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1.
Leaf area (LA) is an important parameter related to plant growth and physiology. An allometric model was developed to estimate the LA of endangered medicinal plant Valeriana jatamansi using linear measurements such as leaf length (L) and width (W). LA and other leaf dimensions were measured using a laser leaf area meter. Leaves from seven accessions of valeriana were collected from the experimental site during 2015. Different regression models were developed between LA and other leaf components, viz. L, W, etc. The linear model having LW as an independent variable (y = 0.487 + 0.644 LW) provided the best estimation [coefficients of determination (R2) = 0.974, root mean square error (RMSE) = 2.222, coefficient of variation (CV) = 4.529]. Validation of the selected model showed a higher correlation between the actual leaf area (ALA) and the predicted leaf area (PLA) [R2 = 0.956, RMSE = 2.310, CV = 5.319, predicted residual error sum of squares (PRESS) = 1067.352].  相似文献   

2.
Leaf Area (LA) is a key index of plant productivity and growth. A multiple linear regression technique is commonly applied to estimate LA as a non-destructive and quick method, but this technique is limited under the realistic situation. Thus, it is indispensable to elaborate new models for estimation. In this research, the performance of the Adaptive Neural-Based Fuzzy Inference System (ANFIS) in predicting the LA of 61 plant species (C) was investigated. Four parameters including leaf length (L), leaf width (W), C, and specific coefficient (K) for each plant were selected as input data to the ANFIS model and the LA as the output. Seven different ANFIS models including different combinations of input data were constructed to reveal the sensitivity analysis of the models. The normalized root mean square error (NRMSE), mean residual error (MRE), and linear regression were applied between observed LA and estimated LA by the models. The results indicated that ANFIS4-K2min which employed all input data was the most accurate (NRMSE = 0.046 and R2 = 0.997) and ANFIS1 which employed only the K input was the worst (NRMSE = 0.452 and R2 = 0.778). In ranking, ANFIS4-K2ave, ANFIS4-K1min, ANFIS4-K1ave, ANFIS3, and ANFIS2 ranked second, third, fourth, fifth, and sixth, respectively. The sensitivity analysis indicated that the predicted LA is more sensitive to the K, followed by L, W, and C. The results displayed that estimations are slightly overestimated. This study demonstrated that the ANFIS model could be accurate and faster alternative to the available laborious and time-consuming methods for LA prediction.  相似文献   

3.
Leaf area index (LAI) has traditionally been difficult to estimate accurately at the landscape scale, especially in heterogeneous vegetation with a range in LAI, but remains an important parameter for many ecological models. Several different methods have recently been proposed to estimate LAI using aerial light detection and ranging (LIDAR), but few systematic approaches have been attempted to assess the performance of these methods using a large, independent dataset with a wide range of LAI in a heterogeneous, mixed forest. In this study, four modeling approaches to estimate LAI using aerial discrete-return LIDAR have been compared to 98 separate hemispherical photograph LAI estimates from a heterogeneous mixed forest with a wide range of LAI. Among the four approaches tested, the model based on the Beer–Lambert law with a single parameter (k: extinction coefficient) exhibited highest accuracy (r2 = 0.665) compared with the other models based on allometric relationships. It is shown that the theoretical k value (=0.5) assuming a spherical leaf angle distribution and the zenith angle of vertical beams (=0°) may be adequate to estimate effective LAI of vegetation using LIDAR data. This model was then applied to six 30 m × 30 m plots at differing spatial extents to investigate the relationship between plot size and model accuracy, observing that model accuracy increased with increasing spatial extent, with a maximum r2 of 0.78 at an area of 900 m2. Findings of the present study can provide useful information for selection and application of LIDAR derived LAI models at landscape or other spatial scales of ecological importance.  相似文献   

4.
For understanding the effects of soil salinity and nitrogen (N) fertilizer on the emergence rate, yield, and nitrogen-use efficiency (NUE) of sunflowers, complete block design studies were conducted in Hetao Irrigation District, China. Four levels of soil salinity (electrical conductivity [ECe] = 2.44–29.23 dS m?1) and three levels of N fertilization (90–180 kg ha?1) were applied to thirty-six microplots. Soil salinity significantly affected sunflower growth (P < 0.05). High salinity (ECe = 9.03–18.06 dS m?1) reduced emergence rate by 24.5 percent, seed yield by 31.0 percent, hundred-kernel weight by 15.2 percent, and biological yield by 27.4 percent, but it increased the harvest index by 0.9 percent relative to low salinity (ECe = 2.44–4.44 dS m?1). Application of N fertilizer alleviated some of the adverse effects of salinity, especially in highly saline soils. We suggest that moderate (135 kg ha?1) and high (180 kg ha?1) levels of N fertilization could provide the maximum benefit in low- to moderate-salinity and high- or severe-salinity fields, respectively, in Hetao Irrigation District and similar sunflower-growing areas.  相似文献   

5.
Abstract

This study was conducted at two sites in Mississippi to determine whether petiole and leaf NO‐ 3 monitoring could be used as a management tool in making fertilizer N recommendations for sunflower (Hellanthus annuus L.). Petiole and leaf samples were taken at the four leaf stage at both sites, and later at two week intervals at Brooksville. Petiole and leaf NO‐ 3 at the four leaf stage was significantly influenced by rate of N application at both sites. The level of petiole and leaf NO‐ 3 was highly correlated with rate of N application as well as with seed yield. The concentration of NO‐ 3 in petioles and leaves was greatest at the four leaf stage and showed quadratic declines as the season progressed. Petiole and leaf NO‐ 3 showed the highest correlations with rate of N application and seed yield at the four leaf stage than at any other sampling time at Brooksville, indicating that this was the “best” period for taking petiole and leaf samples. However, analysis of petioles and leaves at the four leaf growth stage for NO‐ 3 may have limited potential of becoming a useful tool in making N fertilizer recommendations for sunflower. This is due to the sensitivity of both petiole and leaf NO‐ 3 to time of sampling and locational differences, as well as lack of information on response of sunflower to N applied after this stage of growth.  相似文献   

6.
Monitoring exchangeable sodium percentage (ESP) and sodium adsorption ratio (SAR) variability in soils is both time-consuming and expensive. However, in order to estimate the amounts of amendments and land management, it is essential to know ESP and SAR variations and values in sodic or saline and sodic soils. Thus, presenting a method which uses easily obtained indices to estimate ESP and SAR indirectly is more optimal and economical. Input data of the current research were 189 soil samples collected based on a regular networking approach from Miankangi region, Sistan plain, Iran. Then, their physicochemical properties were measured. Results showed that SAR = 3.8 × ln(EC) + 22.83 × ln(pH) – 44.37, (R2 = 0.63), and ESP = 3.98×ln(EC) + 36.88(pH) – 56.98 (R2 = 0.78) are the best regression models for estimating SAR and ESP, respectively. Moreover, multilayer perceptron (MLP), which explains 95–97% of parameters of soil sodicity using EC and pH as inputs, was the best neural network model. Therefore, MLP could be applied for ESP and SAR evaluation with high accuracy in the Miankangi region.  相似文献   

7.
Using pedotransfer functions (PTF) is a useful way for field capacity (FC) and permanent wilting point (PWP) prediction. The aim of this study was to model PTF to estimate FC and PWP using regression tree (RT) and stepwise multiple linear regressions (SMLR). For this purpose, 165 and 45 soil samples from UNSODA and HYPRES datasets were used for development and validation of new PTFs, respectively. %Clay, geometric mean diameter (dg), and bulk density (BD) were selected as predictor variables due to the highest correlation and lowest multicollinearity. The results showed that clay percentage with W* = 0.89 and dg with W* = ?0.57 were the most effective variables to predict PWP and FC, respectively. The RT method had a better performance (R2 = 0.80, ME = ?0.002 cm3cm?3, RMSE = 0.05 cm3cm?3 for FC and R2 = 0.85, ME = 0.003 cm3cm?3, RMSE = 0.03 cm3 cm?3 for PWP) than SMLR in estimation of FC and PWP.  相似文献   

8.
Terminal drought stress (drought at reproductive growth stage) has been considered a severe environmental threat under changing climatic scenarios and undoubtedly inhibits sunflower production. A field study was conducted to explore the potential role of foliar applied boron (B) (0, 15, 30, 45 mg L?1) at late growth periods of sunflower in alleviating the adversities of terminal drought stress (75, 64, 53 mm DI) grown from inflorescence emergence to maturity stages. The plant water relations such as leaf relative water content (RWC), water potential (Ψw), osmotic potential (Ψs), and turgor pressure (Ψp) were increased significantly with B foliar sprays while exposed to terminal drought stress. Foliar B application considerably improved the nitrogen and B concentrations in leaf and seed tissues, and also chlorophyll a and b pigments under terminal drought stress conditions. Drought-induced proline accumulation prevented the damages caused by drought stress, nevertheless, B foliar spray increased its contents. Compared to well-watered conditions, terminal drought stress substantially declined the growth performance in terms of reduced leaf area index (LAI), crop growth rate (CGR), net assimilation rate (NAR), and total dry matter (TDM) production; however, foliar B supply (30 mg L?1) might be helpful for improving drought tolerance in sunflower with reduced growth losses.  相似文献   

9.
This research was carried out to determine the effects of potassium [0, 40, 80, 120 kg potassium oxide (K2O) ha?1] and magnesium (0, 20, 40, 60 kg magnesium oxide (MgO) ha?1) applied into soil separately and together on the grain yield and yield components of sunflower for oil grown in two farmer fields in the semi-arid Central Anatolia in 2009 and 2010. The experiments were set as factorial experiment design in randomized blocks and 4 replicates. Potassium and Mg-fertilizers were used in the single time into base in the sowing. According to the results, K application in the increasing doses increased yield components more than that of Mg. Together giving of the K and Mg in certain combinations took the yield components to maximum levels. The highest grain yields were obtained by the K40Mg40 in the first year (7313 kg ha?1) and by the Mg60 in the second year (6510 kg ha?1).  相似文献   

10.
This study examined zinc (Zn) fixation pattern and kinetics in three semiarid alkaline soils of the Southern High Plains, USA. Soil chemical data obtained from Zn-extraction experiments conducted at different depths were fitted to various kinetic models to examine Zn fixation patterns. Within the experimental period of 90 days, approximately 57% of the total plant-available Zn fixed occurred in the first 14 days when averaged across all soils and depths. Zinc fixation over the experimental period (90 days) was better described by the power function (pfxn) model (R2 = 0.87–0.92, standard error [SE] = 0.130–0.154), but poorly described by the zero-, first- and second-order models (R2 = 0.55–0.76, SE = 0.038–0.267). Average reaction rate constant (from the pfxn model) was higher in the subsurface soils (0.323), suggesting a more rapid Zn fixation, compared to the surface soils (0.293). Zinc fixation within the first 35 days was also more rapid and better described by both the second-order (R2 = 0.91, SE = 0.018) and pfxn (R2 = 0.92, SE = 0.119) models. Findings are applicable to field settings and kinetic parameters obtained will help to advance Zn studies and management in these semiarid soils.  相似文献   

11.
Abstract

To elucidate the effects of broadcast urea on ammonia (NH3) exchange between the atmosphere and rice, we investigated the NH3 exchange flux between rice leaf blades and the atmosphere, xylem sap ammonium (NH+ 4) concentration, leaf apoplastic NH+ 4 concentration and pH, and determined the stomatal NH3 compensation point. Paddy rice (Oryza sativa L. cv. Nipponbare) cultivation using experimental pots was conducted in the open air. Three treatments, no nitrogen (NN), standard nitrogen (SN) and high nitrogen (HN), were prepared for two supplemental fertilizations. Urea with 0, 30 and 60 kg N ha?1 for the NN, SN and HN treatments, respectively, was broadcast at panicle initiation, and urea with 0, 20 and 40 kg N ha?1 for the NN, SN and HN treatments, respectively, was broadcast at heading. The NH3 exchange fluxes between the rice leaf blades and the atmosphere (SN treatment) measured using a dynamic chamber technique showed net deposition in general; however, net emission from the old leaves occurred 1 day after the application at heading. In contrast, the xylem sap NH+ 4 concentrations increased markedly 1 day after both applications, which suggests direct transportation of NH+ 4 from the rice roots to the above-ground parts. The applications resulted in no obvious increase in the leaf apoplastic NH+ 4 concentrations. The relationship between the NH+ 4 concentration in the xylem sap and that in the leaf apoplast was uncertain, although the NH+ 4 in the xylem sap came from the roots and the NH+ 4 in the apoplast might be affected by the stomatal deposition of NH3. The stomatal NH3 compensation point of rice was estimated to be 0.1–4.1 nmol mol?1 air (20°C). The direction and intensity of the exchange flux through the stomata, interpreted on the basis of the temperature-corrected NH3 compensation point, agreed with the observed exchange flux between the rice leaf blades and the atmosphere.  相似文献   

12.
利用普通数码相机估测松林叶面积指数与标准误   总被引：2，自引：0，他引：2  
叶面积指数(LAI)与叶面积指数标准误(SEL)是植被的重要结构变量, 可为森林经营管理、开展病虫害防治检疫工作提供数据参考。针对条件复杂区域LAI与SEL测定仪法应用的限制性, 提出利用数码相机拍摄松林林冠图像, 经特征指数2G B计算图像叶覆盖度(用Cover表示)与叶覆盖度标准差(用Cover SD表示)两个指标, 构建LAI-Cover、SEL-Cover SD关系模型, 实现松林LAI与SEL的估测。利用福建省13个县(市)65组数据对该方法进行试验, 结果表明: Cover与LAI、Cover SD与SEL均呈极显著正相关关系, 可以用 LAI 3.095 5Cover=0.192 6e3.0955cover 准确估测松林 LAI, 用 SEL = 1.105 9Cover SD ? 0.067 4 估测 SEL,, 两模型的R2分别为0.613 5、0.493 5, 估测精度达0.894 6、0.798 5。由此可见, 利用普通数码相机估测松林LAI与SEL具有较高的可行性与准确性, 可将该方法推广应用。  相似文献   

13.
Abstract

We studied the effect of crop residues with various C:N ratios on N2O emissions from soil. We set up five experimental plots with four types of crop residues, onion leaf (OL), soybean stem and leaf (SSL), rice straw (RS) and wheat straw (WS), and no residue (NR) on Gray Lowland soil in Mikasa, Hokkaido, Japan. The C:N ratios of these crop residues were 11.6, 14.5, 62.3, and 110, respectively. Based on the results of a questionnaire survey of farmer practices, we determined appropriate application rates: 108, 168, 110, 141 and 0 g C m?2 and 9.3, 11.6, 1.76, 1.28 and 0 g N m?2, respectively. We measured N2O, CO2 and NO fluxes using a closed chamber method. At the same time, we measured soil temperature at a depth of 5 cm, water-filled pore space (WFPS), and the concentrations of soil NH+ 4-N, NO? 3-N and water-soluble organic carbon (WSOC). Significant peaks of N2O and CO2 emissions came from OL and SSL just after application, but there were no emissions from RS, WS or NR. There was a significant relationship between N2O and CO2 emissions in each treatment except WS, and correlations between CO2 flux and temperature in RS, soil NH+ 4-N and N2O flux in SSL and NR, soil NH+ 4-N and CO2 flux in SSL, and WSOC and CO2 flux in WS. The ratio of N2O-N/NO-N increased to approximately 100 in OL and SSL as N2O emissions increased. Cumulative N2O and CO2 emissions increased as the C:N ratio decreased, but not significantly. The ratio of N2O emission to applied N ranged from ?0.43% to 0.86%, and was significantly correlated with C:N ratio (y = ?0.59 ln [x] + 2.30, r 2 = 0.99, P < 0.01). The ratio of CO2 emissions to applied C ranged from ?5.8% to 45% and was also correlated with C:N ratio, but not significantly (r 2 = 0.78, P = 0.11).  相似文献   

14.
Accurate and reliable predictive models are necessary to estimate above and below ground biomass of plant and biomass carbon stock non-destructively. Different growth models namely viz, Linear, Allometric, Logistic, Gompertz, Richard’s, Negative exponential, Monomolecular, Mitcherlich and Weibull were fitted to the relationship between dry biomass of litchi tree components with collar diameter. Richard’s model outperformed the others and fulfilled the validation criterions to the best possible extent with lowest Akaike information criteria (AICc) of 90.47 and root mean square error (RMSE) of 1.79. The value of adjusted R2 ranged from 0.947 to 0.971 for the Richard’s models fitted on various biomass components and the ‘t’ values for all the components was found non-significant (p > 0.05) indicating the validation of the model. The estimated total dry biomass varied from 0.50 Mg ha?1 in two year to 5.71 Mg ha?1 in 10 year old litchi orchards. The estimated stored biomass carbon stock in litchi orchards (branches, bole and roots) varied from 0.10 Mg ha?1 in two year to 1.85 Mg ha?1 in 10 year orchards with CO2 sequestration potential from 0.19–4.63 Mg ha?1.  相似文献   

15.
ABSTRACT

Soil hydraulic parameters like moisture content at field capacity and permanent wilting point constitute significant input parameters of various biophysical models and agricultural practices (irrigation timing and amount of irrigation to be applied). In this study, the performance of three different methods (Multiple linear regression – MLR, Artificial Neural Network – ANN and Adaptive Neuro-Fuzzy Inference System – ANFIS) with different input parameters in prediction of field capacity and permanent wilting point from easily obtained soil characteristics were compared. Correlation analysis indicated that clay content, sand content, cation exchange capacity, CaCO3, and organic matter had significant correlations with FC and PWP (p < .01). Validation results revealed that the ANN model with the greatest R2 and the lowest MAE and RMSE value exhibited better performance for prediction of FC and PWP than the MLR and ANFIS models. ANN model had R2 = 0.83, MAE = 2.36% and RMSE = 3.30% for FC and R2 = 0.81, MAE = 2.15%, RMSE = 2.89% for PWP in training dataset; R2 = 0.80, MAE = 2.27%, RMSE = 3.12% for FC and R2 = 0.83, MAE = 1.84%, RMSE = 2.40% for PWP in testing dataset. Also, Bayesian Regularization (BR) algorithm exhibited better performance for both FC and PWP than the other training algorithms.  相似文献   

16.
Maize crop is grown mostly in tropical/subtropical environments where drought adversely affects its production. A field experiment was conducted on sandy loam soil for four years (1999 – 2002) to study the effect of wheat straw mulch (0 and 6 t ha?1) and planting methods (flat and channel) on maize sown on different dates. Maximum soil temperature without mulch ranged from 32.2 – 44.4°C in channel and 31.6 – 46.4°C in flat planting method. Mulching, however, lowered soil temperature by 0.8 – 7.0°C in channel and 0 – 9.8°C in flat planting. Mulching, on an average, improved leaf area index by 0.42, plant height by 14 cm, grain yield by 0.24 t ha?1 and biomass by 1.57 t ha?1, respectively. Mulching improved grain yield only in flat sowing. Interaction between sowing date and planting method was significant. Seasonal variation in biomass were significantly correlated (p = 0.05) with mean air temperature during 0 – 45 days after planting (DAP) (r = ?0.95), pan evaporation during 0 – 15 DAP (r = 0.79) and negative correlation with rainfall in entire cropping season (r = ?0.89), whereas biomass increase with mulch in different cropping seasons had negative relation (r = ?0.74) with amount of rain during 0 – 15 DAP.  相似文献   

17.
Using easily measurable soil properties could save time and cost for field capacity (FC) prediction. The objective of this study was to compare Mamdani fuzzy inference system (MFIS) and regression tree (RT) for FC predicting using such properties. One hundred and sixty-five soil samples from Unsaturated Soil hydraulic database data-set and 45 from Hydraulic Properties of European Soils data-set were used for the development and validation of MFIS and RT, respectively. Fuzzy rules and tree diagram based on the relationships between these predictor variables and the response variable FC were defined and 48 rules were written. Results showed a positive linear relevancy in terms of standardized independent variable weight, W*, between clay content and FC and negative linear relevancy between geometric mean particular size diameter (dg) and FC. Among predictor variables, dg (W* = 0.81) and bulk density (BD) (W* = 0.49) had the highest and lowest influence on FC, respectively. A tree diagram is presented for the prediction of FC using clay content, dg, and BD. Overall, based on statistical parameters, RT method (R2 = 0.78, geometric mean error (GME) = 1.02, mean error (ME) = 0.01 cm3 cm?3, and root mean square error (RMSE) = 0.04 cm3 cm?3) showed a higher performance than MFIS method (R2 = 0.72, GME = 1.16, ME = 0.08 cm3 cm?3, and RMSE = 0.06 cm3 cm?3) to predict FC.  相似文献   

18.
Our understanding of leaf litter carbon (C) and nitrogen (N) cycling and its effects on N management of deciduous permanent crops is limited. In a 30-day laboratory incubation, we compared soil respiration and changes in mineral N [ammonium (NH4+-N) + nitrate (NO3–-N)], microbial biomass nitrogen (MBN), total organic carbon (TOC) and total non-extractable organic nitrogen (TON) between a control soil at 15N natural abundance (δ15N = 1.08‰) without leaf litter and a treatment with the same soil, but with almond (Prunus dulcis (Mill.) D.A. Webb) leaf litter that was also enriched in 15N (δ15N = 213‰). Furthermore, a two-end member isotope mixing model was used to identify the source of N in mineral N, MBN and TON pools as either soil or leaf litter. Over 30 d, control and treatment TOC pools decreased while the TON pool increased for the treatment and decreased for the control. Greater soil respiration and significantly lower (p < 0.05) mineral N from 3 to 15 d and significantly greater MBN from 10 to 30 d were observed for the treatment compared to the control. After 30 d, soil-sourced mineral N was significantly greater for the treatment compared to the control. Combined mineral N and MBN pools derived from leaf litter followed a positive linear trend (R2 = 0.75) at a rate of 1.39 μg N g?1 soil day?1. These results suggest early-stage decomposition of leaf litter leads to N immobilization followed by greater N mineralization during later stages of decomposition. Direct observations of leaf litter C and N cycling assists with quantifying soil N retention and availability in orchard N budgets.  相似文献   

19.
基于连续小波变换和随机森林的芦苇叶片汞含量反演   总被引：3，自引：0，他引：3  
植物重金属污染是当今世界面临的重大生态环境问题之一,高光谱技术为快速、大面积监测植被重金属含量提供了可能性。本研究以重金属汞(Hg)和湿地植物芦苇为研究对象,采用连续小波变换(CWT)和随机森林(RF)算法相结合的方法建立芦苇叶片总汞含量反演模型,以期寻求一种较为精准的植物汞污染反演模型,未来可通过高光谱技术建立模型来无损、快速估测湿地植物重金属汞污染情况,为湿地生态系统的监测提供方法支持。结果表明:芦苇叶片总汞含量敏感波段主要分布在可见光波段419~522 nm、664~695 nm和724~876nm以及近红外波段1 450~1 558 nm和1 972~2 500 nm;经CWT变换后,小波系数与叶片总汞含量的相关系数绝对值提高0.04~0.18,所构建的预测反演模型拟合效果R~2提高0.107~0.177,模型精度RMSE提高0.008~0.013,其中利用经小波变换的去包络线光谱(CR-CWT)数据建立的RF模型对芦苇叶片总汞含量的反演精度和拟合效果最优(R~2=0.713,RMSE=0.127);同时在土壤总汞含量约为20 mg?kg~(-1)时,采用CR-CWT数据构建RF模型的方法来反演芦苇叶片总汞含量更为准确和可靠(R~2=0.825,RMSE=0.051)。因此,利用RF算法进行植被重金属含量的反演具有一定的现实可行性,而结合CWT后所构建的反演模型对指导植被重金属含量监测更具参考价值,应用前景广阔。  相似文献   

20.
《Journal of plant nutrition》2013,36(10-11):2243-2252
Abstract

A research was carried out to evaluate the leaves' ability to utilize Fe supplied as a complex with water‐extractable humic substances (WEHS) and the long‐distance transport of 59Fe applied to sections of fully expanded leaves of intact sunflower (Helianthus annuus L.) plants. Plants were grown in a nutrient solution containing 10 µM Fe(III)‐EDDHA (Fe‐sufficient plants), with the addition of 10 mM NaHCO3 to induce iron chlorosis (Fe‐deficient plants). Fe(III)‐WEHS could be reduced by sunflower leaf discs at levels comparable to those observed using Fe(III)‐EDTA, regardless of the Fe status. On the other hand, 59Fe uptake rate by leaf discs of green and chlorotic plants was significantly lower in Fe‐WEHS‐treated plants, possibly suggesting the effect of light on photochemical reduction of Fe‐EDTA. In the experiments with intact plants, 59Fe‐labeled Fe‐WEHS or Fe‐EDTA were applied onto a section of fully expanded leaves. Irrespective of Fe nutritional status, 59Fe uptake was significantly higher when the treatment was carried out with Fe‐EDTA. A significant difference was found in the amount of 59Fe translocated from treated leaf area between green and chlorotic plants. However, irrespective of the Fe nutritional status, no significant difference was observed in the absolute amount of 59Fe translocated to other plant parts when the micronutrient was supplied either as Fe‐EDTA or Fe‐WEHS. Results show that the utilization of Fe complexed to WEHS by sunflower leaves involves an Fe(III) reduction step in the apoplast prior to its uptake by the symplast of leaf cells and that Fe taken up from the Fe‐WEHS complexes can be translocated from fully expanded leaves towards the roots and other parts of the shoot.  相似文献   

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