Variation In Chlorophyll Content Research Articles

Variation of Chlorophyll Content Among the Different Tulsi Species Found in Nuapada District, Odisha

The Tulsi plant, also known as Holy Basil, is a sacred herb in Hinduism and is revered for its medicinal properties as well. It belongs to the Lamiaceae (mint) family and is native to the Indian subcontinent. Tulsi is widely cultivated and is found in many Hindu households where it is worshipped daily. In this work there was an attempt to made to find out chlorophyll content of different Tulsi species found in Nuapada district, Odisha. In this work we were compare chlorophyll pigment of 4 different species of tulsi of Nuapda such as Ocimum tenuiflorum (black tulshi), Ocimum sanctum (green tulshi), Ocimum basilcum (dohna) and Ocimum gratissuma (van tulshi). Among them maximum total chlorophyll content found in Ocimum tenuifflorum And list in Ocimum sanctum. The chlorophyll a found maximum in Ocimum basilcum. And minimum in Ocimum gratissuma.The chlorophyll b found maximum in Ocimum basilcum and minimum in Ocimum tenuiflorum. The total chlorophyll found Ocimum gratissum and minimum in Ocimum sanctum. Such type of work provides us data regarding distribution of chlorophyll in different species of a genera.

Estimation of Paddy leaves Chlorophyll Content Using Convolutional Neural Network (CNN)

In contemporary agriculture, the demand for cutting-edge machine-learning techniques to elevate crop assessment and management is paramount. This study introduces an innovative approach employing a Convolutional Neural Network (CNN) with Inception_v3 as its base model to estimate chlorophyll levels in paddy leaves. The primary aim is to craft a robust, precise model capable of non-destructively predicting chlorophyll content, promising substantial improvements in the efficiency of evaluating paddy crop health and nutritional status. The dataset comprises 566 images of paddy leaves, spanning 122 unique chlorophyll content levels. A meticulous data partitioning strategy allocates 244 images for model training, with 122 and 180 images for validation and testing, respectively. Model performance metrics include a test loss of 1.19 and a test accuracy of 0.81. Leveraging the Inception_v3 architecture empowers the CNN model to extract intricate, distinguishing features from paddy leaf images. This capability enables the model to discern subtle variations in chlorophyll content across different classes, underpinning its promising predictive prowess. Future research directions may explore potential model enhancements and dataset expansion, marking significant progress toward revolutionizing crop health assessment in modern agriculture.

Design of equilibrium modified atmosphere packaging for postharvest cabbages preservation based on introducing available active sites into film materials as gas transport channels

This work aims to explore an available avenue to design an equilibrium modified atmosphere packaging (EMAP) by the modification of gas permeability of material. In this work, the introduction of available active sites endowed materials with adjustable gas permeability properties. With varying concentrations of the resulting materials with various gas permeability, the CO2 and O2 gas permeability of the blending films were modified at the range of 3.92 ∼ 17.84 barrier and 0.65 ∼ 3.46 barrier, respectively. On this basis, the films were used as EMAP to preserve postharvest cabbages. The results indicated that each EMAP achieved an equilibrium atmosphere containing 6.8 % ∼ 3.8 % CO2 and 2.1 % ∼ 5.2 % O2 within 15 h and maintained it continuously. In these atmosphere, the respiratory rate of the preserved cabbages was significantly inhibited, thereby delaying the deterioration of their storage quality. As the results, sensory scores of the preserved samples were maximally maintained. Declines of color indexes and texture indexes were obviously inhibited. Chemical variations in chlorophyll content, total phenolics content, total flavonoids content, ascorbic acid and nitrite content were significantly suppressed. The overall findings revealed that this method is suitable and promising to develop EMAP for the postharvest vegetables.

Chlorophyll Content Variation in Wheat Genotypes Planted in Semi-Arid Region

To achieve better productivity and fill the shortage caused by population increase and decrease of current wheat genotypes productivity. As a part of many studies, this study came to distinguish 21 wheat genotypes about their chlorophyll content in comparison with 3 local varieties eventually electing the superior genotypes in chlorophyll content and associated with high yield which are suitable for arid and semi-arid areas. Functioning chlorophyll enables crops to maintain photosynthesis capacity for a longer time after anthesis under the condition of water and heat stresses and this leads to longer grain filling periods and eventually higher yield. All wheat genotypes (24 genotypes) were planted according to RCBD in a research station of the College of Agriculture/ University of Anbar, western IRAQ. The findings of this study indicated genotypes with high yield and have considerable chlorophyll content, especially after flowering including “4, 6, 7, 9, 29, 31, 39, 41” and therefore can be nominated for plant breeding programs. In addition, those genotypes can be used for production in the region of western Iraq. Further studies and investigations are required to reach considerable stability in those genotypes.

AcHZP45 is a repressor of chlorophyll biosynthesis and activator of chlorophyll degradation in kiwifruit.

The degradation of chlorophyll during fruit development is essential to reveal a more 'ripe' color that signals readiness to wild dispersers of seeds and the human consumer. Here, comparative biochemical analysis of developing fruit of Actinidia deliciosa cv. Xuxiang ('XX', green-fleshed) and Actinidia chinensis cv. Jinshi No.1 ('JS', yellow-fleshed) indicated that variation in chlorophyll content is the major contributor to differences in flesh color. Four differentially expressed candidate genes were identified: the down-regulated genes AcCRD1 and AcPOR1 involved in chlorophyll biosynthesis, and the up-regulated genes AcSGR1 and AcSGR2 driving chlorophyll degradation. Prochlorophyllide and chlorophyllide, the metabolites produced by AcCRD1 and AcPOR1, progressively reduced in 'JS', but not in 'XX', indicating that chlorophyll biosynthesis was less active in yellow-fleshed fruit. AcSGR1 and AcSGR2 were verified to be involved in chlorophyll degradation, using both transient expression in tobacco and stable overexpression in kiwifruit. Furthermore, a homeobox-leucine zipper (HD-Zip II), AcHZP45, showed significantly increased expression during 'JS' fruit ripening, which led to both repressed expression of AcCRD1 and AcPOR1 and activated expression of AcSGR1 and AcSGR2. Collectively, the present study indicated that different dynamics of chlorophyll biosynthesis and degradation coordinate the changes in chlorophyll content in kiwifruit flesh, which are orchestrated by the key transcription factor AcHZP45.

Regional Algorithm for Estimating High Coccolithophore Concentration in the Northeastern Part of the Black Sea

A modified regional algorithm to quantify the coccolithophore concentration in the northeastern part of the Black Sea under conditions of intense bloom is presented. To modify the algorithm, the data of in situ measurements of coccolithophore Emiliania huxleyi abundance performed in June 2017 and 2022 (when the maximum values were 9 × 106 and 13 × 106 Cells L−1, respectively), as well as the data from hydro-optical and satellite measurements, were used. In addition, the ratio between the number of detached coccoliths and coccolithophore cells was taken into account. Based on the expanded array of in situ data, the optimal values of the regional algorithm parameters were obtained. The modified algorithm makes it possible to obtain more accurate results in areas of high coccolithophore concentrations and takes into account the contribution of coccoliths. To test the sensitivity of the algorithm to variations in bio-optical characteristics, model calculations were performed using Hydrolight software. The updated algorithm is significantly less sensitive to variations in chlorophyll concentration and CDOM absorption coefficient than its previous version.

Chlorophyll Meter: A Precision Agricultural Decision-Making Tool for Nutrient Supply in Durum Wheat (Triticum turgidum L.) Cultivation under Drought Conditions

How crop biodiversity adapts to drought conditions and enhances grain yield became the most important issue facing agronomists and plant breeders at the turn of the century. Variations in genetic response, inadequacy of nutrients in the soil, and insufficient access to nutrients are factors that aggravate drought stressors. The development of screening tools for identifying drought tolerance is important in the deployment of durum wheat varieties suited to drought-prone environments. An experiment was conducted to evaluate durum wheat varieties under a range of nutrient supplies in naturally imposed drought conditions. The treatments consisting of two nitrogen regimes (i.e., control and 60 kg ha-1), four durum wheat varieties, and three types of nutrients (control, sulfur, and zinc) that were arranged in a split-split plot design with three replications. Both foliar-based sulfur and zinc fertilization were employed at the flag leaf stage, at a rate of 4 and 3-L ha-1, respectively. The results showed a significant (p < 0.05) genetic variation in chlorophyll concentration, grain protein content, tillering potential, and leaf area index. Varieties that contained better leaf chlorophyll content had improved grain yield by about 8.33% under 60 kg/ha nitrogen. A combined application of nitrogen and zinc at flag leaf stage significantly improved grain yield of Duragold by about 21.3%. Leaf chlorophyll content was found to be a more important trait than spikes per m2 to discriminate durum wheat varieties. Foliar application of sulfur increased the grain yield of drought-stressed plants by about 12.23%. Grain yield and protein content were strongly correlated with late-season SPAD readings. Significant (p < 0.05) correlation coefficients were obtained between normalized difference vegetation index, leaf area index, grain yield, and protein content with late-season chlorophyll content, revealing the importance of chlorophyll content in studying and identifying drought-tolerant varieties.

Variations in chlorophyll content, stomatal conductance, and photosynthesis in Setaria EMS mutants

Chlorophyll (Chl) content, especially Chl b content, and stomatal conductance (Gs) are the key factors affecting the net photosynthetic rate (Pn). Setaria italica, a diploid C4 panicoid species with a simple genome and high transformation efficiency, has been widely accepted as a model in photosynthesis and drought-tolerance research. The current study characterized Chl content, Gs, and Pn of 48 Setaria mutants induced by ethyl methanesulfonate. A total of 24, 34, and 35 mutants had significant variations in Chl content, Gs, and Pn, respectively. Correlation analysis showed a positive correlation between increased Gs and increased Pn, and a weak correlation between decreased Chl b content and decreased Pn was also found. Remarkably, two mutants behaved with significantly decreased Chl b content but increased Pn compared to Yugu 1. Seven mutants behaved with significantly decreased Gs but did not decrease Pn compared to Yugu 1. The current study thus identified various genetic lines, further exploration of which would be beneficial to elucidate the relationship between Chl content, Gs, and Pn and the mechanism underlying why C4 species are efficient at photosynthesis and water saving.

Multi-temporal UAV Imaging-Based Mapping of Chlorophyll Content in Potato Crop

Spectral indices based on unmanned aerial vehicle (UAV) multispectral images combined with machine learning algorithms can more effectively assess chlorophyll content in plants, which plays a crucial role in plant nutrition diagnosis, yield estimation and a better understanding of plant and environment interactions. Therefore, the aim of this study was to use UAV-based spectral indices deriving from UAV-based multispectral images as inputs in different machine learning models to predict canopy chlorophyll content of potato crops. The relative chlorophyll content was obtained using a SPAD chlorophyll meter. Random Forest (RF), support vector regression (SVR), partial least squares regression (PLSR) and ridge regression (RR) were employed to predict the chlorophyll content. The results showed that RF model was the best performing algorithm with an R2 of 0.76, Root Mean Square Error (RMSE) of 1.97. Both RF and SVR models showed much better accuracy than PLSR and RR models. This study suggests that the best models, RF model, allow to map the spatial variation in chlorophyll content of plant canopy using the UAV multispectral images at different growth stages.

Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize Crop

The deployment of novel technologies in the field of precision farming has risen to the top of global agendas in response to the impact of climate change and the possible shortage of resources such as water and fertilizers. The present research addresses the performance of water and nitrogen-sensitive narrow-band vegetation indices to evaluate the response of sweet maize (Zea mays var. saccharata L.) to different irrigation and nitrogen regimes. The experiment was carried out in Valenzano, Bari (Southern Italy), during the 2020 growing season. Three irrigation regimes (full irrigation, deficit irrigation, and rainfed) and two nitrogen levels (300 and 50 kg ha−1) were tested. During the growing season, a Field Spec Handheld 2 spectroradiometer operating in the range of 325–1075 nm was utilized to capture spectral data regularly. In addition, soil water content, biometric parameters, and physiological parameters were measured. The DATT index, based on near-infrared and red-edge wavelengths, performed better than other indices in explaining the variation in chlorophyll content, whereas the double difference index (DD) showed the greatest correlation with the leaf–gas exchange. The modified normalized difference vegetation index (NNDVI) and the ratio of water band index to normalized difference vegetation index (WBI/NDVI) showed the highest capacity to distinguish the interaction of irrigation x nitrogen, while the best discriminating capability of these indices was under a low nitrogen level. Moreover, red-edge-based indices had higher sensitivity to nitrogen levels compared to the structural and water band indices. Our study highlighted that it is critical to choose proper narrow-band vegetation indices to monitor the plant eco-physiological response to water and nitrogen stresses.

Time Course of Age-Linked Changes in Photosynthetic Efficiency of Spirodela polyrhiza Exposed to Cadmium.

Short-term assessment of adverse effects is essential for populations exposed to higher risk of environmental pollution. This study presents the time course of physiological and morphological changes attributed to cadmium, emphasizing age-linked differences in the susceptibility of photosynthetic apparatus of Spirodela polyrhiza fronds exposed to different cadmium concentrations. A four-frond colony represented by mother, daughter, and granddaughter plants was exposed to cadmium concentrations for 6, 24, and 72 h to establish its effect on different generations of the great duckweed. The duration of cadmium exposure accounted for the most variation in chlorophyll content as the most influential variable, and after 72 h, frond responsiveness was a function of cadmium concentration. Carotenoid contents behaved slightly differently in fronds of different ages, with the oldest mother frond exhibiting accelerated senescence. Chlorophyll fluorescence measurements showed that cadmium affects different photosynthetic electron transport segments relative to the frond's chloroplast structure level. Photosynthesis of mother fronds exposed to low cadmium and daughter fronds exposed to high cadmium was determined by the functionality of primary electron acceptance at the PSII level. Mother plants exposed to higher cadmium concentrations were characterized by closed and inactive reaction centers, dissipated energy outflux, and inhibited photosynthesis. Young fronds exposed to low and high cadmium concentrations were characterized by increased non-reducing reaction centers and thermal phase reduction, with activated dissipative mechanisms at high cadmium concentrations. Cadmium-induced changes in the ultrastructure of chloroplasts were visible after 6 h of exposure to lowest concentrations, with gradual degradation of the thylakoid system as the fronds aged. Younger fronds responded to cadmium more dynamically through molecular, physiological, and anatomical changes and tolerated a more reduced electron transport chain under given conditions than older fronds.

Functional characterization of the Pinellia ternata cytoplasmic class II small heat shock protein gene PtsHSP17.2 via promoter analysis and overexpression in tobacco

High temperature is one of the main abiotic factors limiting agricultural production, particularly for heat-sensitive plant species. Small heat-shock proteins contribute substantially to alleviating damage to plants caused by heat stress. In the present study, the heat shock protein gene PtsHSP17.2 from Pinellia ternata was functionally characterized through promoter analysis and its overexpression in tobacco. Respectively, relative expression using real-time RT-PCR and ex situ promoter activity assay indicated that PtsHSP17.2 is strongly inducible under heat stress, and in silico promoter analysis discovered multiple stress-related cis elements including heat shock element. When overexpressing PtsHSP17.2 in tobacco, the thermotolerance of transgenic plants was markedly enhanced. Furthermore, the transgenic tobacco plants exhibited less variation in chlorophyll content, relative electrolyte leakage, and malondialdehyde content under heat stress compared with wild-type (WT) plants. The activities of antioxidant enzymes and content of proline were significantly enhanced under heat stress in transgenic plants relative to WT plants. Transgenic plants also had enhanced water retention and increased antioxidative capacity. Further, the expression levels of genes encoding antioxidant enzymes were more highly induced by heat stress in transgenic lines than WT. These results enrich the current understanding of thermal adaptation of heat-sensitive plant species and encourage further genetic improvement.

Genome-Wide Association Study of Leaf Chlorophyll Content Using High-Density SNP Array in Peanuts (Arachis hypogaea L.)

The content of chlorophyll, a fundamental component required for photosynthesis in plants, has been widely studied across crop species. In this study, we aimed to evaluate the genetic diversity of 453 peanut accessions. We evaluated the evolutionary relationships using a genome-wide association study (GWAS) of leaf color data based on chlorophyll content analysis using the Axiom_Arachis array containing 58K single-nucleotide polymorphisms (SNPs). We identified seven SNPs as being significantly associated with leaf chlorophyll content on the chromosomes Aradu.A02, Aradu.A08, Araip.B02, Araip.B05, Araip.B06, and Araip.B08 in a GAPIT analysis. The SNP AX-176820297 on Araip.B05 was significantly linked with leaf chlorophyll content across the seasons. The Arahy.SDG4EV gene was detected to be in linkage disequilibrium (LD) with the significant SNPs, and its expression was significantly correlated with leaf chlorophyll content. The results of the current study provide useful and fundamental information with which to assess genetic variations in chlorophyll content and can be utilized for further genetic and genomic studies and breeding programs in peanuts.

Agronomic and sensory evaluation of lettuce in hydroponic system

Lettuce is the most important leafy vegetable in Brazil. Hydroponic lettuce cultivation has grown due to the viability of harvesting throughout the year. In this context, this study aimed to evaluate the agronomic characteristics, color, and preference of curly lettuce in the NFT hydroponic system. Six lineages (6601-1A, 6601-2L, 7016-6A, 7119-1B, 7223-1A, and 7224-4A) and two commercial cultivars (Brida and Vanda) of lettuce were used, in a completely randomized blocks design with four replications. Shoot length, root length, stem length, number of leaves, stem diameter, plant diameter, shoot fresh mass, root fresh mass, chlorophyll content, instrumental color, and sensory characteristics were evaluated. As for agronomic evaluation, the bolting of 6601-2L lettuce was relevant in different attributes. The Vanda lettuce and the lineage 7016-6A presented best performances for shoot fresh mass (399.44 and 378.63 g, respectively), while the lineages 7119-1B and 6601-2L present the worst performance (279.50 and 273.13 g, respectively). There was variation in chlorophyll content and luminosity, however, the evaluators did not notice differences between lettuces for brightness or green color, as well as for crunchy texture. Lettuces 6601-2L, 7224-4A, 6601-1A, Brida, 7223-1A, and 7119-1B were preferred. The variation among plants may be due to different situations, such as harvesting times and bolting, and a direct relationship between agronomic properties and preference among lettuces has not been established yet.

Effects of the seasonal variation in chlorophyll concentration on sea surface temperature in the global ocean

Effects of the seasonal variation in chlorophyll concentration on sea surface temperature in the global ocean

Pretreating poplar cuttings with low nitrogen ameliorates salt stress responses by increasing stored carbohydrates and priming stress signaling pathways

Soil salinity is a widespread stress in semi-arid forests worldwide, but how to manage nitrogen (N) nutrition to improve plant saline tolerance remains unclear. Here, the cuttings of a widely distributed poplar from central Asia, Populus russikki Jabl., were exposed to either normal or low nitrogen (LN) concentrations for two weeks in semi-controlled greenhouse, and then they were added with moderate salt solution or not for another two weeks to evaluate their physiological, biochemical, metabolites and transcriptomic profile changes. LN-pretreating alleviated the toxicity caused by the subsequent salt stress in the poplar plants, demonstrated by a significant reduction in the influx of Na+ and Cl- and improvement of the K+/Na+ ratio. The other salt-stressed traits were also ameliarated, indicated by the variations of chlorophyll content, PSII photochemical activity and lipid peroxidation. Stress alleviation resulted from two different processes. First, LN pretreatment caused a significant increase of non-structural carbohydrates (NSC), allowed for an increased production of osmolytes and a higher potential fueling ion transport under subsequent salt condition, along with increased transcript levels of the cation/H+ ATPase. Second, LN pretreatment enhanced the transcript levels of stress signaling components and phytohormones pathway as well as antioxidant enzyme activities. The results indicate that early restrictions of N supply could enhance posterior survival under saline stress in poplar plants, which is important for plantation programs and restoration activities in semi-arid areas.

İNSANSIZ HAVA ARACI TEKNOLOJİSİ KULLANILARAK AYÇİÇEĞİ (HELİANTHUS ANNUUS) BİTKİSİNİN KLOROFİL İÇERİKLERİNİN TAHMİN EDİLEBİLİRLİĞİNİN ARAŞTIRILMASI

High-resolution images obtained with multispectral cameras mounted on unmanned aerial vehicles (UAVs) offer significant potential for agricultural monitoring activities. Chlorophyll content is one of the important parameters in monitoring the growing periods of sunflower plants. In this study, the potential of UAV technology to monitor spatial and temporal changes of sunflower (Helianthus annuus) chlorophyll content was tested. Chlorophyll and vegetation indices calculated using multispectral images taken from the UAV were compared with field chlorophyll measurements using a Spad meter. Significant (p&lt;0.01) high correlations were obtained between the calculated indices and chlorophyll values. The results revealed that the chlorophyll content of sunflower plants can reliably be modeled at p&lt;0.001 significance level using a multivariate linear regression model. The model obtained could successfully explain 28% 𝑅𝐴𝑑𝑗 2 = 0.28 of the variation in chlorophyll content of sunflowers. The results showed that the models developed between Spad measurement and UAVimages were successful in explaining the variation at a high level of importance. However, although statistically significant, the indices produced in the study could only explained 28% of the variation in chlorophyll content of sunflower plants. Keywords: Sunflower, UAV, Spad meter, Estimation, Vegetation indices

Band selection algorithms for foliar trait retrieval using AVIRIS-NG: a comparison of feature based attribute evaluators

Interband information overlapping enhances redundancy in hyperspectral data. This makes identification of application-specific optimal bands essential for obtaining accurate information about foliar traits. The current study investigated the performance of three novel Band Selection (BS) algorithms (i.e. the Chi-squared-statistics based attribute evaluator (CSS), the Recursive elimination of features-based attribute evaluator (REF) and the Correlation-based attribute subset evaluator (CBS)) in identifying the spectral bands of Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) from visible and Near Infrared (NIR) regions that are sensitive to variation in Chlorophyll Content (CC). Identified bands were employed to formulate Hyperspectral Indices (HIs) by incorporating combinations of Blue, Green, Red, and NIR regions. CC models were built by establishing a linear fit between ground CC and HIs. For all the three BS algorithms, optimum bands varied for visible and NIR regions. REF-HI (NIR,R), REF-HI(NIR,R + G), CSS-HI(NIR,R) and CSS-HI(NIR,R + G) had the best correlation with CC. HI(NIR,R) is identified as the best HI and REF the best BS algorithm for retrieving CC.

Larval connectivity and water quality explain spatial distribution of crown-of-thorns starfish outbreaks across the Great Barrier Reef.

Outbreaks of the coral eating crown-of-thorns starfish (COTS; Acanthasts cf. solaris) occur in cyclical waves along the Great Barrier Reef (GBR), contributing significantly to the decline in hard coral cover over the past 30 years. One main difficulty faced by scientists and managers alike, is understanding the relative importance of contributing factors to COTS outbreaks such as increased nutrients and water quality, larval connectivity, fishing pressure, and abiotic conditions. We analysed COTS abundances from the most recent outbreak (2010-2018) using both boosted regression trees and generalised additive models to identify key predictors of COTS outbreaks. We used this approach to predict the suitability of each reef on the GBR for COTS outbreaks at three different levels: (1) reefs with COTS present intermittently (Presence); (2) reefs with COTS widespread and present in most samples and (Prevalence) (3) reefs experiencing outbreak levels of COTS (Outbreak). We also compared the utility of two auto-covariates accounting for spatial autocorrelation among observations, built using weighted inverse distance and weighted larval connectivity to reefs supporting COTS populations, respectively. Boosted regression trees (BRT) and generalised additive mixed models (GAMM) were combined in an ensemble model to reduce the effect of model uncertainty on predictions of COTS presence, prevalence and outbreaks. Our results from best performing models indicate that temperature (Degree Heating Week exposure: relative importance=13.1%) and flood plume exposure (13.0%) are the best predictors of COTS presence, variability in chlorophyll concentration (12.6%) and flood plume exposure (8.2%) best predicted COTS prevalence and larval connectivity potential (22.7%) and minimum sea surface temperature (8.0%) are the best predictors of COTS outbreaks. Whether the reef was open or closed to fishing, however, had no significant effect on either COTS presence, prevalence or outbreaks in BRT results (<0.5%). We identified major hotspots of COTS activity primarily on the mid shelf central GBR and on the southern Swains reefs. This study provides the first empirical comparison of the major hypotheses of COTS outbreaks and the first validated predictions of COTS outbreak potential at the GBR scale incorporating connectivity, nutrients, biophysical and spatial variables, providing a useful aid to management of this pest species on the GBR.

Strontium Uptake and Effect in Lettuce and Radish Cultivated Under Hydroponic Conditions.

The accumulation of strontium (Sr) in lettuce and radish under 0 (control), 0.5, 1, 2.5, 5, and 10mM Sr treatments in hydroponic solution at 16, 23 and 30days and the effects of Sr stress on six nutrient elements in plants were investigated. The results showed that Sr concentrations in plant aerial and underground parts increased in low-Sr treatments (0.5, 1 and 2.5mM) and fluctuated in high-Sr treatments (5 and 10mM) throughout the three sampling periods. Sr concentrations were higher in roots than in leaves, reaching 108.8 ± 14.7 and 134.1 ± 1.2mg/g in lettuce and radish roots, respectively, after 10mM Sr treatment. Translocation factor (TF) values (ratio of the Sr concentrations in aerial parts to that in roots) were inversely related to the Sr content in the hydroponic solution, and reached 1.45 ± 0.17 to 0.15 ± 0.03 and 1.06 ± 0.20 to 0.12 ± 0.004 for lettuce and radish. The variation in chlorophyll content was consistent with that in plant biomass.