共查询到20条相似文献，搜索用时 15 毫秒
1.
ABSTRACT Although Asian soybean rust occurs in a broad range of environmental conditions, the most explosive and severe epidemics have been reported in seasons with warm temperature and abundant moisture. Associations between weather and epidemics have been reported previously, but attempts to identify the major factors and model these relationships with field data have been limited to specific locations. Using data from 2002-03 to 2004-05 from 34 field experiments at 21 locations in Brazil that represented all major soybean production areas, we attempted to identify weather variables using a 1-month time window following disease detection to develop simple models to predict final disease severity. Four linear models were identified, and these models explained 85 to 93% of variation in disease severity. Temperature variables had lower correlation with disease severity compared with rainfall, and had minimal predictive value for final disease severity. A curvilinear relationship was observed between 1 month of accumulated rainfall and final disease severity, and a quadratic response model using this variable had the lowest prediction error. Linear response models using only rainfall or number of rainy days in the 1-month period tended to overestimate disease for severity <30%. The study highlights the importance of rainfall in influencing soybean rust epidemics in Brazil, as well as its potential use to provide quantitative risk assessments and seasonal forecasts for soybean rust, especially for regions where temperature is not a limiting factor for disease development. 相似文献
2.
P. Vijaya Kumar 《European journal of plant pathology / European Foundation for Plant Pathology》2014,140(3):429-440
Weather based prediction models for leaf rust were developed using disease severity and weather data recorded at four locations viz. Ludhiana, Kanpur, Faizabad and Sabour of the All India Wheat and Barley Improvement Project. Weeks 7–9 of the crop growing season at Ludhiana, Faizabad and Sabour and weeks 10–12 at Kanpur were identified as critical periods for relating weather variables to disease. Highly significant correlation coefficients were found between disease severity and a greater number of weather variables in these critical 3-week periods than at other times. The correlation coefficients were greatest for the Humid Thermal Ratio (HTR), Maximum Temperature (MXT) and Special Humid Thermal Ratio (SHTR), and these three weather variables were selected as predictor variables. Linear regressions with these predictor variables (individually) during the critical periods, and a multiple regression with MXT and relative humidity (RH), serve as four disease prediction models, with sufficient lead-time to take control measures. Validation of these prediction models with independent disease severity data showed that the regression equation with MXT (Model-1) was the best among the prediction models, with four out of six simulations matching observed disease severity classes and also having lowest residual sum of squares (SSE) value of 2727. Models 4 (multiple regression), 2 (HTR) and 3 (SHTR) with SSE values of 2881, 3092 and 3732, respectively are in order of decreasing accuracy of prediction. The model using MXT can be used to predict the disease severity in the Indo-Gangetic Plains and provide the basis for efficient disease control. 相似文献
3.
Assessing mango anthracnose using a new three-dimensional image-analysis technique to quantify lesions on fruit 总被引：1，自引：0，他引：1
G. Corkidi K. A. Balderas-Ruíz B. Taboada L. Serrano-Carreón E. Galindo 《Plant pathology》2006,55(2):250-257
An accurate image-analysis method was developed to assess quantitatively the spot-like lesions on fruits resulting from pathogen attack. The technique was applied to evaluation of the development and severity of anthracnose of mango fruit, caused by the fungus Colletotrichum gloeosporioides . In this method, a stepper motor rotates the mango fruit along its longitudinal axis while acquiring a sequence of 360 images of its total surface (one image for each degree). This set of images is used to create a pseudocylindrical 'equal-area' projection of the fruit in a two-dimensional map containing complete morphometrical and photometrical information of its surface. The lesion area can easily be evaluated from this map with image-analysis procedures. Quantitative data (percentage of area affected) can be used to establish an assessment scale for the disease based on lesion spots measured, as well as for detailed laboratory studies of mango anthracnose development. The average error of the method is −0·1%, standard deviation 0·44 ( r 2 = 0·99), and it may be adapted for use with most commercial image analysers and for other diseases with spot-like symptoms. 相似文献
4.
W. P. ROBERTS 《EPPO Bulletin》1991,21(3):623-631
Australia is free from fireblight, a serious apple and pear disease. Published models and weather data from all major apple and pear-producing areas of Australia were used to predict the possible severity of the disease and losses in production should the disease enter and establish in Australia. The results suggest that fireblight could be severe in most areas in most seasons. In the worst case, with every area affected, this could result in up to 20% losses in apple production and up to 50% losses in pear production. 相似文献
5.
The epidemiology of the Neotropical rust caused by Puccinia psidii in the Indian Myrtaceae Syzygium jambos (rose apple) was investigated in central Brazil. Disease severities recorded during a 12-month period were fitted by a Fourier curve with three cyclic components or harmonics. The first, second and third harmonics accounted for 49·6, 25·9, and 1·5% of total disease measured, respectively. A highly significant linear correlation was observed between the first harmonic and the accumulated number of days having at least 6 h wetness, or a minimum of 90% relative humidity, combined with temperatures that ranged from 18 to 20°C. No significant correlation was observed between the second and third harmonics and the weather variables evaluated. Rose apple trees showed a flush of growth with new susceptible host tissue during the evaluation period, with two major outbreaks of rust of variable intensity. Host growth was fitted by a Fourier curve with two significant harmonics. The first and second harmonics accounted for 37·5 and 22·1% of total host growth measured, respectively. A highly significant negative linear correlation was observed between the first harmonic and daily maximum and minimum temperatures, rainfall, and duration of the light period. Inoculum availability was not a limiting factor for disease progress since urediniospores were present during most of the period studied. A major peak in numbers of rust spores followed the main peak of disease severity. Thus, rust epidemics on rose apple in central Brazil were shown to depend on the duration of leaf wetness in the dark, and also on night-time temperatures during that same wetness period. This study is the first example of a periodical analysis of an epidemic in a perennial crop. 相似文献
6.
Simulation of apparent infection rate to predict severity of soybean rust using a fuzzy logic system
ABSTRACT Few biologically based models to assess the risk of soybean rust have been developed because of difficulty in estimating variables related to infection rate of the disease. A fuzzy logic system, however, can estimate apparent infection rate by combining meteorological variables and biological criteria pertinent to soybean rust severity. In this study, a fuzzy logic apparent infection rate (FLAIR) model was developed to simulate severity of soybean rust and validated using data from field experiments on two soybean cultivars, TK 5 and G 8587. The FLAIR model estimated daily apparent infection rate of soybean rust and simulated disease severity based on population dynamics. In weekly simulation, the FLAIR model explained >85% of variation in disease severity. In simulation of an entire epidemic period, the FLAIR model was able to predict disease severity accurately once initial values of disease severity were predicted accurately. Our results suggest that a model could be developed to determine apparent infection rate and an initial value of disease severity in advance using forecasted weather data, which would provide accurate prediction of severity of soybean rust before the start of a season. 相似文献
7.
ABSTRACT Two models for predicting Septoria tritici on winter wheat (cv. Riband) were developed using a program based on an iterative search of correlations between disease severity and weather. Data from four consecutive cropping seasons (1993/94 until 1996/97) at nine sites throughout England were used. A qualitative model predicted the presence or absence of Septoria tritici (at a 5% severity threshold within the top three leaf layers) using winter temperature (January/February) and wind speed to about the first node detectable growth stage. For sites above the disease threshold, a quantitative model predicted severity of Septoria tritici using rainfall during stem elongation. A test statistic was derived to test the validity of the iterative search used to obtain both models. This statistic was used in combination with bootstrap analyses in which the search program was rerun using weather data from previous years, therefore uncorrelated with the disease data, to investigate how likely correlations such as the ones found in our models would have been in the absence of genuine relationships. 相似文献
8.
L. L. Loguercio L. S. Santos G. R. Niella R. A. C. Miranda J. T. de Souza R. T. Collins A.W.V. Pomella † 《Plant pathology》2009,58(6):1104-1115
The collective impact of several environmental factors on the biocontrol activity of Trichoderma stromaticum ( Ts ) against Moniliophthora perniciosa ( Mp ), the cause of cacao witches' broom disease, was assessed under field conditions of shaded cacao ( Theobroma cacao ) in south-eastern Bahia, Brazil. Biocontrol experiments were performed adjacent to an automated weather station, with sensors and Ts -treated brooms placed at different canopy heights. Sporulation occurred at the same dates for all Ts isolates, but in different quantities. Broom moisture >30%, air temperature of approximately 23 ± 3°C, relative humidity >90%, solar radiation intensities <0·12 KW m− ² and wind speed near zero were the key environmental parameters that preceded Ts sporulation events. A multiple logistic regression indicated that these weather variables combined were capable of distinguishing sporulation from non-sporulation events, with a significant effect of wind speed. Analyses of environmental factors at ground level indicated similar pre-sporulation conditions, with a soil moisture content above a threshold of 0·34 m3 m−3 preceding all sporulation events. The sporulation of five selected Ts isolates was compared at four different canopy heights. Isolates responded differently to weather variation in terms of sporulation and antagonism to Mp at different canopy levels, indicating that different microclimates are established along the vertical profile of a shaded cacao plantation. The potential of these findings for development of predictive mathematical models and disease-management approaches is discussed. 相似文献
9.
Effects of weather variables of mould development on sorghum grain were studied over three consecutive seasons in South Africa. Five sorghum hybrids planted at different dates ensured developing seeds were exposed to different weather conditions. Incidence of grain mould fungi was determined at harvest by incubating seeds on 2% malt extract agar. Averages of different weather variables (maximum and minimum temperatures, maximum relative humidity, total precipitation and frequency of precipitation) were determined for all permutations of weekly time intervals for a 2-month postflowering period to identify when these variables and pathogen incidence were significantly correlated. Significant correlations were used to develop models to quantify relationships between variables. Significant positive correlations were observed between the incidence of mould fungi and weather 4–6 weeks after flowering in the shorter season hybrid cv. Buster, and 5–8 weeks after flowering in the remaining hybrids. In most hybrids, correlations between the incidence of grain mould pathogens, including Alternaria alternata , Curvularia spp. ( C. lunata and C. clavata ), Fusarium spp. ( F. proliferatum and F. graminearum ), and Drechslera sorghicola , and average minimum temperature, total rainfall and frequency of rainfall were significant ( P = 0·05). In four hybrids, models showing a linear relationship between the logarithm of pathogen incidence and minimum temperature, and in one hybrid, between pathogen incidence and rainfall frequency, were developed. Depending on the hybrid, models that used minimum temperature as predictor described 60–82% of variation in the incidence of pathogens. Frequency of rainfall explained 93% of the variation in pathogen incidence in one sorghum hybrid genotype. Evaluation of the models using an independent data set yielded average prediction errors near zero, indicating that the models were acceptable. 相似文献
10.
European blackberry ( Rubus fruticosus agg.) is an aggregate of closely related taxa, with at least 15 taxa naturalized in Australia. Biological control of this Weed of National Significance, using the nonindigenous rust fungus Phragmidium violaceum , is effective when the weather is conducive to multiple cycles of infection, but some blackberry taxa escape severe disease. Thirty-one taxa of naturalized R. fruticosus agg. from southeastern Australia were isolated, their DNA phenotype determined and clones of each taxon inoculated with P. violaceum isolate SA1. Disease development was monitored for at least four generations of uredinia on large potted plants under field conditions. Although variation in mean disease severity appeared continuous over the range of Rubus clones tested, counts of uredinia and telia enabled identification of eight resistant taxa. Fine scale variation in susceptibility to rust disease was observed when different clones of R. leucostachys with the same DNA phenotype were found to express either resistance or susceptibility to P. violaceum (SA1). There were significant differences among 23 Rubus taxa rated as susceptible to rust disease in the mean number of leaves emerging per latent period of uredinia (LELPU). Mean LELPU appeared to account for some of the variation in two measures of mean disease severity observed among susceptible Rubus clones, although the correlation was insignificant (0·10 < P > 0·05). 相似文献
11.
Sébastien Guyader Julia Crombez Michèle Salles François Bussière Thierry Bajazet 《European journal of plant pathology / European Foundation for Plant Pathology》2013,136(3):535-545
Modelling the epidemiology of water yam anthracnose (Dioscorea alata) caused by the fungus Colletotrichum gloeosporioides is an important research goal, as it will allow the investigation of a wide range of scenarios of new practices to reduce the disease impact before experimentation in the field. Developing such a model requires a prior knowledge of the fungus’s response to the environmental conditions, which will be affected by pest management. In this work, we first measured the response of the fungus to the main physical environmental factors controlling its development, namely temperature (ranging from 18 °C to 36 °C) and wetness duration (from 2 h to 72 h). As response variables, we measured the percentage of formed appressoria (relative to the total number of spores), the length of the latent period (time lag between inoculation and first symptoms observed), and the rate of necrotic lesion extension (percentage of diseased leaf surface at different time steps). These variables allow us to estimate the effects of temperature and wetness duration on the success of infection (appressoria formation) and the subsequent rate of disease development (latent period length and lesion extension rate). The data were fitted to non-linear models chosen for their ability to describe the observed patterns. From our data and model analyses, we were able to estimate parameters such as the optimal and maximal temperatures (25–28 °C and 36 °C, respectively), the required wetness duration to reach 20 % of infection success and the time to reach 5 % disease severity as a function of temperature. 相似文献
12.
ABSTRACT Regional prevalence of soybean Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum, was modeled using tillage practices, soil texture, and weather variables (monthly air temperature and monthly precipitation from April to August) as inputs. Logistic regression was used to estimate the probability of stem rot prevalence with historical disease data from four states of the north-central region of the United States. Potential differences in disease prevalence between states in the region were addressed using regional indicator variables. Two models were developed: model I used spring (April) weather conditions and model II used summer (July and August) weather conditions as input variables. Both models had high explanatory power (78.5 and 77.8% for models I and II, respectively). To investigate the explanatory power of the models, each of the four states was divided into small geographic areas, and disease prevalence in each area was estimated using both models. The R(2) value of the regression analysis between observed and estimated SSR prevalence was 0.65 and 0.71 for models I and II, respectively. The same input variables were tested for their significance to explain the within-field SSR incidence by using Poisson regression analysis. Although all input variables were significant, only a small amount of variation of SSR incidence was explained, because R(2) of the regression analysis between observed and estimated SSR incidence was 0.065. Incorporation of available site-specific information (i.e., fungicide seed treatment, weed cultivation, and manure and fertilizer applications in a field) improved slightly the explained amount of SSR incidence (R(2) = 0.076). Predicted values of field incidence generally were overestimated in both models compared with the observed incidence. Our results suggest that preseason prediction of regional prevalence would be feasible. However, prediction of field incidence would not, and a different site-specific approach should be followed. 相似文献
13.
R. F. Santos M. Ciampi‐Guillardi L. Amorim N. S. Massola Júnior M. B. Spósito 《Plant pathology》2018,67(3):692-706
Anthracnose is an important disease in vineyards in south and southeast Brazil, the main grape‐producing regions in the country. This study aimed to identify the causal agents of grapevine anthracnose in Brazil through multilocus phylogenetic analyses, morphological characterization and pathogenicity tests. Thirty‐nine Elsinoë ampelina and 13 Colletotrichum spp. isolates were obtained from leaves, stems and berries with anthracnose symptoms collected in 38 vineyards in southern and southeastern Brazil. For E. ampelina isolates, the internal transcribed spacer (ITS), histone H3 (HIS3) and elongation factor 1‐α (TEF) sequences were analysed. HIS3 was the most informative region with 55 polymorphic sites including deletions and substitutions of bases, enabling the grouping of isolates into five haplotypes. Colonies of E. ampelina showed slow growth, variable colouration and a wrinkled texture on potato dextrose agar. Conidia were cylindrical to oblong with rounded ends, hyaline, aseptate, (3.57–) 5.64 (?6.95) μm long and (2.03–) 2.65 (?3.40) μm wide. Seven species of Colletotrichum were identified: C. siamense, C. gloeosporioides, C. fructicola, C. viniferum, C. nymphaeae, C. truncatum and C. cliviae, with a wide variation in colony and conidium morphology. Only E. ampelina caused anthracnose symptoms on leaves, tendrils and stems of Vitis vinifera and V. labrusca. High disease severity and a negative correlation between disease severity and shoot dry weight were observed only when relative humidity was above 95%. In this study, only E. ampelina caused anthracnose symptoms on grapevine shoots in Brazil. 相似文献
14.
ABSTRACT Sixty-five isolates of Alternaria alternata were sampled from brown spot lesions on tangerines and mandarins (Citrus reticulata) and tangerine x grapefruit (C. reticulata x C. paradisi) hybrids in the United States, Colombia, Australia, Turkey, South Africa, and Israel to investigate the worldwide phylogeography of the fungus. Genetic variation was scored at 15 putative random amplified polymorphic DNA (RAPD) loci and 465 bp of an endo-polygalacturonase (endo-PG) gene was sequenced for each isolate. Cluster analysis of RAPD genotypes revealed significant differentiation between United State and Colombia isolates and Turkey, South Africa, Israel, and Australia isolates. Sequencing of endo-PG revealed 21 variable sites when the outgroup A. gaisen (AK-toxin-producing pathogen of Japanese pear) was included and 13 variable sites among the sampled isolates. Nucleotide substitutions at 10 of 13 variable sites represented silent mutations when endo-PG was translated in frame. Eight distinct endo-PG haplotypes were found among the sampled isolates and estimation of a phylogeny with endo-PG sequence data revealed three clades, each with strong bootstrap support. The most basal clade (clade 1) was inferred based on its similarity to the outgroup A. gaisen and consisted exclusively of pathogenic isolates from the United States and Colombia. Clade 2 consisted of pathogenic and nonpathogenic isolates from the United States, Australia, South Africa, and Israel and clade 3 contained pathogenic and nonpathogenic isolates from Australia, South Africa, Israel, and Turkey. Quantitative estimates of virulence (disease incidence) were obtained for isolates from the United States, Colombia, South Africa, Israel, and Turkey by spray inoculating detached citrus leaves and counting the number of lesions 24 h after inoculation. Large differences in virulence were detected among isolates within each location and isolates from the United States were significantly more virulent than isolates from other locations. Several isolates from Colombia, South Africa, Israel, and Turkey had low virulence and 8% of all isolates were nonpathogenic. All but one of the nonpathogenic isolates were found in clade 2 of the endo-PG phylogeny, which also included the most highly virulent isolates sampled. 相似文献
15.
Three diagrammatic grading keys were designed for the assessment of the severity of late blight (caused by Phytophthora infestans ) in tomato leaves. Simplified and broad keys considered, respectively, six (3, 12, 22, 40, 60 and 77%) and eight (3, 6, 12, 22, 40, 60, 77 and 90%) levels of disease severity, whilst a modified key based on a previous proposal for potato late blight considered six levels (1, 5, 10, 16, 32 and 50%). The keys were validated by 24 evaluators who assessed digital images of tomato leaves exhibiting different areas with lesions. Evaluator errors were compared using a mixed model in which evaluators were considered as random effects and the keys and evaluations as fixed effects. The accuracy and precision of the evaluators were compared by simple linear regression between the estimated and actual values of disease severity. The repeatability of evaluators was assessed using Pearson's correlation coefficient. There was significant ( P ≤ 0·001) variability amongst the errors made by evaluators, although the precision of each of the three keys was high with a coefficient of determination (R2 ) of 0·96, 0·93 and 0·83 for the simplified, broad and modified key, respectively. Repeatability of estimations amongst the evaluators was adequate (correlation coefficients of 0·91, 0·91 and 0·90 for the three keys, respectively). The simplified and broad keys resulted in higher precision and accuracy for the estimation of severity than did the modified key. Since the simplified key considers a smaller number of disease severity levels, its use is recommended in the assessment of late blight in tomato leaves. 相似文献
16.
Weeds PL Chakraborty S Fernandes CD d'A Charchar MJ Ramesh CR Kexian Y Kelemu S 《Phytopathology》2003,93(2):176-185
ABSTRACT Using molecular markers, this work compares the genetic diversity in Colletotrichum gloeosporioides infecting species of the tropical forage legume Stylosanthes at the center of origin in Brazil and Colombia with that of Australia, China, and India, where Stylosanthes spp. have been introduced for commercial use. There was extensive diversity in the pathogen population from Brazil, Colombia, China, and India. The Australian pathogen population was least diverse probably due to its geographical isolation and effective quarantine. The extensive diversity in China and India means that threats from exotic pathogen races to Stylosanthes pastures can potentially come from countries outside the South American center of origin. In Brazil and India, both with native Stylosanthes populations, a high level of genetic differentiation in the pathogen population was associated with sites where native or naturalized host population was widely distributed. There was limited genetic diversity at germplasm evaluation sites, with a large proportion of isolates having identical haplotypes. This contrasts recent pathogenicity results for 78 of the Brazilian isolates that show hot spots of complex races are more common around research stations where host germplasm are tested, but few are found at sites containing wild host populations. For a pathogen in which the same races arise convergently from different genetic backgrounds, this study highlights the importance of using both virulence and selectively neutral markers to understand pathogen population structure. 相似文献
17.
Regression equations used as empirical models to predict rice blast caused by Pyricularia grisea on cv. Jinheung at Icheon, South Korea, and on cvs. IR50 and C22 at Cavinti, Philippines, were generated, using weather factors identified by the WINDOW PANE program to be highly correlated with disease. Consecutive days with RH≥80% (CDRH80), number of days with RH≥80% (NDRH80), consecutive days with precipitation, and number of days with precipitation ≥ 84 mm day−1 were important variables predicting blast at Icheon. Total precipitation, precipitation frequency, mean maximum and minimum temperatures, number of days with wind speed above 3.5 m s−1 , CDRH80, and NDRH80 were important predictors of blast at Cavinti. The Allen's predicted error sum of squares (PRESS) criterion and a cross-validation procedure were used to evaluate the models using data that were not included in model development. Validation test showed that all models developed for the two sites, except the models predicting maximum lesion number and panicle blast incidence at Icheon, and panicle blast severity on IR50 at Cavinti, predicted blast reasonably well based on low PRESS values and close to zero average prediction errors. These models can be applied in actual rice production systems, but future validation is needed to further improve their predictive ability. 相似文献
18.
ABSTRACT Logistic regression models for wheat Fusarium head blight were developed using information collected at 50 location-years, including four states, representing three different U.S. wheat-production regions. Non-parametric correlation analysis and stepwise logistic regression analysis identified combinations of temperature, relative humidity, and rainfall or durations of specified weather conditions, for 7 days prior to anthesis, and 10 days beginning at crop anthesis, as potential predictor variables. Prediction accuracy of developed logistic regression models ranged from 62 to 85%. Models suitable for application as a disease warning system were identified based on model prediction accuracy, sensitivity, specificity, and availability of weather variables at crop anthesis. Four of the identified models correctly classified 84% of the 50 location-years. A fifth model that used only pre-anthesis weather conditions correctly classified 70% of the location-years. The most useful predictor variables were the duration (h) of precipitation 7 days prior to anthesis, duration (h) that temperature was between 15 and 30 degrees C 7 days prior to anthesis, and the duration (h) that temperature was between 15 and 30 degrees C and relative humidity was greater than or equal to 90%. When model performance was evaluated with an independent validation set (n = 9), prediction accuracy was only 6% lower than the accuracy for the original data sets. These results indicate that narrow time periods around crop anthesis can be used to predict Fusarium head blight epidemics. 相似文献
19.
Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance. 相似文献
20.
Effects of nitrogen, phosphorus, potassium and calcium nutrition on strawberry anthracnose 总被引：1，自引：0，他引：1
The effects of a range of concentrations of four nutrients – nitrogen, phosphorus, potassium and calcium – in fertilizer solutions on the severity of anthracnose on strawberry cv. Nyoho cultivated under a noncirculation hydroponics system were determined after inoculation with Colletotrichum gloeosporioides . Crop growth and tissue nitrogen, phosphorus, potassium and calcium contents of the entire above-ground parts of the plant were also investigated. Elevated nitrogen and potassium concentrations in the fertilizer solution increased disease severity in contrast to phosphorus and calcium. Treatment with either NH4 or NO3 nitrogen was not significantly different. The dry weight of the strawberry plants increased significantly with elevated concentrations of nitrogen ( R 2 = 0·9078) and phosphorus ( R 2 = 0·8842), but was not influenced by the elevated amounts of potassium ( R 2 = 0·8587) and calcium ( R 2 = 0·6526) concentrations. 相似文献