolerance evaluation method must strongly correlate with the chlorophyll index, its performance was verified using the newly proposed cross-point analyzer. While nonlinear drought evaluation technology can serve as a robust analysis method based on extensive data, it has the disadvantage of requiring a long evaluation time. However, the additionally developed cross-point analyzer can improve the real-time capability of testing. Proper utilization of these two analytical technologies enhances the performance of robust and rapid drought tolerance evaluation for Kimchi cabbage seedlings. Therefore, this study introduces two techniques for non-destructively and quantitatively explaining plant water stress.

Supervised classification and circuit parameter analysis of electrical bioimpedance spectroscopy data of water stress in tomato plants

Drought poses a significant challenge by inducing water stress in crops, urgently calling for effective monitoring and early intervention. In this work, we conducted a comprehensive 38-day investigation of the bioimpedance of water stressed tomato stems under controlled environmental conditions. A total of 8000 measurements were meticulously collected across a frequency spectrum spanning from 100 Hz to 10 MHz. The collected data was categorized into control, early stress, and late stress groups, corresponding to distinct phases of water stress treatment. To analyze the data, we employed established equivalent circuit models, including Cole, Randles, and double Cole. Subsequently, we evaluated the performance of eight machine learning algorithms widely-used in predicting the water stress stages of the plants. Remarkably, the Cole model, in conjunction with a multi-layer perceptron (MLP) algorithm, demonstrated robust performance, achieving an impressive F1 score of 0.89. In fact, in the control group, 378 out of 388 instances were accurately identified. However, misclassifications were observed in the early and late stress groups, with 31 out of 179 and 14 out of 208 instances mislabeled, respectively. Furthermore, we scrutinized the Cole model’s circuit parameters over time, providing insights aligned with the plant physiological behavior documented in the literature. Our findings suggest that MLP models trained on stem bioimpedance data hold promise as a valuable technique for estimating water stress in tomato plants, offering an essential tool for proactive management by farmers.

Direct and Remote Sensing Monitoring of Plant Salinity Stress in a Coastal Back-Barrier Environment: Mediterranean Pine Forest Stress and Mortality as a Case Study

The increase in atmospheric and soil temperatures in recent decades has led to unfavorable conditions for plants in many Mediterranean coastal environments. A typical example can be found along the coast of the Campania region in Italy, within the “Volturno Licola Falciano Natural Reserve”, where a pine forest suffered a dramatic loss of trees in 2021. New pines were planted in 2023 to replace the dead ones, with a larger tree layout and interspersed with Mediterranean bushes to replace the dead pine forest. A direct (in situ) monitoring program was planned to analyze the determinants of the pine salinity stress, coupled with Sentinel-2 L2A data; in particular, multispectral indices NDVI and NDMI were provided by the EU Copernicus service for plant status and water stress level information. Both the vadose zone and shallow groundwater were monitored with continuous logging probes. Vadose zone monitoring indicated that salinity peaked at a 30 cm soil depth, with values up to 1.9 g/L. These harsh conditions, combined with air temperatures reaching peaks of more than 40 °C, created severe difficulties for pine growth. The results of the shallow groundwater monitoring showed that the groundwater salinity was low (0.35–0.4 g/L) near the shoreline since the dune environment allowed rapid rainwater infiltration, preventing seawater intrusion. Meanwhile, salinity increased inland, reaching a peak at the end of the summer, with values up to 2.8 g/L. In November 2023, salts from storm-borne aerosols (“sea spray”) deposited on the soil caused the sea-facing portion of the newly planted pines to dry out. Differently, the pioneer vegetation of the Mediterranean dunes, directly facing the sea, was not affected by the massive deposition of sea spray. The NDMI and NDVI data were useful in distinguishing the old pine trees suffering from increasing stress and final death but were not accurate in detecting the stress conditions of newly planted, still rather short pine trees because their spectral reflectance largely interfered with the adjacent shrub growth. The proposed coupling of direct and remote sensing monitoring was successful and could be applied to detect the main drivers of plant stress in many other Mediterranean coastal environments.

Water Footprint Assessment of Agricultural Production in Bilecik Province

The freshwater sources are under serious pressure both in terms of quality characteristics due to pollution and in terms of quantity due to the increase in parameters such as temperature and evaporation under the influence of global warming. To ensure sustainable use of these resources, it is necessary to employ high-efficiency pressurized irrigation systems and cultivate plant species that are resilient to various stress factors and highly productive. In determining the water usage characteristics of plants, rapid atmospheric effects brought by climate change, plant water and temperature stress, soil moisture should be monitored, and water production indicators should be determined. In the water-intensive agricultural sector, monitoring the water footprint has become one of the important indicators in terms of ensuring water-food-energy sustainability, efficient use and fair sharing of water resources. This study aims to determine the water footprint of agricultural production in Bilecik province and its districts located in the transitional zone. Accordingly, values of crop and livestock production throughout the province and using a volume-based approach, the water footprint of crop production is estimated at 0.6 billion cubic meters (BCM), while the water footprint of livestock production is 0.5 BCM, resulting in a total agricultural water footprint of 1.1 BCM. In crop production, green water footprint constitutes 33%, blue water footprint 59%, and grey water footprint 8% of the total water footprint. The data obtained will form the basis for developing strategies in sustainable water and food management, aligned with climate change scenarios, to achieve sectoral supply-demand balance.

Understanding the leaf rolling of paddy and exploring its management options under aerobic rice

Rice is a staple food in the diets of more than half of the world's population. With India's irregular rainfall patterns and continual environmental anomalies, particularly in Kerala, the identification of climate-smart management practices which can withstand drought is critical. In this context, atrial was conducted in the experimental plots to evolve effective water and nutrient management practices under aerobic rice in lateritic soils of Kerala. However, during the experiment in a few treatments, rolling of leaves was observed, and when explored for the reasons, it was due to soil moisture deficit and plant water stress. When compared to other crop species, rice is highly vulnerable to water deficit. In this regard, an attempt has been made to study the leaf rolling pattern in aerobic rice and how this can be managed with a few soil amendments so that rice productivity can be sustained. The results showed that plant growth parameters, relative water content (RWC), membrane leakage (ML) and spectral signatures were significantly affected by the leaf rolling. It was found that leaf rolling affected plants have less RWC and higher ML and are under drought stress. Pearson correlation analysis showed a strong positive correlation (P < 0.05) of key spectral indices with other physiological traits such as RWC and negatively correlated with ML. Moisture absorbent media such as cocopeat, compost, saw dust and vermiculite were attempted as management strategies to overcome this stress. Results showed that among the absorbents attmepted, cocopeat was found to be better in managing the stress. These results suggest that for aerobic rice under lateritic soil, moisture absorbent media such as cocopeat, has to be incorporated so that it can reduce the rate of leaf rolling thereby sustaining the paddy yield.