Leaf Water Content Research Articles

A Review of Leaf-Level Flammability Traits in Eucalypt Trees

With more frequent and intense fires expected under future climate conditions, it is important to understand the mechanisms that control flammability in Australian forests. We followed a systematic review approach to determine which physical traits make eucalypts leaves more or less flammable. Specifically, we reviewed 20 studies that covered 35 eucalypt species across five countries and found that leaf water content, leaf area (LA), and specific leaf area (SLA) are the main drivers of leaf flammability. These traits are easy and straightforward to measure, while more laborious traits (e.g., volatile organic compounds and structural carbohydrates) are seldom measured and reported. Leaf flammability also varies with species, and, while the biochemistry plays a role in how leaves burn, it plays a minor role in fire behaviour at landscape scales. This review highlights the range of different protocols used to measure flammability and leaf water content, warranting caution when comparing traits and results between studies. As a result, we propose a standardised protocol to measure leaf water content and advocate for long-term measurements of leaf traits and flammability. This study not only contributes to the understanding of how and why eucalypt leaves burn but also encourages research into the relative importance of traits in influencing flammability and provides a guide for selecting traits that can be monitored using satellite images to inform fire management policies and strategies.

The halotolerant exopolysaccharide-producing Rhizobium azibense increases the salt tolerance mechanism in Phaseolus vulgaris (L.) by improving growth, ion homeostasis, and antioxidant defensive enzymes

Globally, agricultural productivity is facing a serious problem due to soil salinity which often causes osmotic, ionic, and redox imbalances in plants. Applying halotolerant rhizobacterial inoculants having multifarious growth-regulating traits is thought to be an effective and advantageous approach to overcome salinity stress. Here, salt-tolerant (tolerating 300 mM NaCl), exopolysaccharide (EPS) producing Rhizobium azibense SR-26 (accession no. MG063740) was assessed for salt alleviation potential by inoculating Phaseolus vulgaris (L.) plants raised under varying NaCl regimes. The metabolically active cells of strain SR-26 produced a significant amount of phytohormones (indole-3-acetic acid, gibberellic acid, and cytokinin), ACC deaminase, ammonia, and siderophore under salt stress. Increasing NaCl concentration variably affected the EPS produced by SR-26. The P-solubilization activity of the SR-26 strain was positively impacted by NaCl, as demonstrated by OD shift in NaCl-treated/untreated NBRIP medium. The detrimental effect of NaCl on plants was lowered by inoculation of halotolerant strain SR-26. Following soil inoculation, R. azibense significantly (p ≤ 0.05) enhanced seed germination (10%), root (19%) shoot (23%) biomass, leaf area (18%), total chlorophyll (21%), and carotenoid content (32%) of P. vulgaris raised in soil added with 40 mM NaCl concentration. Furthermore, strain SR-26 modulated the relative leaf water content (RLWC), proline, total soluble protein (TSP), and sugar (TSS) of salt-exposed plants. Moreover, R. azibense inoculation lowered the concentrations of oxidative stress biomarkers; MDA (29%), H2O2 content (24%), electrolyte leakage (31%), membrane stability (36%) and Na+ ion uptake (28%) when applied to 40 mM NaCl-treated plants. Further, R. azibense increases the salt tolerance mechanism of P. vulgaris by upregulating the antioxidant defensive responses. Summarily, it is reasonable to propose that EPS-synthesizing halotolerant R. azibense SR-26 should be applied as the most cost-effective option for increasing the yields of legume crops specifically P. vulgaris in salinity-challenged soil systems.

Regulatory mechanisms of plant rhizobacteria on plants to the adaptation of adverse agroclimatic variables

The mutualistic plant rhizobacteria which improve plant development and productivity are known as plant growth-promoting rhizobacteria (PGPR). It is more significant due to their ability to help the plants in different ways. The main physiological responses, such as malondialdehyde, membrane stability index, relative leaf water content, photosynthetic leaf gas exchange, chlorophyll fluorescence efficiency of photosystem-II, and photosynthetic pigments are observed in plants during unfavorable environmental conditions. Plant rhizobacteria are one of the more crucial chemical messengers that mediate plant development in response to stressed conditions. The interaction of plant rhizobacteria with essential plant nutrition can enhance the agricultural sustainability of various plant genotypes or cultivars. Rhizobacterial inoculated plants induce biochemical variations resulting in increased stress resistance efficiency, defined as induced systemic resistance. Omic strategies revealed plant rhizobacteria inoculation caused the upregulation of stress-responsive genes—numerous recent approaches have been developed to protect plants from unfavorable environmental threats. The plant microbes and compounds they secrete constitute valuable biostimulants and play significant roles in regulating plant stress mechanisms. The present review summarized the recent developments in the functional characteristics and action mechanisms of plant rhizobacteria in sustaining the development and production of plants under unfavorable environmental conditions, with special attention on plant rhizobacteria-mediated physiological and molecular responses associated with stress-induced responses.

Foliar spraying of zinc oxide nanoparticles improves water transport and nitrogen metabolism in tomato (Solanum lycopersicum L.) seedlings mitigating the negative impacts of cadmium.

The use of bio-nanotechnology in agriculture-such as the biological applications of metal oxide nanoparticles (NPs)-greatly improves crop yield and quality under different abiotic stress factors including soil metal contamination. Here, we explore the effectiveness of zinc oxide (ZnO)-NPs (0, 50 mg/L) foliar spraying to ameliorate the detrimental effects of cadmium (Cd) on the water transport and nitrogen metabolism in tomato (Solanum lycopersicum Mill. cv. Chibli F1) plants grown on a Cd-supplied (CdCl2; 0, 10, 40 μM) Hoagland nutrient solution. The results depicted that the individually studied factors (ZnO-NPs and Cd) had a significant impact on all the physiological parameters analyzed. Independently to the Cd concentration, ZnO-NPs-sprayed plants showed significantly higher dry weight (DW) in both leaves and roots compared to the non-sprayed ones, which was in consonance with higher and lower levels of Zn2+ and Cd2+ ions, respectively, in these organs. Interestingly, ZnO-NPs spraying improved water status in all Cd-treated plants as evidenced by the increase in root hydraulic conductance (L0), apoplastic water pathway percentage, and leaf and root relative water content (RWC), compared to the non-sprayed plants. This improved water balance was associated with a significant accumulation of osmoprotectant osmolytes, such as proline and soluble sugars in the plant organs, reducing electrolyte leakage (EL), and osmotic potential (ψπ). Also, ZnO-NPs spraying significantly improved NO3- and NH4+ assimilation in the leaf and root tissues of all Cd-treated plants, leading to a reduction in NH4+ toxicity. Our findings point out new insights into how ZnO-NPs affect water transport and nitrogen metabolism in Cd-stressed plants and support their use to improve crop resilience against Cd-contaminated soils.

Use of compost to improve Technosol properties and spontaneous plant-soil relationships of Mediterranean species potentially suitable for urban greening

Organic-based amendments are promising, eco-friendly solutions among soil requalification strategies. In this context, the current study explored the application of compost to Technosols (2 kg m-2) to improve soil quality, making the substrate suitable for plant growth. Changes in soil quality have been assessed before compost addition (time zero, T0) and plant transplanting and at 2, 4 and 11 months (T2, T4, and T11) after plant establishment. To test the soil suitability for plant growth, we monitored (at T2, T4, and T11) structural and functional ecological traits in the herbaceous spontaneous species Malva sylvestris L. and in transplanted Mediterranean sclerophyllous Phillyrea angustifolia L., and Quercus ilex L., often used in the urban greening, also considering plant and soil relationships. Our study demonstrated that compost increased soil nutrients availability over time, favoring M. sylvestris physiological performance in long-lasting, compared to sclerophyllous, since the beginning of the application. M. sylvestris exhibited high photosynthetic efficiency and carbon investment in photosynthetic tissues (higher leaf area and lower leaf mass per area) on compost-enriched soil. On the other hand, P. angustifolia and Q. ilex, even if they did not benefit from compost addition for photosynthetic efficiency, after 11 months, maintained higher leaf water content despite limited soil water availability. These results encourage the use of compost in ameliorating the quality of Technosols for urban greening, also evidencing that the species’choice is pivotal in obtaining benefits from plants and a period longer than one year is needed for sclerophyllous to see beneficial effects.

A meta-analysis of photosynthetic efficiency and stress mitigation by melatonin in enhancing wheat tolerance

BackgroundOur meta-analysis examines the effects of melatonin on wheat under varying abiotic stress conditions, focusing on photosynthetic parameters, chlorophyll fluorescence, leaf water status, and photosynthetic pigments. We initially collected 177 publications addressing the impact of melatonin on wheat. After meticulous screening, 31 published studies were selected, encompassing 170 observations on photosynthetic parameters, 73 on chlorophyll fluorescence, 65 on leaf water status, 240 on photosynthetic pigments.ResultsThe analysis revealed significant heterogeneity across studies (I² > 99.90%) for the aforementioned parameters and evidence of publication bias, emphasizing the complex interaction between melatonin application and plant physiological responses. Melatonin enhanced the overall response ratio (lnRR) for photosynthetic rates, stomatal conductance, transpiration rates, and fluorescence yields by 20.49, 22.39, 30.96, and 1.09%, respectively, compared to the control (no melatonin). The most notable effects were under controlled environmental conditions. Moreover, melatonin significantly improved leaf water content and reduced water potential, particularly under hydroponic conditions and varied abiotic stresses, highlighting its role in mitigating water stress. The analysis also revealed increases in chlorophyll pigments with soil drenching and foliar spray, and these were considered the effective application methods. Furthermore, melatonin influenced chlorophyll SPAD and intercellular CO2 concentrations, suggesting its capacity to optimize photosynthetic efficiency.ConclusionsThis synthesis of meta-analysis confirms that melatonin significantly enhances wheat’s resilience to abiotic stress by improving photosynthetic parameters, chlorophyll fluorescence, leaf water status, and photosynthetic pigments. Despite observed heterogeneity and publication bias, the consistent beneficial effects of melatonin, particularly under controlled conditions with specific application methods e.g. soil drenching and foliar spray, demonstrate its utility as a plant growth regulator for stress management. These findings encourage focused research and application strategies to maximize the benefits of melatonin in wheat farming, and thus contributing to sustainable agricultural practices.

Dissecting wheat above-ground architecture for enhanced water use efficiency and grain yield in the subtropics

BackgroundGrowing wheat under climate change scenarios challenges, scientists to develop drought and heat-tolerant genotypes. The adaptive traits should therefore be explored and engineered for this purpose. Thus, this study aimed to dissect surface traits and optimizing the leaf architecture to enhance water use efficiency (WUE) and grain yield. Twenty-six wheat genotypes were assessed for five novel leaf traits (NLTs: leaf prickle hairs, groove type, rolling, angle and wettability) under normal, drought and heat conditions following triplicated factorial randomized complete block design (RCBD). The data for NLTs, physiological traits (stomatal conductance, WUE, transpiration, and photosynthesis), and standard morphological and yield traits were recorded. Leaves were sampled at the stem elongation stage (Zadoks 34) to measure the leaf water content (%), contact angle, and to obtain pictures through scanning electron microscopy (SEM). The air moisture harvesting efficiency was evaluated for five selected genotypes. The ideotype concept was applied to evaluate the best-performing genotypes.ResultsThe correlation analysis indicated that long leaf prickle hairs (> 100 μm), short stomatal aperture and density (40–60 mm− 2), inward to spiral leaf rolling, medium leaf indentation, low contact angle hysteresis (< 10°), and cuticular wax were positively associated with WUE. This, in turn, was significantly correlated to grain yield. Thus, the genotypes (E-1) with these traits and alternate leaf wettability had maximum grain yield (502 g m− 2) and WUE supported with high photosynthesis rate, and relative water content (94 and 75% under normal and stress conditions, respectively). However, the genotype (1-hooded) with dense leaf hairs on edges but droopy leaves, spiral leaf rolling, and lighter groove, also performed better in terms of grain yield (450 g m− 2) under heat stress conditions by maintaining high photosynthesis and WUE with low stomatal conductance and transpiration rate.ConclusionThe SEM analysis verified that the density of hairs on the leaf surface and epicuticular wax contributes towards alternate wettability patterns thereby increasing the water-use efficiency and yield of the wheat plant. This study paves a way towards screening and and developing heat and drought-tolerant cultivars that are water-saving and climate-resilient.

Evaluation of raspberry drought tolerance

Physiological parameters of drought tolerance of fi ve raspberry varieties (‘Meteor’, ‘Gusar’, ‘Lavina’, ‘Patricija’, and ‘Ulyabka’) and seven selected raspberry forms (4-122-2, 6-125-3, 1-76-1, 6-125-4, 2-83-21, 1-76-25, 2-90-3) were investigated. Experiments were conducted in 2022–2023 at the Kokinsky experimental station of the Federal Horticultural Center for Breeding, Agrotechnology and Nursery (Bryansk Oblast) and at the Center for Collective Use of Bryansk State Agrarian University. Drought tolerance was assessed based on the indices of total leaf water content, water defi cit, and water-retaining capacity in the phenophases of budding (May) and fruiting (July). The analysis showed that within one vegetation period, the total leaf water content and water-retaining capacity decreased from the phase of budding to that of fruiting, compared to water defi cit, which showed an inverse trend. The water-retaining capacity of the studied varieties was found to be higher in a drier season than in a moderatelyhumid year. A signifi cant variability among genotypes was observed in terms of water regime. During the fruiting phase, the total leaf water content decreased to an average level in all the studied genotypes (less than 70.0 %), except for the ‘Gusar’ and ‘Lavina’ varieties which demonstrated lower levels (less than 60.0 %). Forms outperforming in a number of leaf water regime parameters were identifi ed. Thus, the ‘Meteor’ variety, although showing high values of water content in the budding phenophase, was characterized by low water losses after 6-hour wilting (less than 30.0 %) and a leaf water defi cit (less than 10.0 %). Water defi cit in the ‘Ulyabka’ variety, as well as 6-125-4 and 2-90-3 selected forms, exceeded 10.0 % in the fruiting phenophase, corresponding to the average level of drought tolerance. The 2-83-21 form showed a reduced water-retaining capacity in the fruiting phenophase (water losses exceeded 30.0 %).

The effect of drought‐induced leaf traits onFicusleaf palatability is species specific

AbstractDrought has a significant impact on plant–insect interactions by altering plant survival, growth, leaf quality, and defense traits. Tropical plants are particularly vulnerable to water depression because of shallow root depth. In the context of climate change, drought events are expected to increase in frequency and intensity; however, their impact on tropical ecosystems remains poorly known. Insect herbivores represent the largest feeding guild of arthropods, and they devour four to five times more plant material than vertebrates do. Understanding how drought affects plant traits and leaf palatability in a keystone and ecologically diverse plant genus, such asFicus(Moraceae), is crucial for predicting how climate change might alter tropical plant–insect interactions. We examined the impact of drought intensity and duration on the leaf nutritional quality, defensive traits, and herbivory damage by caterpillars in three tropical and one MediterraneanFicusspecies in a greenhouse. We also conducted food choice trials with generalist caterpillars to evaluate the impact of drought on herbivores. Drought intensity and duration had no direct effect on leaf palatability across theFicusspecies. However, drought indirectly affected leaf palatability via drought‐induced leaf traits in a species‐specific manner. Drought intensity and duration decreased leaf water content, resulting in decreased leaf palatability inF. benjaminaandF. lyrata. Leaf defensive traits such as flavonoid concentration were affected by drought intensity and decreased leaf palatability inF. carica. Drought influenced the leaf traits ofF. elastica, but none of them affected leaf palatability. Overall, this study establishes the link between drought and insect feeding on plants via leaf traits. The species‐specific responses to drought highlight the significance of climate‐related plant life histories in relation to climate change, underscoring the need for further investigations.

Impact of Photosynthetic Efficiency on Watermelon Cultivation in the Face of Drought

Water availability is a limiting factor for plant production, especially in Brazilian semi-arid regions. The main aim of the study was to investigate the physiological effects of drought during the fruiting stage of watermelon cultivation. A completely randomized block design with four replications and six treatments varied by the number of lateral drip tapes (1 or 2) and the duration of drought stress (0, 4, and 8 days) was used. The following parameters were evaluated: relative chlorophyll content, relative leaf water content, electrolyte leakage, CO2 assimilation (A), stomatal conductance (gs), internal CO2 concentration, leaf temperature, transpiration (E), water use efficiency (WUE), carboxylation efficiency (CE), yield, thickness, diameter, length, and fruit °brix, at 4 and 8 days of drought. Drought negatively affected photosynthesis, particularly in treatments with a single dripper and 4 days of drought, resulting in reductions of up to 60% in A, 68% in gs, 44% in E, 58% in WUE, and 59% in CE, but did not have a significant effect on watermelon yield after 4 or 8 days of irrigation. It was concluded that drought influences the physiological responses of watermelon plants, mainly in reducing photosynthesis, but does not drastically affect fruit productivity in short periods of stress.

A causal trait model for explaining foliar water uptake capacity

AbstractQuestionsPlants largely vary in their capacity for foliar water uptake (FWU), that is, the capacity to increase leaf water content by directly absorbing water from leaf‐wetting events. Climate change will reduce leaf wetting and increase drought events. Therefore, we need a better understanding of the underlying traits and mechanisms that facilitate FWU.LocationSeasonally dry tropical montane grasslands in Brazil (Campos de Altitude).MethodsWe measured FWU and leaf traits related to wettability, surface conductance, water potential and water storage on up to 55 plant species. By using Direct Acyclic Graph theory and Bayesian modelling, we tested how those leaf traits affect FWU.ResultsWe found that stomatal conductance largely explained interspecific variation in FWU, which was also favoured in species with hydrophilic leaves, high cuticular conductance, more negative leaf water potentials, low dry‐matter content, isohydric behaviour, and more elastic cell walls.ConclusionsDue to the existence of trade‐offs, not all species exhibit an optimal combination of traits that favours FWU. Instead, co‐occurring species have achieved a similar capacity for FWU through distinct trait combinations. Consequently, species engaged in FWU may exhibit differential vulnerabilities to climate change as they can cope with drought using other strategies beside FWU.

Water Use Strategies and Shoot and Root Traits of High-Yielding Winter Wheat Cultivars under Different Water Supply Conditions

Drought is the most important factor limiting winter wheat yield in the North China Plain (NCP). Choosing high-yielding cultivars is an important measure to minimize the negative effects of drought stress. Field studies were conducted with 10 cultivars in the 2020–2022 seasons under three irrigation treatments (I0, without irrigation; I1, irrigated at jointing stage; I2, irrigated at jointing and anthesis stages) in the NCP to examine the water use strategies and root and shoot traits of high-yielding cultivars under different water supply conditions. The results showed that yield variation among cultivars was 21.2–24.6%, 23.7–25.9% and 11.6–15.3% for the I0, I1 and I2 treatments, respectively. Under water deficit conditions (I0 and I1), high-yielding cultivars reduced water use during vegetative stages and increased soil water use during reproductive stages, especially water use from deeper soil layers. Those cultivars with higher root length density (RLD) in deep soil layers exhibited higher water uptake. Each additional millimeter of water used after anthesis from the 100–200 cm soil layers increased grain yield by 23.6–29.6 kg/ha and 16.4–28.5 kg/ha under I0 and I1, respectively. This water use strategy enhanced dry matter accumulation after anthesis, decreased canopy temperature (CT) and increased relative leaf water contents (RLWC), which ultimately improved grain yield. For winter wheat grown under I2, cultivars that decreased water use after anthesis had higher water productivity (WP). Root length (RL), root weight (RW) and root:shoot ratio were each negatively correlated with grain yield, while above-ground biomass was positively correlated with grain yield. Therefore, higher dry matter accumulation and smaller root systems are two important traits of high-yielding cultivars under sufficient water supply conditions (I2) in the NCP.

GhMAPK3, a mitogen-activated protein kinase, enhance salt and drought tolerance in cotton (Gossypium hirsutum)

Multiple abiotic stresses, such as drought and high salinity, seriously limit cotton production. However, the mitogen-activated protein kinases (MAPKs) could play a critical role in responding to multiple environmental abiotic stresses. In this study, one of the MAPKs in cotton, GhMAPK3 (GH_D03G1517), was cloned and its role in drought and salt stress tolerance was investigated. The qRT-PCR assays demonstrated that GhMAPK3 predominantly expressed in leaf and root parts and showed higher expression under salt and drought stress. Subcellular localization assays revealed that GhMAPK3 was distributed in the nucleus and cytoplasm. The silenced of GhMAPK3 could decrease the tolerance of cotton plants under salt and drought stress via virus-induced gene silencing (VIGS) experiments. In GhMAPK3-slienced plants, the expression of stress-responsive genes has been revealed to be down-regulated levels, while the oxidants and antioxidant enzymes showed relatively higher levels and relatively lower levels, respectively. We further acquired three GhMAPK3 overexpression Arabidopsis lines, and they showed higher drought and salt tolerance than the wild-type (WT) plants, the chlorophyll content and relative leaf water content were found to be relatively stable through GhMAPK3 overexpressed plants under the abiotic stress. Further investigation revealed that GhMAPK3 showed a higher germination rate and longer root length under salt and drought stress. Overall, our findings revealed that the GhMAPK3 gene plays a prominent role in drought and salt tolerance and offers knowledge on crop genetic improvements.

The PROLIB leaf radiative transfer model: Simulation of the dorsiventrality of leaves from visible to mid-wave infrared

Many plant species have dorsiventral leaves that have significant differences in optical properties from one side to the other. Several studies have revealed that ignoring this asymmetry induces significant errors in plant canopy reflectance, and current leaf models simulating leaf dorsiventrality are limited to the 0.4–2.5 μm wavelength range. This article, partly based on two recently collected datasets in the 2.5–14 μm wavelength range, demonstrates that ignoring leaf dorsiventrality induces significant errors in brightness temperature and effective emissivity at the canopy scale. The PROLIB model, which inherits from the PROSPECT-VISIR and LIBERTY models, is the first radiative transfer model to simulate the reflectance and transmittance of both leaf sides from 0.4 to 5.7 μm. The palisade and spongy mesophylls are represented as plate and sphere layers, respectively, to account for the structural asymmetry of leaf cells. The sieve effect that explains the differences in transmittance between the adaxial and abaxial sides of the leaf is successfully incorporated into PROLIB. Evaluation of the model on several leaf datasets shows that: (1) It reproduces well the adaxial and abaxial optical properties of the leaves, with a root mean square error (RMSE) of 0.0109 for reflectance and transmittance. (2) It can be inversed to retrieve leaf traits, with RMSE values for leaf chlorophyll, carotenoid, anthocyanin, water, and dry matter content of 5.519 μg/cm2, 2.344 μg/cm2, 4.219 μg/cm2, 0.0022 g/cm2, and 0.0017 g/cm2, respectively (corresponding normalized RMSE values of 22.0%, 34.0%, 49.4%, 19.6%, and 24.7%). However, better and more complete leaf datasets are needed for leaf dorsiventrality analysis and model calibration.

UAV-Based Remote Sensing to Evaluate Daily Water Demand Characteristics of Maize: A Case Study from Yuci Lifang Organic Dry Farming Experimental Base in Jinzhong City, China

Soil moisture critically influences crop growth, especially in dryland environments. Precise agricultural management requires real-time monitoring of stratified soil moisture and assessment of crops’ daily water needs. We aim to provide low-cost, high-throughput information acquisition services for dryland regions with underdeveloped infrastructure and offer scientific support for sustainable water resource management. We used UAVs (Unmanned Aerial Vehicles) with multi-spectral sensors for routine maize monitoring, capturing leaf reflectance. Constructing vegetation indices, we quantified the relationship between leaf water content and surface soil moisture, using the Biswas model to predict deep soil moisture distribution. We used UVAs to monitor crop height and calculated the daily water demand for the entire growth period of corn using the Penman Montes equation. We found an R2 of 0.8603, RMSE of 2.455%, and MAE of 2.099% between NDVI and canopy leaf water content. A strong linear correlation (R2 = 0.7510) between canopy leaf water content and soil moisture was observed in the top 20 cm of soil. Deep soil moisture inversion from the top 20 cm soil moisture showed an R2 of 0.9984, with RE mostly under 10%, but exceeding 20% at 120 cm depth. We also constructed a maize height model aligning with a sigmoidal growth curve (R2 = 0.9724). Maize’s daily water demand varied from 0.7121 to 9.4263 mm, exhibiting a downward-opening parabolic trend. Integration of rainfall and soil water data allowed for dynamic irrigation adjustments, mitigating drought and water stress effects on crops. We highlighted UAV multi-spectral imaging’s effectiveness in monitoring crop water needs, facilitating quick daily water requirement estimations. Our work offers a scientific foundation for managing maize cultivation in drylands, enhancing water resource utilization.

Trade‐Off Between Light Deprivation and Desiccation in Intertidal Seagrasses Due To Periodic Tidal Inundation and Exposure: Insights From a Data‐Calibrated Model

AbstractSome seagrass species thrive in shallow intertidal zones globally, adapting to periodic tidal inundation and exposure with distinctive physiological traits and offering crucial ecosystem services. However, predicting the responses of intertidal seagrasses to external stressors is hampered by the complexity of the dynamic and harsh environments they occupy. Intertidal seagrass growth models, especially those incorporating dynamic physiological responses, are scarce in the literature. Our study comprehensively collated relevant data from the literature to parameterize the relationship between air exposure, seagrass leaf water content and photosynthetic efficiency to inform new growth rate functions for generalizable intertidal seagrass growth models. We tested the applicability of these model formulations for scenarios with varying physiological process assumptions, seagrass species, tidal conditions, meadow elevations and water turbidity. We found that neglecting air‐exposed physiological responses (i.e., leaf water content loss and reduced photosynthetic efficiency) can substantially overestimate seagrass growth rates. We also observed a trade‐off between light deprivation and desiccation on intertidal seagrass growth under specific tidal ranges and turbidity conditions. This can yield an “optimal” elevation where overall stress of desiccation (increasing with meadow elevation) and light deprivation (decreasing with meadow elevation) are minimized. The predicted optimal elevation, that is, the most suitable habitat for intertidal seagrass, moves upward as water turbidity increases. Our study provides conceptual and quantitative guidance for ecological modelers to include air exposure responses of intertidal seagrasses in coastal ecosystem models. The model also helps to evaluate the viability of intertidal seagrass habitats and inform decisions on coastal ecosystem management under changing environmental conditions.

تأثير الرش بمضادات النتح على النمو، الانتاجية وصفات الجودة للقطن المصري تحت ظروف الاجهاد المائي للأراضي الطينية

Two field experiments were conducted at Sakha, Agricultural Research Station, Egypt in two growing seasons during 2021 and 2022 seasons, to study the effect of three irrigation intervals (every 15, 30 and 45 days) and four foliar application with some anti-transpirants (without , linseed Oil (7%), Pure Gylatine (1.5 %) Magnesium Carbonate for dusting (250 g / plot), Potassium Silicate (3cm3 K2SiO3 / liter) on the growth, productivity, quality of Egyptian cotton plants (Super Giza 94 cultivar) and some water relations .The experiment was designed by using split plot design with three replicates. The results showed that, irrigation cotton plants every 30 days significantly increased leaf water content%, chlorophyll (a) in the second season, chlorophyll (b), number of open bolls / plant, earliness % in the second season, seed cotton yield, boll weight, seed index all in the two growing seasons compared with other two irrigation intervals. On the other hand, irrigation every 15 days was more effective on plant height, number of fruiting branches per plant in both seasons, fineness in the first season, fiber length in the second season and fiber strength in the two seasons. Foliar application of anti- transpirants significantly increased in the most studied characters, leaf water content%, chlorophyll a and b , plant height, number of fruiting branches, number of open bolls, earliness %, seed cotton yield, boll weight , seed index , fiber fineness , fiber strength and fiber length except fiber uniformity which was not affected in the two seasons as compared with the control in the two seasons. The highest values were obtained from potassium silicate compared with other anti- traspirants. Concerning the interaction effect between irrigation interval and anti-transpirants , the data indicated that the application of Potassium Silicate and irrigation cotton plants every 30 days produced the highest significant increase in leaf water content %, chlorophyll a , chlorophyll b , number of fruiting branches ,seed cotton yield and earliness % in the first and second season.

Inside-out: Synergising leaf biochemical traits with stomatal-regulated water fluxes to enhance transpiration modelling during abiotic stress.

As the global climate continues to change, plants will increasingly experience abiotic stress(es). Stomata on leaf surfaces are the gatekeepers to plant interiors, regulating gaseous exchanges that are crucial for both photosynthesis and outward water release. To optimise future crop productivity, accurate modelling of how stomata govern plant-environment interactions will be crucial. Here, we synergise optical and thermal imaging data to improve modelled transpiration estimates during water and/or nutrient stress (where leaf N is reduced). By utilising hyperspectral data and partial least squares regression analysis of six plant traits and fluxes in wheat (Triticum aestivum), we develop a new spectral vegetation index; the Combined Nitrogen and Drought Index (CNDI), which can be used to detect both water stress and/or nitrogen deficiency. Upon full stomatal closure during drought, CNDI shows a strong relationship with leaf water content (r2 = 0.70), with confounding changes in leaf biochemistry. By incorporating CNDI transformed with a sigmoid function into thermal-based transpiration modelling, we have increased the accuracy of modelling water fluxes during abiotic stress. These findings demonstrate the potential of using combined optical and thermal remote sensing-based modelling approaches to dynamically model water fluxes to improve both agricultural water usage and yields.

Improving the prediction performance of leaf water content by coupling multi-source data with machine learning in rice (Oryza sativa L.)

BackgroundLeaf water content (LWC) significantly affects rice growth and development. Real-time monitoring of rice leaf water status is essential to obtain high yield and water use efficiency of rice plants with precise irrigation regimes in rice fields. Hyperspectral remote sensing technology is widely used in monitoring crop water status because of its rapid, nondestructive, and real-time characteristics. Recently, multi-source data have been attempted to integrate into a monitored model of crop water status based on spectral indices. However, there are fewer studies using spectral index model coupled with multi-source data for monitoring LWC in rice plants. Therefore, 2-year field experiments were conducted with three irrigation regimes using four rice cultivars in this study. The multi-source data, including canopy ecological factors and physiological parameters, were incorporated into the vegetation index to accurately predict LWC in rice plants.ResultsThe results presented that the model accuracy of rice LWC estimation after combining data from multiple sources improved by 6–44% compared to the accuracy of a single spectral index normalized difference index (ND). Additionally, the optimal prediction accuracy of rice LWC was produced using a machine algorithm of gradient boosted decision tree (GBDT) based on the combination of ND(1287,1673) and crop water stress index (CWSI) (R2 = 0.86, RMSE = 0.01).ConclusionsThe machine learning estimation model constructed based on multi-source data fully utilizes the spectral information and considers the environmental changes in the crop canopy after introducing multi-source data parameters, thus improving the performance of spectral technology for monitoring rice LWC. The findings may be helpful to the water status diagnosis and accurate irrigation management of rice plants.

Estimating leaf photosynthetic capacity using hyperspectral reflectance: Model variability and transferability

Leaf photosynthetic capacity is a crucial parameter for characterizing plant growth status and global nitrogen-carbon cycles. While leaf trait and reflectance models have been widely applied to assess leaf photosynthetic capacity across various plant species, the variability and transferability of these estimation models remain unclear. Thus, this study investigated the variability in estimating leaf maximum carboxylation rate of Rubisco (Vcmax, μmol m−2 s−1) using hyperspectral reflectance across seven plant species datasets. To improve model transferability, we proposed model updating by adding new samples and developed a stacking model to integrate multiple regression model results to reduce variability in the predictions. The PROSPECT model, coupled with spectral derivatives and similarity metrics, was used to retrieve leaf structural and biochemical traits. Our results showed that Vcmax was significantly correlated with the contents of leaf chlorophyll (Cab) and protein (Prot), and other traits such as leaf structure, carotenoid content, and water content also influenced Vcmax. However, the strength of these correlations varied among different datasets due to differences in vegetation types, growth periods, and the number of species. Leaf trait relationships also varied with datasets, with Cab proving to be a good proxy of photosynthesis across all datasets. Leaf traits were superior to leaf reflectance in characterizing the differences between datasets. While leaf reflectance performed well in estimating Vcmax for most datasets, leaf traits were more suitable for constructing transferable estimation models of Vcmax between different datasets. Model transferability was affected by differences in datasets, such as data range and plant species. Model updating by adding 10% new samples significantly improved the assessment of Vcmax, with leaf reflectance yielding better estimation results. Our data also revealed that different models produced inconsistent results, and a stacking model combining multiple models optimized the estimation of Vcmax using leaf traits and reflectance, with the cross-validation coefficient of determination and relative root mean square error of 0.88 and 19.92%, respectively. These findings offer new methods and ideas for assessing leaf photosynthetic capacity across different agro-ecosystems. Further recalibration of the proposed model with canopy radiative transfer models and datasets would enable monitoring of plant photosynthesis at large scales.