Changes In Leaf Water Content Research Articles

AI-assisted image analysis and physiological validation for progressive drought detection in a diverse panel of Gossypium hirsutum L.

Drought detection, spanning from early stress to severe conditions, plays a crucial role in maintaining productivity, facilitating recovery, and preventing plant mortality. While handheld thermal cameras have been widely employed to track changes in leaf water content and stomatal conductance, research on thermal image classification remains limited due mainly to low resolution and blurry images produced by handheld cameras. In this study, we introduce a computer vision pipeline to enhance the significance of leaf-level thermal images across 27 distinct cotton genotypes cultivated in a greenhouse under progressive drought conditions. Our approach involved employing a customized software pipeline to process raw thermal images, generating leaf masks, and extracting a range of statistically relevant thermal features (e.g., min and max temperature, median value, quartiles, etc.). These features were then utilized to develop machine learning algorithms capable of assessing leaf hydration status and distinguishing between well-watered (WW) and dry-down (DD) conditions. Two different classifiers were trained to predict the plant treatment-random forest and multilayer perceptron neural networks-finding 75% and 78% accuracy in the treatment prediction, respectively. Furthermore, we evaluated the predicted versus true labels based on classic physiological indicators of drought in plants, including volumetric soil water content, leaf water potential, and chlorophyll a fluorescence, to provide more insights and possible explanations about the classification outputs. Interestingly, mislabeled leaves mostly exhibited notable responses in fluorescence, water uptake from the soil, and/or leaf hydration status. Our findings emphasize the potential of AI-assisted thermal image analysis in enhancing the informative value of common heterogeneous datasets for drought detection. This application suggests widening the experimental settings to be used with deep learning models, designing future investigations into the genotypic variation in plant drought response and potential optimization of water management in agricultural settings.

Remotely sensed normalized difference red-edge index for rangeland biomass estimation

PurposeThe purpose of this study is rangeland biomass estimation and its spatial–temporal dynamics. Remote sensing has been a significant method for estimating biomass in recent years. The connection between vegetation index and field biomass will be used to assign probabilities, but in some cases, it does not provide acceptable results because of soil background and geographical and temporal variability.Design/methodology/approachIn this study, the normalized difference red-edge (NDRE) index was used to calculate the rangeland biomass in comparison to five vegetation indices. Field measurements of biomass of natural rangeland in the West of Iran were taken in 2015, 2018 and 2021, and SENTINEL-2 data were used for analysis.FindingsThe results indicated that the overall advantage of NDRE stems from the fact that it adjusts for changes in leaf water content while overcoming the detrimental effects of soil substrate heterogeneity, both of these factors have a significant impact on pasture biomass. These results suggest that an NDRE-based biomass estimation model might be useful for estimating and monitoring biomass in large rangelands with significant geographical and temporal variability.Originality/valueIdentifying the best vegetation index to establish a vegetation-based biomass regression model for rangelands in large areas with different climatic conditions, plant compositions and soil types is the overall aim of this study.

Monitoring plant water status via static uniaxial compression of the leaf lamina.

Turgor pressure is an essential, but difficult to measure indicator of plant water status. Turgor has been quantified by localized compression of cells or tissues, but a simple method to perform these measurements is lacking. We hypothesized that changes in leaf turgidity can be monitored by uniaxially compressing the leaf lamina and measuring the mechanical stress under a constrained thickness (stress relaxation)and that changes in leaf water content can be monitored by measuring the leaf thickness under constant mechanical stress. Using a simple, custom-built leaf squeeze-flow rheometer, we performed different compression tests on leaves from 13 plant species. The mechanical stress measured during stress relaxation was correlated with leaf bulk turgor pressure (R2 > 0.95) and thus with balancing pressure (R2 > 0.94); the leaf thickness measured under constant mechanical stress was correlated with relative water content (R2 > 0.74). The coefficients of these relationships were related to the leaf bulk osmotic pressure at the turgor-loss point. An idealized average-cell model suggests that, under isothermal conditions, the stationary bulk modulus during compression is largely determined by the bulk osmotic pressure. Our study presents an inexpensive, accessibleand automatable method to monitor plant water status noninvasively.

北京山区干旱胁迫下侧柏叶片水分吸收策略

PDF HTML阅读 XML下载 导出引用 引用提醒 北京山区干旱胁迫下侧柏叶片水分吸收策略 DOI: 10.5846/stxb202010072553 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41877152）；林果业生态环境功能提升协同创新中心（市级）项目（CEFF-PXM2019_014207_000099） Leaf water absorption of Platycladus orientalis under drought stress in Beijing Author: Affiliation: Fund Project: National Natural Science( 41877152)；Project of Collaborative Innovation Center (municipal level) for forest and Fruit Industry ecological Environment Function Improvement( CEFF-PXM2019_014207_000099) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:干旱与半干旱地区，水分是限制树木生长的重要影响因子。由于降水稀缺且分配不均，叶片吸收水分是此地区树木吸收和利用小量级降水和凝结水的主要方式。北京山区处于易旱少雨的生态脆弱地带，森林植被经常遭受干旱胁迫，所以对该地区的森林系统而言，叶片直接吸收利用截留的降雨是干旱时期树木获得水分的重要途径。基于野外对比控制试验和室内盆栽模拟试验，选取北京山区的主要造林树种侧柏为研究对象，进行利用天然降雨与模拟降雨试验，研究降雨前后侧柏叶片吸水特征，探究侧柏在干旱环境下如何通过叶片吸水缓解干旱胁迫。结果表明：当侧柏长期处于干旱胁迫状态时，叶片可以利用降雨，从中获益用来缓解树木的干旱胁迫状态；叶片的吸水能力与降雨强度呈正相关关系，与土壤含水率呈负相关关系；重度干旱下侧柏植株在降雨强度为15 mm/h时叶片吸水现象最明显，叶水势变化最大为（1.18±0.17） MPa，叶片含水率变化最大为（8.47±1.00） mg/cm2；当土壤水率高于20.8%时，基本不发生叶片吸水现象。试验结果说明在干旱地区叶片吸水是树木除根系吸水外的重要水分来源方式，并且对干旱地区有效利用短缺水资源，减轻植物水分亏缺具有重要意义。 Abstract:In arid and semi-arid areas, water is an important factor that restricts the growth of trees. Due to the scarcity and uneven distribution of precipitation, the leaf absorption of water is the main way for trees in this area to absorb and use small amounts of precipitation and condensate. The mountainous area of Beijing is located in an ecologically fragile zone prone to drought and less rain. Forest vegetation often suffers from drought stress. Therefore, for the forest system in this area, the direct absorption and use of intercepted rainfall by leaves is an important way for trees to obtain water during dry periods. Based on field comparative control experiments and indoor pot plant simulation experiments, Platycladus orientalis, the main afforestation tree species in Beijing mountainous areas, was selected as the research object. Natural rainfall and simulated rainfall experiments were carried out to study the water absorption characteristics of Platycladus orientalis leaf before and after rainfall, and explore how Platycladus orientalis under arid environment alleviate drought stress by absorbing water by leaves. The results show that when Platycladus orientalis is under drought stress for a long time, the leaves can use rainfall to alleviate the drought stress of trees; the water absorption capacity of leaves is positively correlated with rainfall intensity and negatively correlated with soil moisture content; Under severe drought, Platycladus orientalis plants have the most obvious water absorption phenomenon when the rainfall intensity is 15 mm/h. The maximum change in leaf water potential is (1.18±0.17) MPa, and the maximum change in leaf water content is (8.47±1.00) mg/cm2; When the soil moisture content is higher than 20.8%, there is basically no water absorption by the blades. The test results show that leaf water absorption in arid areas is an important source of water for trees in addition to root water absorption, and it is of great significance for effective use of scarce water resources in arid areas and alleviating plant water deficit. 参考文献 相似文献 引证文献

Shifting cultivation induced burn area dynamics using ensemble approach in Northeast India

Identifying shifting cultivation areas and assessing their spatio-temporal dynamics are essential in framing climate-adaptive policies for efficient forest management and agriculture practices for the benefit of people. The current study attempts to develop an alternative approach to classify the shifting cultivation areas using an ensemble technique, integrating multiple spectral indices in three states of northeast India (NEI), such as Assam, Manipur, and Meghalaya. The adopted approach integrates green cover and leaf water content changes during shifting cultivation land preparation in Landsat imagery. The deforested burned area patches were identified based on threshold values using Landsat data-derived indices on vegetation, burned area and leaf water, and digital elevation model (DEM). The ensemble approach provided shifting cultivation maps with good overall accuracy (> 83%). The maximum shifting cultivation area was observed in Assam (126.87 km2), followed by Meghalaya (51.53 km2) and Manipur (46.04 km2) in 2016. The normalized difference vegetation index (NDVI) and NDVI difference performed better than other vegetation indices. The ensemble approach can be applied in other regions with minor modifications in threshold values, thus having the potential for accounting to shifting cultivation dynamics on an operational basis. Future research may include blending local traditional knowledge and modern scientific solutions for improved forest and land resources planning for the benefit of inhabitants and the mountain environment under the climate change scenarios.

A Mobile NMR Sensor and Relaxometric Method to Non-destructively Monitor Water and Dry Matter Content in Plants.

Water content (WC) and dry matter content (DMC) are some of the most basic parameters to describe plant growth and yield, but are exceptionally difficult to measure non-invasively. Nuclear Magnetic Resonance (NMR) relaxometry may fill this methodological gap. It allows non-invasive detection of protons in liquids and solids, and on the basis of these measures, can be used to quantify liquid and dry matter contents of seeds and plants. Unfortunately, most existing NMR relaxometers are large, unwieldy and not suitable to measure intact plants or to be used under field conditions. In addition, currently the appropriate NMR relaxometric methods are poorly suited for non-expert use. We here present a novel approach to overcome these drawbacks. We demonstrate that a basic NMR relaxometer with the capability to accept intact plants, in combination with straightforward NMR and data processing methods, can be used as an NMR plant sensor to continuously, quantitatively and non-invasively monitor changes in WC and DMC. This can be done in vivo, in situ, and with high temporal resolution. The method is validated by showing that measured liquid and solid proton densities accurately reflect WC and DMC of reference samples. The NMR plant sensor is demonstrated in an experimental context by monitoring WC of rice leaves under osmotic stress, and by measuring the dynamics of water and dry matter accumulation during seed filling in a developing wheat ear. It is further demonstrated how the method can be used to estimate leaf water potential on the basis of changes in leaf water content.

The induction of salt stress tolerance by jasmonic acid treatment in roselle (Hibiscus sabdariffa L.) seedlings through enhancing antioxidant enzymes activity and metabolic changes

The objective of the present study was to assess the effects of exogenous application of 1 mM Jasmonic acid (JA), an endogenous plant growth regulator, on mitigation of oxidative and osmotic stresses caused by various levels of NaCl: none (0 mM), light (50 mM), moderate (150 mM), and severe (300 mM) in roselle (Hibiscus sabdariffa L.) seedlings. Salt stress without any change in leaf water content negatively affected seedlings growth from the aspect of plant height, root length, leaf morphological properties, plant biomass and levels of pigments, reducing sugars, starch, proteins and free amino acids, but accumulated higher levels of non-reducing sugars, total phenols, anthocyanins, flavonoids, proline and increased activities of both enzymatic and non-enzymatic antioxidants, such as ascorbate peroxidase (APX), pyrogallol peroxidase (PPX) and polyphenol oxidase (PPO). JA-treated seedlings exhibited a significant increase in growth parameters and activities of APX and PPX under salt stress, with hyper-accumulation of metabolite levels, but accumulated lower amounts of dry matter in roots and decreased the activity of PPO. These results clearly showed that exogenous JA treatment protected roselle seedlings against salt-induced damage through up-regulating the activity of H2O2-decomposing enzymes, osmoprotectants biosynthesis, and the accumulation of metabolites.

Prediction and monitoring of leaf water content in soybean plants using terahertz time-domain spectroscopy

Leaf water content (LWC) is one of the physiological parameters most commonly used for describing crop growth status and productivity. Thus, rapid and non-destructive methods for the prediction of LWC are important. Here, a rapid and accurate LWC monitoring method using terahertz time-domain spectroscopy (THz-TDS) was tested on soybean. A high-precision mathematical model was developed to predict LWC based on the results of THz-TDS. Next, the model was used to study the effect of various levels of water -stress, different growth media, and leaf treatment with exogenous ABA. Reliable results showed that the correlation coefficient and root mean square error of the prediction set were 0.9153 and 0.0526, respectively. LWC gradually decreased over time under different moisture treatments, and even more slowly under conditions of normal water supply than under water stress. The trend followed by LWC under water deficit was dependent on the water-holding capacity of the growth medium. Soil had the best water-holding capacity, followed by the seedling matrix and the vermiculite matrix. Furthermore, the stomata of the adaxial and abaxial leaf surfaces closed due to water deficit, as determined by laser scanning confocal microscopy (LSCM). We found that stomatal opening in leaves significantly decreased under water stress to prevent excessive water loss, consistent with the observed reduction in leaf moisture content. Results indicated a rapid increase in LWC upon ABA treatment followed by a slower decrease. Similarly, changes in stomatal opening were observed using LSCM, consistent with the changes in leaf water content detected macroscopically. This study showed that THz radiation technology combined with modeling methods provides an effective, contact-free, safe, and non-destructive technique to measure water content in soybean leaves. This technique could facilitate further study of plant-water relations.

Estimating leaf water content at the leaf scale in soybean inoculated with arbuscular mycorrhizal fungi from in situ spectral measurements

Leaf water content (LWC) of crops is a suitable parameter for evaluation of plant water status and arbuscular mycorrhizal effect on the host plant under drought stress. Remote sensing technology provides an effective avenue to estimate LWC in crops. However, few LWC retrieval models have been developed specifically for the arbuscular mycorrhizal inoculated crops. In this study, soybean with inoculation and non-inoculation treatments were planted under the severe drought, moderate drought and normal irrigation levels. The LWC changes under different treatments at the 30th, 45th and 64th day after the inoculation were investigated, and the spectral response characteristics of inoculated and non-inoculated soybean leaves under the three drought stresses were analyzed. Five types of spectral variables/indices including: raw spectral reflectance (R), continuum-removed spectral reflectance (RC), difference vegetation index (DVI), normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) were applied to determine the best estimator of LWC. The results indicate that LWC decreased as the aggravating of drought stress levels. However, LWC in inoculated leaves was higher than that in the counterparts under the same drought stress level, and the values of raw reflectance measured at inoculated leaves were lower than the non-inoculated leaves, especially around 1900 nm and 1410 nm. These water spectral features were more evident in the corresponding continuum-removed spectral reflectance. The newly proposed DVIC(2280, 1900) index, derived from the continuum-removed spectral reflectance at 2280 nm and the raw spectral reflectance at 1900 nm in DVI type of index, was the most robust for soybean LWC assessment, with R2 value of 0.72 (p < 0.01) and root mean square error (RMSE) and mean absolute error (MAE) of 2.12% and 1.75%, respectively. This study provides a means to monitor the mycorrhizal effect on drought-induced crops indirectly and non-destructively. Keywords: leaf water content, remote sensing, arbuscular mycorrhizal fungi, drought, crops DOI: 10.25165/j.ijabe.20191206.4950 Citation: Kong W P, Huang W J, Zhou X F, Mortimer H, Ma L L, Tang L L, et al. Estimating leaf water content at the leaf scale in soybean inoculated with arbuscular mycorrhizal fungi from in situ spectral measurements. Int J Agric & Biol Eng, 2019; 12(6): 149–155.

Estimating leaf water content at the leaf scale in soybean inoculated with arbuscular mycorrhizal fungi from in situ spectral measurements

Leaf water content (LWC) of crops is a suitable parameter for evaluation of plant water status and arbuscular mycorrhizal effect on the host plant under drought stress. Remote sensing technology provides an effective avenue to estimate LWC in crops. However, few LWC retrieval models have been developed specifically for the arbuscular mycorrhizal inoculated crops. In this study, soybean with inoculation and non-inoculation treatments were planted under the severe drought, moderate drought and normal irrigation levels. The LWC changes under different treatments at the 30th, 45th and 64th day after the inoculation were investigated, and the spectral response characteristics of inoculated and non-inoculated soybean leaves under the three drought stresses were analyzed. Five types of spectral variables/indices including: raw spectral reflectance (R), continuum-removed spectral reflectance (RC), difference vegetation index (DVI), normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) were applied to determine the best estimator of LWC. The results indicate that LWC decreased as the aggravating of drought stress levels. However, LWC in inoculated leaves was higher than that in the counterparts under the same drought stress level, and the values of raw reflectance measured at inoculated leaves were lower than the non-inoculated leaves, especially around 1900 nm and 1410 nm. These water spectral features were more evident in the corresponding continuum-removed spectral reflectance. The newly proposed DVIC(2280, 1900) index, derived from the continuum-removed spectral reflectance at 2280 nm and the raw spectral reflectance at 1900 nm in DVI type of index, was the most robust for soybean LWC assessment, with R2 value of 0.72 (p < 0.01) and root mean square error (RMSE) and mean absolute error (MAE) of 2.12% and 1.75%, respectively. This study provides a means to monitor the mycorrhizal effect on drought-induced crops indirectly and non-destructively. Keywords: leaf water content, remote sensing, arbuscular mycorrhizal fungi, drought, crops DOI: 10.25165/j.ijabe.20191206.4950 Citation: Kong W P, Huang W J, Zhou X F, Mortimer H, Ma L L, Tang L L, et al. Estimating leaf water content at the leaf scale in soybean inoculated with arbuscular mycorrhizal fungi from in situ spectral measurements. Int J Agric & Biol Eng, 2019; 12(6): 149–155.

The potential of the spectral 'water balance index' (WABI) for crop irrigation scheduling.

Hyperspectral sensing can detect slight changes in plant physiology, and may offer a faster and nondestructive alternative for water status monitoring. This premise was tested in the current study using a narrow-band 'water balance index' (WABI), which is based on independent changes in leaf water content (1500nm) and the efficiency of the nonphotochemical quenching (NPQ) photo-protective mechanism (531nm). The hydraulic, photo-protective and spectral behaviors of five important crops - grapevine, corn, tomato, pea and sunflower - were evaluated under water deficit conditions in order to associate the differences in stress physiology with WABI suitability. Rapid alterations in both leaf water content and NPQ were observed in grapevine, pea and sunflower, and were effectively captured by WABI. Apart from water status monitoring, the index was also successful in scheduling the irrigation of a vineyard, despite phenological and environmental variability. Conversely, corn and tomato displayed a relatively strict stomatal regime and/or mild NPQ responses and were, thus, unsuitable for WABI-based monitoring. WABI shows great potential for irrigation scheduling of various crops, and has a clear advantage over spectral models that focus on either of the abovementioned physiological mechanisms.

Hyperspectral characterization of freezing injury and its biochemical impacts in oilseed rape leaves

Automatic detection and monitoring of freezing injury in crops is of vital importance for assessing plant physiological status and yield losses. This study investigates the potential of hyperspectral techniques for detecting leaves at the stages of freezing and post-thawing injury, and for quantifying the impacts of freezing injury on leaf water and pigment contents. Four experiments were carried out to acquire hyperspectral reflectance and biochemical parameters for oilseed rape plants subjected to freezing treatment. Principal component analysis and support vector machines were applied to raw reflectance, first and second derivatives (SDR), and inverse logarithmic reflectance to differentiate freezing and the different stages of post-thawing from the normal leaf state. The impacts on biochemical retrieval using particular spectral domains were also assessed using a multivariate analysis. Results showed that SDR generated the highest classification accuracy (>95.6%) in the detection of post-thawed leaves. The optimal ratio vegetation index (RVI) generated the highest predictive accuracy for changes in leaf water content, with a cross validated coefficient of determination (R2cv) of 0.85 and a cross validated root mean square error (RMSEcv) of 2.4161mg/cm2. Derivative spectral indices outperformed multivariate statistical methods for the estimation of changes in pigment contents. The highest accuracy was found between the optimal RVI and the change in carotenoids content (R2CV=0.70 and RMSECV=0.0015mg/cm2). The spectral domain 400–900nm outperformed the full spectrum in the estimation of individual pigment contents, and hence this domain can be used to reduce redundancy and increase computational efficiency in future operational scenarios. Our findings indicate that hyperspectral remote sensing has considerable potential for characterizing freezing injury in oilseed rape, and this could form a basis for developing satellite remote sensing products for crop monitoring.

Identifying leaf traits that signal stress in TIR spectra

Plants under constant water and temperature stress experience a chain of reactions that in the long term alter their leaf traits (morphology, anatomy and chemistry). The use of these traits as proxies for assessing plant stress was so far mainly based on conventional laboratory methods, which are expensive and time-consuming. Remote sensing methods based on spectral changes can detect changes in pigments and productivity using the visible and near infrared. However, the use of infrared spectra, where changes in the spectra are associated with physical changes of the leaf, is still incipient.In this study plants of Rhododendron cf. catawbiense, were exposed to low temperatures and low soil water content during a six months experiment. The spectral response in the infrared region 1.4–16μm, microstructural variables, leaf water content, leaf area and leaf molecules such as lignin and cellulose concentrations were measured in individual leaves after the period of stress. This study revealed that under cold conditions plants have most changes in leaf water content, lignin and cellulose concentrations and leaf area, while under drought conditions the most striking change is water loss. These leaf trait modifications are also correlated with changes in thermal infrared spectra, showing their potential as proxies for detecting plant stress in this species. A multinomial model allows the estimation of the stress treatments imposed on these plants from their infrared spectra. This model reveals a group of 15 bands in the SWIR and MWIR between 2.23 and 7.77μm, which show relatively large changes, and had an overall accuracy of 87%.Finally, individual partial least squares regression models show that lignin, cellulose, leaf water content and leaf area are the leaf traits reacting significantly to long-term stress and that are also generating measurable changes in the infrared spectra. Although these models are based on laboratory data, the congruence of the identified bands with the fundamental molecular vibrations used in remote sensing, shows the potential of these findings in the assessment of plant stress.

Modeling biophysical controls on canopy foliage water 18O enrichment in wheat and corn

AbstractLeaf water 18O enrichment is an important factor controlling the H218O, C18OO, and O18O exchanges between the biosphere and the atmosphere. At present, there is limited capacity to explain the enrichment mechanisms in field conditions. In this study, three models of varying complexity were used to simulate the leaf water 18O enrichment at the canopy scale. Comparisons were made among the models and with high‐frequency isotopic measurements of ecosystem water pools in wheat and corn. The results show that the steady state assumption was a better approximation for ecosystems with lower canopy resistance, that it is important to consider the effect of leaf water turnover in modeling the enrichment and not necessary to deal with time changes in leaf water content, and that the leaf‐scale Péclet effect was incompatible with the big‐leaf modeling framework for canopy‐air interactions. After turbulent diffusion has been accounted for in an apparent kinetic factor parameterization, the mean 18O composition of the canopy foliage water was a well‐behaved property predictable according to the principles established by leaf‐scale studies, despite substantial variations in the leaf water enrichment with leaf and canopy positions. In the online supplement we provided a discussion on the observed variability of leaf water 18O composition with leaf and canopy positions and on the procedure for correcting isotopic measurements for organic contamination.

Can changes in leaf water potential be assessed spectrally?

Leaf water potential (LWP) is an important indicator of plant water status. However, its determination via classical pressure-chamber measurements is tedious and time-consuming. Moreover, such methods cannot easily account for rapid changes in this parameter arising from changes in environmental conditions. Spectrometric measurements, by contrast, have the potential for fast and non-destructive measurements of plant water status, but are not unproblematic. Spectral characteristics of plants vary across plant development stages and are also influenced by environmental factors. Thus, it remains unclear whether changes in leaf water potential per se can reliably be detected spectrometrically or whether such measurements also reflect autocorrelated changes in the leaf water content (LWC) or the aerial plant biomass. We tested the accuracy of spectrometric measurements in this context under controlled climate chamber conditions in series of six experiments that minimised perturbing influences but allowed for significant changes in the LWP. Short-term exposure of dense stands of plants to increasing or decreasing artificial light intensities in a growth chamber more markedly decreased LWP than LWC in both wheat and maize. Significant relationships (R2-values 0.74-0.92) between LWP and new spectral indices ((R940/R960)/NDVI; R940/R960) were detected with or without significant changes in LWC of both crop species. The exact relationships found, however, were influenced strongly by the date of measurement or water stress induced. Thus, global spectral relationships measuring LWP probably cannot be established across plant development stages. Even so, spectrometric measurements supplemented by a reduced calibration dataset from pressure chamber measurements might still prove to be a fast and accurate method for screening large numbers of diverse lines.

Changes in water content and distribution in Quercus ilex leaves during progressive drought assessed by in vivo 1H magnetic resonance imaging.

BackgroundDrought is a common stressor in many regions of the world and current climatic global circulation models predict further increases in warming and drought in the coming decades in several of these regions, such as the Mediterranean basin. The changes in leaf water content, distribution and dynamics in plant tissues under different soil water availabilities are not well known. In order to fill this gap, in the present report we describe our study withholding the irrigation of the seedlings of Quercus ilex, the dominant tree species in the evergreen forests of many areas of the Mediterranean Basin. We have monitored the gradual changes in water content in the different leaf areas, in vivo and non-invasively, by 1H magnetic resonance imaging (MRI) using proton density weighted (ρw) images and spin-spin relaxation time (T2) maps.Resultsρw images showed that the distal leaf area lost water faster than the basal area and that after four weeks of similar losses, the water reduction was greater in leaf veins than in leaf parenchyma areas and also in distal than in basal leaf area. There was a similar tendency in all different areas and tissues, of increasing T2 values during the drought period. This indicates an increase in the dynamics of free water, suggesting a decrease of cell membranes permeability.ConclusionsThe results indicate a non homogeneous leaf response to stress with a differentiated capacity to mobilize water between its different parts and tissues. This study shows that the MRI technique can be a useful tool to follow non-intrusively the in vivo water content changes in the different parts of the leaves during drought stress. It opens up new possibilities to better characterize the associated physiological changes and provides important information about the different responses of the different leaf areas what should be taken into account when conducting physiological and metabolic drought stress studies in different parts of the leaves during drought stress.

Response to water stress of some oleander cultivars suitable for pot plant production

Oleander ( Nerium oleander L.) is an evergreen shrub of great ornamental interest which, in recent times, has been increasingly used as a flowering pot plant. Plants grown in pots undergo more frequent water stress conditions than those grown in the soil, due to the limited volume of substrate available for the roots. Oleander is a species adaptable to dry conditions and able to survive long periods of drought. It is well known that under water stress conditions all plants reduce photosynthetic activity, resulting in reduced plant growth. In case of severe water stress, leaves undergo strong wilting and senescence resulting in the loss of ornamental value. In the present work, a study was conducted to evaluate the ecophysiological response to water stress in four oleander cultivars previously recognised (on the basis of traits such as size, habit, earliness, abundance and duration of flowering, aptitude for cutting propagation and rapidity of growth) as suitable for pot plant production. Our data confirm the high drought tolerance of oleander. In the studied cultivars, plants submitted to water stress showed only minor variations in leaf gas exchange parameters [transpiration ( E), stomatal conductance ( g s) and CO 2 net assimilation ( A)] for at least 10 days without a change in leaf water content [assessed as relative water content (RWC)] for 22 days from the beginning of the stress treatment. During this period, non-irrigated plants maintained the same water status as control plants and were visually undistinguishable from them. Moreover, plants survived without water supply for one month. Following the supply of water again, they were able to restore RWC, gas exchange parameters and instantaneous water use efficiency [ A/ E ratio (WUE inst)] to the values of control plants. Furthermore, if at the end of the stress period plants appeared withered and were pale green in colour, they regained their normal appearance after they were irrigated again. Although the four studied cultivars showed some minor differences in leaf gas exchange parameters and in the manner in which the latter parameters changed after irrigation was stopped, the response to water stress was essentially the same. Therefore, as far as drought tolerance is concerned, all these cultivars have a good aptitude for use as flowering pot plants.

Sensitivity studies of the moisture effects on MODIS SWIR reflectance and vegetation water indices

The effects of soil moisture and leaf water content on canopy reflectance of MODIS shortwave infrared (SWIR) bands 5, 6, and 7 and water‐related indices are studied quantitatively using the coupled soil–leaf–canopy reflectance model. Canopy spectra simulations under various input conditions show that soil moisture has a large effect on each SWIR reflectance at low leaf area index (LAI) values, among which band 5 is the most sensitive to soil moisture variations, while band 7 responds strongest to dry soil conditions. Band 5 is also better suited to measure leaf water content change, since it obtains a higher variation when leaf water content changes from dry to wet. In general, each SWIR band responds to soil moisture and leaf water content differently. By using the normalized calculation between the water absorption‐sensitive band and insensitive band, the Normalized Difference Water Index shows the most capability to remove the soil background effect and enhance the sensitivity to leaf water content. These two moisture variables may be separated by combining multiple rather than one SWIR band with a near‐infrared band considering that each SWIR band has a different response to soil moisture and leaf water content.

Extraneous variables and their influence on reflectance-based measurements of leaf water content

Leaf water indices based on leaf reflectance may depend not only on the variable of interest, leaf water content, but may also be influenced by a variety of extraneous variables, leading to considerable data variability if such extraneous variables are not eliminated or taken into account. Here, we examined the nature of three potential extraneous variables: homogeneity of the leaf target area, the distance between a primary reflecting leaf and background material, and measurement sensitivity at various wavelengths. Although leaf water indices appear to be homogeneously distributed between major leaf veins, they may fluctuate substantially in areas where major veins are present. Leaf water indices may also depend to some extent on the distance between a primary reflecting leaf and any reflecting background material, at least for small distances. Leaf water indices utilizing the 970 or 1200 nm water absorption bands have been shown to be rather insensitive to changes in leaf water content, potentially resulting in low signal-to-noise ratios, an additional source of data variability.

Photosynthetic and growth responses of juvenile Chinese kale (Brassica oleracea var. alboglabra) and Caisin (Brassica rapa subsp. parachinensis) to waterlogging and water deficit

Abstract Chinese kale (Brassica oleracea var. alboglabra) and Caisin (Brassica rapa subsp. parachinensis) are leafy vegetable crops grown in south-east Asian countries where rainfall varies dramatically from excess to deficit within and between seasons. We investigated the physiological and growth responses of these plants to waterlogging and water deficit in a controlled experiment in a glasshouse. Juvenile plants were subjected to waterlogging or water deficit for 19 days in case of Chinese kale and 14 days in case of Caisin and compared with well-watered controls. Caisin tolerated waterlogging better than Chinese kale because it produced hypocotyl roots and gas spaces developed at the stem base. In Chinese kale, waterlogging reduced plant fresh weight (90%), leaf area (86%), dry weight (80%) and leaf number (38%). In contrast, waterlogging had no impact on leaf number in Caisin and reduced plant fresh and dry weights and leaf area by 60–70%. Water deficit reduced leaf area, fresh weight and dry weight of both species by more than half. Leaf number in Chinese kale was reduced by 38% but no effect occurred in Caisin. Water deficit increased the concentration of nitrogen in the leaf dry matter by more than 60% in both species and the leaf colour of water deficient plants was dark green compared with the leaf colour of well-watered plants. Soil water deficit delayed flowering of Caisin while waterlogging accelerated it. Thickening and whitening of the cuticle on the leaves of Chinese kale probably increased its ability to retain water under drought while Caisin adjusted osmotically and Chinese kale did not. Waterlogging and water deficit had strong effects on leaf gas exchange of both Brassica species. Water deficit closed the stomata in both species and this was associated with a leaf water content of 9 g g−1 DW. In contrast, waterlogging reduced conductance from 1.0 to 0.1 mol H2O m−2 s−1 in direct proportion to changes in leaf water content, which fell from 11 to 5 g g−1 DW. This separation of the effects of water deficit and waterlogging on conductance was reflected in transpiration, internal CO2 concentration and net photosynthesis. In conclusion, Chinese kale and Caisin showed rather different adaptations in response to waterlogging and water deficit. Caisin was more tolerant of waterlogging than Chinese kale and also showed evidence of tolerance of drought. There is genetic variation to waterlogging within the Brassica genus among the leafy vegetables that could be used for cultivar improvement.