The leaf nitrogen(N)to phosphorus(P)ratio(N:P)is a critical indicator of nutrient dynamics and ecosystem function.Investigating temporal variations in leaf N:P can provide valuable insights into how plants adapt to en...The leaf nitrogen(N)to phosphorus(P)ratio(N:P)is a critical indicator of nutrient dynamics and ecosystem function.Investigating temporal variations in leaf N:P can provide valuable insights into how plants adapt to environmental changes and nutrient availability.However,limited research has been conducted on long-term temporal leaf N:P variation over a range of temperature zones.Using long-term monitoring data from the Chinese Ecosystem Research Network(CERN),we investigated temporal changes in leaf N and P stoichiometry for 50 dominant tree species from 10 typical forest sites across temperate and subtropical regions,and identified the underlying mechanisms driving these changes.For both regions combined,leaf P concentration of the 50 dominant tree species decreased(20.6%),whereas leaf N:P increased(52.0%)from 2005 to 2020.Leaf P decreased and leaf N:P increased in 67% and 69% of the tree species,respectively.The leaf N:P increase was primarily driven by the tree species in eastern subtropical forests,where global change factors and soil nutrients explained 68% of leaf N:P variation.The P limitation exhibited by tree species in eastern subtropical forest ecosystems intensified over time,and elevated temperature and CO_(2) levels,coupled with decreased soil available P concentrations,appear to be the main factors driving long-term leaf N:P increases in these forests.Investigating long-term variations in soil nutrients together with global change factors will improve our understanding of the nutrient status of forest ecosystems in the context of global change and will support effective forest ecosystem management.展开更多
Real-time monitoring of nitrogen status in rice and wheat plant is of significant importance for nitrogen diagnosis, fertilization recommendation, and productivity prediction. With 11 field experiments involving diffe...Real-time monitoring of nitrogen status in rice and wheat plant is of significant importance for nitrogen diagnosis, fertilization recommendation, and productivity prediction. With 11 field experiments involving different cultivars, nitrogen rates, and water regimes, time-course measurements were taken of canopy hyperspeetral reflectance between 350-2 500 nm and leaf nitrogen accumulation （LNA） in rice and wheat. A new spectral analysis method through the consideration of characteristics of canopy components and plant growth status varied with phenological growth stages was designed to explore the common central bands in rice and wheat. Comprehensive analyses were made on the quantitative relationships of LNA to soil adjusted vegetation index （SAVI） and ratio vegetation index （RVI） composed of any two bands between 350-2 500 nm in rice and wheat. The results showed that the ranges of indicative spectral reflectance were largely located in 770-913 and 729-742 nm in both rice and wheat. The optimum spectral vegetation index for estimating LNA was SAVI （R822, R738） during the early-mid period （from jointing to booting）, and it was RVI （Rs22, R73s） during the mid-late period （from heading to filling） with the common central bands of 822 and 738 nm in rice and wheat. Comparison of the present spectral vegetation indices with previously reported vegetation indices gave a satisfactory performance in estimating LNA. It is concluded that the spectral bands of 822 and 738 nm can be used as common reflectance indicators for monitoring leaf nitrogen accumulation in rice and wheat.展开更多
Increasing leaf photosynthesis per area（A） is of great importance to achieve yield further improvement. The aim of this study was to exploit varietal difference in A and its correlation with specific leaf weight（SL...Increasing leaf photosynthesis per area（A） is of great importance to achieve yield further improvement. The aim of this study was to exploit varietal difference in A and its correlation with specific leaf weight（SLW）. Twelve rice cultivars, including 6 indica and 6 japonica varieties, were pot-grown under two N treatments, low N（LN） and sufficient N（SN）. Leaf photosynthesis and related parameters were measured at tillering stage. Compared with LN treatment, A, stomatal conductance（g_s）, mesophyll conductance（g_m）, leaf N content（N_（area））, and chlorophyll content were significantly improved under SN treatment, while SLW and photosynthetic N use efficiency（PNUE） were generally decreased. Varietal difference in A was positively related to both g_s and g_m, but not related to N_（area）. This resulted in a low PNUE in high N_（area） leaves. Varietal difference in PNUE was generally negatively related to SLW. Response of PNUE to N supply varied among different rice cultivars, and interestingly, the decrease in PNUE under SN was negatively related to the decrease in SLW. With a higher N_（area）, japonica rice cultivars did not show a higher A than indica rice cultivars because of possession of high-SLW leaves. Therefore, varietal difference in A was not related to N_（area）, and SLW can substantially interfere with the correlation between A and N_（area）. These findings may provide useful information for rice breeders to maximize A and PNUE, rather than over reliance on N_（area） as an indicator of photosynthetic performance.展开更多
Employing the pot experiment of the complete random block design with 6 replications,four varieties of japonica rice (Fujisaka 5,Honenwase,Akitakomachi and Taichung 65) were used to study the varietal differences in l...Employing the pot experiment of the complete random block design with 6 replications,four varieties of japonica rice (Fujisaka 5,Honenwase,Akitakomachi and Taichung 65) were used to study the varietal differences in leaf nitrogen content(LNC) and leaf area during mature period,their relation and effects to the ripening rate.The results showed that(1) thee were varietal differences in LNC at the heading stage and the LNC decrease rate during the matue period,the high LNC at the heading stage was related to the rapid LNC decrease.(2) There were two phases of the leaf area changing process during the mature period,first was the stable,and second was the decreased phase.There was varietal difference in the critical time of phase 1 and phase 2.The hign leaf area in the phase 1 was in relation to the rapid leaf area decrease in the phase 2.It was not found that there was relation between the leaf quality and quantity.(3)It wa unfavorable to the ripening rate for the high leaf area at the heading stage and the rapid decrease of the leaf area during the mature period.(4)It was put forward that the super high yield rice variety should possess the not very high leaf area and high LNC at the heading stage,slow senescence in the leaf area during the mature period.展开更多
The radiation use efficiency(RUE)is one of the most important functional traits determining crop productivity.The coordination of the vertical distribution of light and leaf nitrogen has been proven to be effective in...The radiation use efficiency(RUE)is one of the most important functional traits determining crop productivity.The coordination of the vertical distribution of light and leaf nitrogen has been proven to be effective in boosting the RUE from both experimental and computational evidence.However,previous simulation studies have primarily assumed that the leaf area is uniformly distributed along the canopy depth,rarely considering the optimization of the leaf area distribution,especially for C4 crops.The present study hypothesizes that the RUE may be maximized by matching the leaf area and leaf nitrogen vertical distributions in the canopy.To test this hypothesis,various virtual maize canopies were generated by combining the leaf inclination angle,vertical leaf area distribution,and vertical leaf nitrogen distribution and were further evaluated by an improved multilayer canopy photosynthesis model.We found that a greater fraction of leaf nitrogen is preferentially allocated to canopy layers with greater leaf areas to maximize the RUE.The coordination of light and nitrogen emerged as a property from the simulations to maximize the RUE in most scenarios,particularly in dense canopies.This study not only facilitates explicit and precise profiling of ideotypes for maximizing the RUE but also represents a primary step toward high-throughput phenotyping and screening of the RUE for massive numbers of inbred lines and cultivars.展开更多
Leaf nitrogen(N) and phosphorus(P) concentrations are critical for photosynthesis, growth, reproduction and other ecological processes of plants. Previous studies on large-scale biogeographic patterns of leaf N and P ...Leaf nitrogen(N) and phosphorus(P) concentrations are critical for photosynthesis, growth, reproduction and other ecological processes of plants. Previous studies on large-scale biogeographic patterns of leaf N and P stoichiometric relationships were mostly conducted using data pooled across taxa, while family/genus-level analyses are rarely reported. Here, we examined global patterns of family-specific leaf N and P stoichiometry using a global data set of 12,716 paired leaf N and P records which includes 204 families, 1,305 genera, and 3,420 species. After determining the minimum size of samples(i.e., 35 records), we analyzed leaf N and P concentrations, N:P ratios and N^P scaling relationships of plants for 62 families with 11,440 records. The numeric values of leaf N and P stoichiometry varied significantly across families and showed diverse trends along gradients of mean annual temperature(MAT) and mean annual precipitation(MAP). The leaf N and P concentrations and N:P ratios of 62 families ranged from 6.11 to 30.30 mg g–1, 0.27 to 2.17 mg g–1, and 10.20 to 35.40, respectively. Approximately 1/3–1/2 of the families(22–35 of 62) showed a decrease in leaf N and P concentrations and N:P ratios with increasing MAT or MAP, while the remainder either did not show a significant trend or presented the opposite pattern. Family-specific leaf N^P scaling exponents did not converge to a certain empirical value, with a range of 0.307–0.991 for 54 out of 62 families which indicated a significant N^P scaling relationship. Our results for the first time revealed large variation in the family-level leaf N and P stoichiometry of global terrestrial plants and that the stoichiometric relationships for at least one-third of the families were not consistent with the global trends reported previously. The numeric values of the family-specific leaf N and P stoichiometry documented in the current study provide critical synthetic parameters for biogeographic modeling and for further studies on the physiological and ecological mechanisms underlying the nutrient use strategies of plants from different phylogenetic taxa.展开更多
The yield of maize(Zea mays L.)is highly influenced by nitrogen fertilization.This study investigated the impact of nitrogen fertilization on morphophysiological traits in maize(Zea mays L.)and developed algorithms to...The yield of maize(Zea mays L.)is highly influenced by nitrogen fertilization.This study investigated the impact of nitrogen fertilization on morphophysiological traits in maize(Zea mays L.)and developed algorithms to relate manual phenotyping and digital phenotyping of maize with leaf nitrogen and digital field image traits.The experiment included three hybrid maize varieties,V1(Hybrid 981),V2(BARI Hybrid maize-9),and V3(Hybrid P3396),which were evaluated across three nitrogen levels(N1=100 kg N ha^(−1),N2=200 kg N ha^(−1),N3=300 kg N ha^(−1))in a split-plot design with three replications.The results revealed that nitrogen levels(N),varieties(V),and their interactions(V×N)significantly influenced traits such as plant height(PH),leaf area index(LAI),normalized difference vegetation index(NDVI),canopy cover(CC),chlorophyll content(Chl a and Chl b),leaf nitrogen content(LNC),total dry matter(TDM),and grain yield.The hybrid P3396 with 300 kg N ha^(−1)(V3N3)achieved the highest grain yield of 14.45 t ha^(−1),which was statistically similar to that of Hybrid 981 and 300 kg N ha^(−1)(V1N3).Nitrogen significantly improved dry matter accumulation,leaf area,and physiological parameters,with maximum values recorded during flowering.The NDVI,CC,and SPAD were strongly correlated with LNC and TDM,highlighting their potential as indicators for nitrogen management.The digital imaging traits analysed via software effectively differentiated the nitrogen treatments,demonstrating their utility for precise nitrogen application.In conclusion,nitrogen fertilization at 300 kg N ha^(−1) optimized the growth and yield of hybrid maize,with Hybrid P3396 performing best.This study underscores the role of advanced phenotyping tools in improving nitrogen use efficiency and sustainable maize production.展开更多
Field experiments were conducted in the Ebro Delta area （Spain）, from 2007 to 2009 with two rice varieties： Gleva and Tebre. The experimental treatments included a series of seed rates, two different water manageme...Field experiments were conducted in the Ebro Delta area （Spain）, from 2007 to 2009 with two rice varieties： Gleva and Tebre. The experimental treatments included a series of seed rates, two different water management systems and two different nitrogen fertilization times. The number of leaves on the main stems and their emergence time were periodically tagged. The results indicated that the final leaf number on the main stems in the two rice varieties was quite stable over a three-year period despite of the differences in their respective growth cycles. Interaction between nitrogen fertilization and water management influenced the final leaf number on the main stems. Plant density also had a significant influence on the rate of leaf appearance by extending the phyllochron and postponing the onset of intraspecific competition after the emergence of the 7th leaf on the main stems. Final leaf number on the main stems was negatively related to plant density. A relationship between leaf appearance and thermal time was established with a strong nonlinear function. In direct-seeded rice, the length of the phyllochron increases exponentially in line with the advance of plant development. A general model, derived from 2-year experimental data, was developed and satisfactorily validated; it had a root mean square error of 0.3 leaf. An exponential model can be used to predict leaf emergence in direct-seeded rice.展开更多
Greenness and nitrogen content of each leaf on main stem of different japonica and indica rice varieties under different nitrogen levels were investigated. Results showed that the fourth leaf from the top exhibited ac...Greenness and nitrogen content of each leaf on main stem of different japonica and indica rice varieties under different nitrogen levels were investigated. Results showed that the fourth leaf from the top exhibited active changes with the change of plant nitrogen status. When the plant nitrogen content was low, its color and nitrogen content were obviously lower than those of the three top leaves. With the increase of plant nitrogen content, the color and nitrogen content of the fourth leaf increased quickly, and the differences of color and nitrogen content between the fourth leaf and the three top leaves decreased. So, the fourth leaf was an ideal indication of plant nutrition status. In addition, color difference between the fourth and the third leaf from the top was highly related to the plant nitrogen content regardless of the variety and development stage. Therefore, color difference between the fourth and the third leaf could be widely used for diagnosis of plant nutrition. Results also indicated that the minimized color difference between the fourth and the third leaf at the critical effective tillering, the emergence of the second leaf from the top, and the heading was the symbol of high yield. Plant nitrogen content of 27 g kg-1 DW for japonica rice and 25 g kg-1 DW for indica were the critical nitrogen concentrations.展开更多
Excessive use of nitrogen (N) fertilizers in agricultural systems increases the cost of production and risk of environmental pollution. Therefore, determination of optimum N requirements for plant growth is necessary....Excessive use of nitrogen (N) fertilizers in agricultural systems increases the cost of production and risk of environmental pollution. Therefore, determination of optimum N requirements for plant growth is necessary. Previous studies mostly established critical N dilution curves based on aboveground dry matter (DM) or leaf dry matter (LDM) and stem dry matter (SDM), to diagnose the N nutrition status of the whole plant. As these methods are time consuming, we investigated the more rapidly determined leaf area index (LAI) method to establish the critical nitrogen (Nc) dilution curve, and the curve was used to diagnose plant N status for winter wheat in Guanzhong Plain in Northwest China. Field experiments were conducted using four N fertilization levels (0, 105, 210 and 315 kg ha?1) applied to six wheat cultivars in the 2013–2014 and 2014–2015 growing seasons. LAI, DM, plant N concentration (PNC) and grain yield were determined. Data points from four cultivars were used for establishing the Nc curve and data points from the remaining two cultivars were used for validating the curve. The Nc dilution curve was validated for N-limiting and non-N-limiting growth conditions and there was good agreement between estimated and observed values. The N nutrition index (NNI) ranged from 0.41 to 1.25 and the accumulated plant N deficit (Nand) ranged from 60.38 to –17.92 kg ha?1 during the growing season. The relative grain yield was significantly affected by NNI and was adequately described with a parabolic function. The Nc curve based on LAI can be adopted as an alternative and more rapid approach to diagnose plant N status to support N fertilization decisions during the vegetative growth of winter wheat in Guanzhong Plain in Northwest China.展开更多
Leaf area index （LAI） is used for crop growth monitoring in agronomic research, and is promising to diagnose the nitrogen （N） status of crops. This study was conducted to develop appropriate LAI-based N diagnostic...Leaf area index （LAI） is used for crop growth monitoring in agronomic research, and is promising to diagnose the nitrogen （N） status of crops. This study was conducted to develop appropriate LAI-based N diagnostic models in irrigated lowland rice. Four field experiments were carried out in Jiangsu Province of East China from 2009 to 2014. Different N application rates and plant densities were used to generate contrasting conditions of N availability or population densities in rice. LAI was determined by LI-3000, and estimated indirectly by LAI-2000 during vegetative growth period. Group and individual plant characters （e.g., tiller number （TN） and plant height （H）） were investigated simultaneously. Two N indicators of plant N accumulation （NA） and N nutrition index （NNI） were measured as well. A calibration equation （LAI=1.7787LAI2o00-0.8816, R2=0.870＂） was developed for LAI-2000. The linear regression analysis showed a significant relationship between NA and actual LAI （R2=0.863^＊＊）. For the NNI, the relative LAI （R2=0.808-） was a relatively unbiased variable in the regression than the LAI （R^2=0.33^＊＊）. The results were used to formulate two LAI-based N diagnostic models for irrigated lowland rice （NA=29.778LAI-5.9397; NNI=0.7705RLAI＋0.2764）. Finally, a simple LAI deterministic model was developed to estimate the actual LAI using the characters of TN and H （LAI=-0.3375（THxHx0.01）2＋3.665（TH×H×0.01）-1.8249, R2=0.875＊＊）. With these models, the N status of rice can be diagnosed conveniently in the field.展开更多
A field trial comprising 3 rice varieties (NDR-359, Sarju 52, HUBR 2-1) and 4 LCC scores (≤ 2, ≤ 3, ≤ 4, ≤ 5) along with the recommended dose of N was conducted in a split plot design to calibrate the LCC for nitr...A field trial comprising 3 rice varieties (NDR-359, Sarju 52, HUBR 2-1) and 4 LCC scores (≤ 2, ≤ 3, ≤ 4, ≤ 5) along with the recommended dose of N was conducted in a split plot design to calibrate the LCC for nitrogen requirement of rice. Maximum grain yields of NDR-359, Sarju 52 at LCC ≤ 5 and HUBR 2-1 at LCC ≤ 4 were found to be 47.10, 40.66 and 36.04 q/ha respectively. The critical LCC score for real time nitrogen requirement for NDR 359 and Sarju 52 was found to be ≤ 5, while for HUBR 2-1 it was ≤ 4. Agronomic and recovery efficiency of nitrogen also followed the same trend. In the functional relationship between SPAD value and LCC score, while it was linear in NDR-359 and Sarju 52, for HUBR 2-1 it was quadratic. Further a positive correlation between SPAD values and LCC score was observed in all the 3 varieties.展开更多
The response of transcription factor genes to low nitrogen stress was studied to provide molecular basis for improving the absorption and utilization efficiency of nitrogen fertilizer in rice. The agilent rice genome ...The response of transcription factor genes to low nitrogen stress was studied to provide molecular basis for improving the absorption and utilization efficiency of nitrogen fertilizer in rice. The agilent rice genome arrays were used to study the varied expression of transcription factor genes in two rice varieties （SN 196 and Toyonishhiki） with different chlorophyll contents under low nitrogen stress. The results showed that a total of 53 transcription factor genes （35 down-regulated and 18 up-regulated genes at the transcription level） in flag leaves of super-green rice SN196 and 27 transcription factor genes （21 down-regulated and 6 up-regulated genes at the transcription level） in flag leaves of Toyonishiki were affected by low nitrogen stress. Among those nitrogen-responsive genes, 48 transcription factor genes in SN196 and 22 in Toyonishiki were variety-specific. There were overlapped transcription factor genes responded to low nitrogen stress between SN196 and Toyonishiki, with 1 up-regulated and 4 down-regulated at the transcription level. Distributions of low nitrogen responsive genes on chromosomes were different in two rice varieties.展开更多
Remote sensing has been increasingly used for precision nitrogen management to assess the plant nitrogen status in a spatial and real-time manner.The nitrogen nutrition index(NNI)can quantitatively describe the nitrog...Remote sensing has been increasingly used for precision nitrogen management to assess the plant nitrogen status in a spatial and real-time manner.The nitrogen nutrition index(NNI)can quantitatively describe the nitrogen status of crops.Nevertheless,the NNI diagnosis for cotton with unmanned aerial vehicle(UAV)multispectral images has not been evaluated yet.This study aimed to evaluate the performance of three machine learning models,i.e.,support vector machine(SVM),back propagation neural network(BPNN),and extreme gradient boosting(XGB)for predicting canopy nitrogen weight and NNI of cotton over the whole growing season from UAV images.The results indicated that the models performed better when the top 15 vegetation indices were used as input variables based on their correlation ranking with nitrogen weight and NNI.The XGB model performed the best among the three models in predicting nitrogen weight.The prediction accuracy of nitrogen weight at the upper half-leaf level(R^(2)=0.89,RMSE=0.68 g m^(-2),RE=14.62%for calibration and R^(2)=0.83,RMSE=1.08 g m^(-2),RE=19.71%for validation)was much better than that at the all-leaf level(R^(2)=0.73,RMSE=2.20 g m^(-2),RE=26.70%for calibration and R^(2)=0.70,RMSE=2.48 g m^(-2),RE=31.49%for validation)and at the plant level(R^(2)=0.66,RMSE=4.46 g m^(-2),RE=30.96%for calibration and R^(2)=0.63,RMSE=3.69 g m^(-2),RE=24.81%for validation).Similarly,the XGB model(R^(2)=0.65,RMSE=0.09,RE=8.59%for calibration and R^(2)=0.63,RMSE=0.09,RE=8.87%for validation)also outperformed the SVM model(R^(2)=0.62,RMSE=0.10,RE=7.92%for calibration and R^(2)=0.60,RMSE=0.09,RE=8.03%for validation)and BPNN model(R^(2)=0.64,RMSE=0.09,RE=9.24%for calibration and R^(2)=0.62,RMSE=0.09,RE=8.38%for validation)in predicting NNI.The NNI predictive map generated from the optimal XGB model can intuitively diagnose the spatial distribution and dynamics of nitrogen nutrition in cotton fields,which can help farmers implement precise cotton nitrogen management in a timely and accurate manner.展开更多
Investigating the effects of ontogenetic stage and leaf age on leaf traits is important for understanding the utilization and distribution of resources in the process of plant growth.However,few studies have been cond...Investigating the effects of ontogenetic stage and leaf age on leaf traits is important for understanding the utilization and distribution of resources in the process of plant growth.However,few studies have been conducted to show how traits and trait-trait relationships change across a range of ontogenetic stage and leaf age for evergreen coniferous species.We divided 67 Pinus koraiensis Sieb.et Zucc.of various sizes(0.3-100 cm diameter at breast height,DBH)into four ontogenetic stages,i.e.,young trees,middle-aged trees,mature trees and over-mature trees,and measured the leaf mass per area(LMA),leaf dry matter content(LDMC),and mass-based leaf nitrogen content(N)and phosphorus content(P)of each leaf age group for each sampled tree.One-way analysis of variance(ANOVA)was used to describe the variation in leaf traits by ontogenetic stage and leaf age.The standardized major axis method was used to explore the effects of ontogenetic stage and leaf age on trait-trait relationships.We found that LMA and LDMC increased significantly and N and P decreased significantly with increases in the ontogenetic stage and leaf age.Most trait-trait relationships were consistent with the leaf economic spectrum(LES)at a global scale.Among them,leaf N content and LDMC showed a significant negative correlation,leaf N and P contents showed a significant positive correlation,and the absolute value of the slopes of the trait-trait relationships showed a gradually increasing trend with an increasing ontogenetic stage.LMA and LDMC showed a significant positive correlation,and the slopes of the trait-trait relationships showed a gradually decreasing trend with leaf age.Additionally,there were no significant relationships between leaf N content and LMA in most groups,which is contrary to the expectation of the LES.Overall,in the early ontogenetic stages and leaf ages,the leaf traits tend to be related to a"low investment-quick returns"resource strategy.In contrast,in the late ontogenetic stages and leaf ages,they tend to be related to a"high investment-slow returns"resource strategy.Our results reflect the optimal allocation of resources in Pinus koraiensis according to its functional needs during tree and leaf ontogeny.展开更多
Nitrogen（N） fertilizer experiments were conducted to investigate the optimal subtending leaf N concentration for fiber strength,and its relationship with activities of key enzymes（sucrose synthase and β-1,3-glucan...Nitrogen（N） fertilizer experiments were conducted to investigate the optimal subtending leaf N concentration for fiber strength,and its relationship with activities of key enzymes（sucrose synthase and β-1,3-glucanase） and contents of key constituents（sucrose and β-1,3-glucan） involved in fiber strength development in the lower,middle and upper fruiting branches of two cotton cultivars（Kemian 1 and NuCOTN 33B）.For each sampling day,we simulated changes in fiber strength,activity of sucrose synthase and β-1,3-glucanase and levels of sucrose and β-1,3-glucan in response to leaf N concentration using quadratic eqs.;the optimal subtending leaf N concentrations were deduced from the eqs.For the same fruiting branch,changes in the optimal leaf N concentration based on fiber development（DPA） could be simulated by power functions.From these functions,the average optimal subtending leaf N concentrations during fiber development for the cultivar,Kemian 1,were 2.84% in the lower fruiting branches,3.15% in the middle fruiting branches and 3.04% in the upper fruiting branches.For the cultivar,NuCOTN 33B,the optimum concentrations were 3.04,3.28 and 3.18% in the lower,middle and upper fruiting branches,respectively.This quantification may be used as a monitoring index for evaluating fiber strength and its related key enzymes and constituents during fiber formation at the lower,middle and upper fruiting branches.展开更多
基金supported by the National Natural Science Foundation of China(No.42030509)the Special Project on National Science and Technology Basic Resources Investigation of China(No.2021FY100705).
文摘The leaf nitrogen(N)to phosphorus(P)ratio(N:P)is a critical indicator of nutrient dynamics and ecosystem function.Investigating temporal variations in leaf N:P can provide valuable insights into how plants adapt to environmental changes and nutrient availability.However,limited research has been conducted on long-term temporal leaf N:P variation over a range of temperature zones.Using long-term monitoring data from the Chinese Ecosystem Research Network(CERN),we investigated temporal changes in leaf N and P stoichiometry for 50 dominant tree species from 10 typical forest sites across temperate and subtropical regions,and identified the underlying mechanisms driving these changes.For both regions combined,leaf P concentration of the 50 dominant tree species decreased(20.6%),whereas leaf N:P increased(52.0%)from 2005 to 2020.Leaf P decreased and leaf N:P increased in 67% and 69% of the tree species,respectively.The leaf N:P increase was primarily driven by the tree species in eastern subtropical forests,where global change factors and soil nutrients explained 68% of leaf N:P variation.The P limitation exhibited by tree species in eastern subtropical forest ecosystems intensified over time,and elevated temperature and CO_(2) levels,coupled with decreased soil available P concentrations,appear to be the main factors driving long-term leaf N:P increases in these forests.Investigating long-term variations in soil nutrients together with global change factors will improve our understanding of the nutrient status of forest ecosystems in the context of global change and will support effective forest ecosystem management.
基金supported by the National High-Tech R&D Program of China(2011AA100703)the National Natural Science Foundation of China(30900868)+2 种基金the Natural Science Foundation of Jiangsu Province, China(BK2010453)the Academic Program Development of Jiangsu Higher Education Institutions, China(PAPD)the Science and Technology Support Plan of Jiangsu Province, China(BE2011351)
文摘Real-time monitoring of nitrogen status in rice and wheat plant is of significant importance for nitrogen diagnosis, fertilization recommendation, and productivity prediction. With 11 field experiments involving different cultivars, nitrogen rates, and water regimes, time-course measurements were taken of canopy hyperspeetral reflectance between 350-2 500 nm and leaf nitrogen accumulation （LNA） in rice and wheat. A new spectral analysis method through the consideration of characteristics of canopy components and plant growth status varied with phenological growth stages was designed to explore the common central bands in rice and wheat. Comprehensive analyses were made on the quantitative relationships of LNA to soil adjusted vegetation index （SAVI） and ratio vegetation index （RVI） composed of any two bands between 350-2 500 nm in rice and wheat. The results showed that the ranges of indicative spectral reflectance were largely located in 770-913 and 729-742 nm in both rice and wheat. The optimum spectral vegetation index for estimating LNA was SAVI （R822, R738） during the early-mid period （from jointing to booting）, and it was RVI （Rs22, R73s） during the mid-late period （from heading to filling） with the common central bands of 822 and 738 nm in rice and wheat. Comparison of the present spectral vegetation indices with previously reported vegetation indices gave a satisfactory performance in estimating LNA. It is concluded that the spectral bands of 822 and 738 nm can be used as common reflectance indicators for monitoring leaf nitrogen accumulation in rice and wheat.
基金supported by the National Natural Science Foundation of China(31301840)the National Excellent Doctoral Dissertation of China(201465)+2 种基金the Program for Changjiang Scholars and Innovative Research Team in University of China(IRT1247)the Natural Science Foundation of Hubei Province,China(2013CFB201)the Fundamental Research Funds for the Central Universities,China(2013PY107)
文摘Increasing leaf photosynthesis per area（A） is of great importance to achieve yield further improvement. The aim of this study was to exploit varietal difference in A and its correlation with specific leaf weight（SLW）. Twelve rice cultivars, including 6 indica and 6 japonica varieties, were pot-grown under two N treatments, low N（LN） and sufficient N（SN）. Leaf photosynthesis and related parameters were measured at tillering stage. Compared with LN treatment, A, stomatal conductance（g_s）, mesophyll conductance（g_m）, leaf N content（N_（area））, and chlorophyll content were significantly improved under SN treatment, while SLW and photosynthetic N use efficiency（PNUE） were generally decreased. Varietal difference in A was positively related to both g_s and g_m, but not related to N_（area）. This resulted in a low PNUE in high N_（area） leaves. Varietal difference in PNUE was generally negatively related to SLW. Response of PNUE to N supply varied among different rice cultivars, and interestingly, the decrease in PNUE under SN was negatively related to the decrease in SLW. With a higher N_（area）, japonica rice cultivars did not show a higher A than indica rice cultivars because of possession of high-SLW leaves. Therefore, varietal difference in A was not related to N_（area）, and SLW can substantially interfere with the correlation between A and N_（area）. These findings may provide useful information for rice breeders to maximize A and PNUE, rather than over reliance on N_（area） as an indicator of photosynthetic performance.
文摘Employing the pot experiment of the complete random block design with 6 replications,four varieties of japonica rice (Fujisaka 5,Honenwase,Akitakomachi and Taichung 65) were used to study the varietal differences in leaf nitrogen content(LNC) and leaf area during mature period,their relation and effects to the ripening rate.The results showed that(1) thee were varietal differences in LNC at the heading stage and the LNC decrease rate during the matue period,the high LNC at the heading stage was related to the rapid LNC decrease.(2) There were two phases of the leaf area changing process during the mature period,first was the stable,and second was the decreased phase.There was varietal difference in the critical time of phase 1 and phase 2.The hign leaf area in the phase 1 was in relation to the rapid leaf area decrease in the phase 2.It was not found that there was relation between the leaf quality and quantity.(3)It wa unfavorable to the ripening rate for the high leaf area at the heading stage and the rapid decrease of the leaf area during the mature period.(4)It was put forward that the super high yield rice variety should possess the not very high leaf area and high LNC at the heading stage,slow senescence in the leaf area during the mature period.
基金supported by the National Key R&D Program of China(2022YFD2001003)the National Natural Science Foundation of China(32330075 and 32001420)+2 种基金the Science and Technology Innovation Special Construction Funded Program of Beijing Academy of Agriculture and Forestry Sciences(KJCX20220401)the Young Elite Scientist Sponsorship Program by BAST(no.BYESS2023204)the earmarked fund for CARS-02 and CARS-54.
文摘The radiation use efficiency(RUE)is one of the most important functional traits determining crop productivity.The coordination of the vertical distribution of light and leaf nitrogen has been proven to be effective in boosting the RUE from both experimental and computational evidence.However,previous simulation studies have primarily assumed that the leaf area is uniformly distributed along the canopy depth,rarely considering the optimization of the leaf area distribution,especially for C4 crops.The present study hypothesizes that the RUE may be maximized by matching the leaf area and leaf nitrogen vertical distributions in the canopy.To test this hypothesis,various virtual maize canopies were generated by combining the leaf inclination angle,vertical leaf area distribution,and vertical leaf nitrogen distribution and were further evaluated by an improved multilayer canopy photosynthesis model.We found that a greater fraction of leaf nitrogen is preferentially allocated to canopy layers with greater leaf areas to maximize the RUE.The coordination of light and nitrogen emerged as a property from the simulations to maximize the RUE in most scenarios,particularly in dense canopies.This study not only facilitates explicit and precise profiling of ideotypes for maximizing the RUE but also represents a primary step toward high-throughput phenotyping and screening of the RUE for massive numbers of inbred lines and cultivars.
基金supported by the National Natural Science Foundation of China (31800397)National Key Research and Development Program of China (2017YFC0503900)+2 种基金the TRY initiative on plant traits (http://www.try-db.org)The TRY database is hosted at the Max Planck Institute for Biogeochemistry (Jena, Germany)supported by DIVERSITAS/Future Earth, the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and EU project BACI (640176)
文摘Leaf nitrogen(N) and phosphorus(P) concentrations are critical for photosynthesis, growth, reproduction and other ecological processes of plants. Previous studies on large-scale biogeographic patterns of leaf N and P stoichiometric relationships were mostly conducted using data pooled across taxa, while family/genus-level analyses are rarely reported. Here, we examined global patterns of family-specific leaf N and P stoichiometry using a global data set of 12,716 paired leaf N and P records which includes 204 families, 1,305 genera, and 3,420 species. After determining the minimum size of samples(i.e., 35 records), we analyzed leaf N and P concentrations, N:P ratios and N^P scaling relationships of plants for 62 families with 11,440 records. The numeric values of leaf N and P stoichiometry varied significantly across families and showed diverse trends along gradients of mean annual temperature(MAT) and mean annual precipitation(MAP). The leaf N and P concentrations and N:P ratios of 62 families ranged from 6.11 to 30.30 mg g–1, 0.27 to 2.17 mg g–1, and 10.20 to 35.40, respectively. Approximately 1/3–1/2 of the families(22–35 of 62) showed a decrease in leaf N and P concentrations and N:P ratios with increasing MAT or MAP, while the remainder either did not show a significant trend or presented the opposite pattern. Family-specific leaf N^P scaling exponents did not converge to a certain empirical value, with a range of 0.307–0.991 for 54 out of 62 families which indicated a significant N^P scaling relationship. Our results for the first time revealed large variation in the family-level leaf N and P stoichiometry of global terrestrial plants and that the stoichiometric relationships for at least one-third of the families were not consistent with the global trends reported previously. The numeric values of the family-specific leaf N and P stoichiometry documented in the current study provide critical synthetic parameters for biogeographic modeling and for further studies on the physiological and ecological mechanisms underlying the nutrient use strategies of plants from different phylogenetic taxa.
基金supported by the Bangladesh Agricultural Research Insti-tute,Gazipur-1701,Bangladesh.This research was also funded by Taif University,Saudi Arabia,Project No.(TU-DSPP-2024-07).
文摘The yield of maize(Zea mays L.)is highly influenced by nitrogen fertilization.This study investigated the impact of nitrogen fertilization on morphophysiological traits in maize(Zea mays L.)and developed algorithms to relate manual phenotyping and digital phenotyping of maize with leaf nitrogen and digital field image traits.The experiment included three hybrid maize varieties,V1(Hybrid 981),V2(BARI Hybrid maize-9),and V3(Hybrid P3396),which were evaluated across three nitrogen levels(N1=100 kg N ha^(−1),N2=200 kg N ha^(−1),N3=300 kg N ha^(−1))in a split-plot design with three replications.The results revealed that nitrogen levels(N),varieties(V),and their interactions(V×N)significantly influenced traits such as plant height(PH),leaf area index(LAI),normalized difference vegetation index(NDVI),canopy cover(CC),chlorophyll content(Chl a and Chl b),leaf nitrogen content(LNC),total dry matter(TDM),and grain yield.The hybrid P3396 with 300 kg N ha^(−1)(V3N3)achieved the highest grain yield of 14.45 t ha^(−1),which was statistically similar to that of Hybrid 981 and 300 kg N ha^(−1)(V1N3).Nitrogen significantly improved dry matter accumulation,leaf area,and physiological parameters,with maximum values recorded during flowering.The NDVI,CC,and SPAD were strongly correlated with LNC and TDM,highlighting their potential as indicators for nitrogen management.The digital imaging traits analysed via software effectively differentiated the nitrogen treatments,demonstrating their utility for precise nitrogen application.In conclusion,nitrogen fertilization at 300 kg N ha^(−1) optimized the growth and yield of hybrid maize,with Hybrid P3396 performing best.This study underscores the role of advanced phenotyping tools in improving nitrogen use efficiency and sustainable maize production.
基金supported by the IRTA (Institute for Food and Agricultural Research and Technology), Spain
文摘Field experiments were conducted in the Ebro Delta area （Spain）, from 2007 to 2009 with two rice varieties： Gleva and Tebre. The experimental treatments included a series of seed rates, two different water management systems and two different nitrogen fertilization times. The number of leaves on the main stems and their emergence time were periodically tagged. The results indicated that the final leaf number on the main stems in the two rice varieties was quite stable over a three-year period despite of the differences in their respective growth cycles. Interaction between nitrogen fertilization and water management influenced the final leaf number on the main stems. Plant density also had a significant influence on the rate of leaf appearance by extending the phyllochron and postponing the onset of intraspecific competition after the emergence of the 7th leaf on the main stems. Final leaf number on the main stems was negatively related to plant density. A relationship between leaf appearance and thermal time was established with a strong nonlinear function. In direct-seeded rice, the length of the phyllochron increases exponentially in line with the advance of plant development. A general model, derived from 2-year experimental data, was developed and satisfactorily validated; it had a root mean square error of 0.3 leaf. An exponential model can be used to predict leaf emergence in direct-seeded rice.
文摘Greenness and nitrogen content of each leaf on main stem of different japonica and indica rice varieties under different nitrogen levels were investigated. Results showed that the fourth leaf from the top exhibited active changes with the change of plant nitrogen status. When the plant nitrogen content was low, its color and nitrogen content were obviously lower than those of the three top leaves. With the increase of plant nitrogen content, the color and nitrogen content of the fourth leaf increased quickly, and the differences of color and nitrogen content between the fourth leaf and the three top leaves decreased. So, the fourth leaf was an ideal indication of plant nutrition status. In addition, color difference between the fourth and the third leaf from the top was highly related to the plant nitrogen content regardless of the variety and development stage. Therefore, color difference between the fourth and the third leaf could be widely used for diagnosis of plant nutrition. Results also indicated that the minimized color difference between the fourth and the third leaf at the critical effective tillering, the emergence of the second leaf from the top, and the heading was the symbol of high yield. Plant nitrogen content of 27 g kg-1 DW for japonica rice and 25 g kg-1 DW for indica were the critical nitrogen concentrations.
基金financial support from the National Key Research and Development Program of China (2017YFC0403303)the Shanxi Agricultural University of Science and Technology Innovation Fund, China (2016YJ07 and 2016007)
文摘Excessive use of nitrogen (N) fertilizers in agricultural systems increases the cost of production and risk of environmental pollution. Therefore, determination of optimum N requirements for plant growth is necessary. Previous studies mostly established critical N dilution curves based on aboveground dry matter (DM) or leaf dry matter (LDM) and stem dry matter (SDM), to diagnose the N nutrition status of the whole plant. As these methods are time consuming, we investigated the more rapidly determined leaf area index (LAI) method to establish the critical nitrogen (Nc) dilution curve, and the curve was used to diagnose plant N status for winter wheat in Guanzhong Plain in Northwest China. Field experiments were conducted using four N fertilization levels (0, 105, 210 and 315 kg ha?1) applied to six wheat cultivars in the 2013–2014 and 2014–2015 growing seasons. LAI, DM, plant N concentration (PNC) and grain yield were determined. Data points from four cultivars were used for establishing the Nc curve and data points from the remaining two cultivars were used for validating the curve. The Nc dilution curve was validated for N-limiting and non-N-limiting growth conditions and there was good agreement between estimated and observed values. The N nutrition index (NNI) ranged from 0.41 to 1.25 and the accumulated plant N deficit (Nand) ranged from 60.38 to –17.92 kg ha?1 during the growing season. The relative grain yield was significantly affected by NNI and was adequately described with a parabolic function. The Nc curve based on LAI can be adopted as an alternative and more rapid approach to diagnose plant N status to support N fertilization decisions during the vegetative growth of winter wheat in Guanzhong Plain in Northwest China.
基金supported by the Special Program for Agriculture Science and Technology from the Ministry of Agriculture of China (201303109)the National Key Research & Development Program of China (2016YFD0300604+3 种基金 2016YFD0200602)the Fundamental Research Funds for the Central Universities,China (262201602)the Priority Academic Program Development of Jiangsu Higher Education Institutions of China (PAPD)the 111 Project of China (B16026)
文摘Leaf area index （LAI） is used for crop growth monitoring in agronomic research, and is promising to diagnose the nitrogen （N） status of crops. This study was conducted to develop appropriate LAI-based N diagnostic models in irrigated lowland rice. Four field experiments were carried out in Jiangsu Province of East China from 2009 to 2014. Different N application rates and plant densities were used to generate contrasting conditions of N availability or population densities in rice. LAI was determined by LI-3000, and estimated indirectly by LAI-2000 during vegetative growth period. Group and individual plant characters （e.g., tiller number （TN） and plant height （H）） were investigated simultaneously. Two N indicators of plant N accumulation （NA） and N nutrition index （NNI） were measured as well. A calibration equation （LAI=1.7787LAI2o00-0.8816, R2=0.870＂） was developed for LAI-2000. The linear regression analysis showed a significant relationship between NA and actual LAI （R2=0.863^＊＊）. For the NNI, the relative LAI （R2=0.808-） was a relatively unbiased variable in the regression than the LAI （R^2=0.33^＊＊）. The results were used to formulate two LAI-based N diagnostic models for irrigated lowland rice （NA=29.778LAI-5.9397; NNI=0.7705RLAI＋0.2764）. Finally, a simple LAI deterministic model was developed to estimate the actual LAI using the characters of TN and H （LAI=-0.3375（THxHx0.01）2＋3.665（TH×H×0.01）-1.8249, R2=0.875＊＊）. With these models, the N status of rice can be diagnosed conveniently in the field.
文摘A field trial comprising 3 rice varieties (NDR-359, Sarju 52, HUBR 2-1) and 4 LCC scores (≤ 2, ≤ 3, ≤ 4, ≤ 5) along with the recommended dose of N was conducted in a split plot design to calibrate the LCC for nitrogen requirement of rice. Maximum grain yields of NDR-359, Sarju 52 at LCC ≤ 5 and HUBR 2-1 at LCC ≤ 4 were found to be 47.10, 40.66 and 36.04 q/ha respectively. The critical LCC score for real time nitrogen requirement for NDR 359 and Sarju 52 was found to be ≤ 5, while for HUBR 2-1 it was ≤ 4. Agronomic and recovery efficiency of nitrogen also followed the same trend. In the functional relationship between SPAD value and LCC score, while it was linear in NDR-359 and Sarju 52, for HUBR 2-1 it was quadratic. Further a positive correlation between SPAD values and LCC score was observed in all the 3 varieties.
基金supported by the Agricultural Science and Technology Achievement Transformation Fund of Science and Technology Ministry of China(Grant No. 2010GB2B000077)the Special Fund forAgro-scientific Research in the Public Interest of theministry of Agriculture of China (Grant No.201203026)
文摘The response of transcription factor genes to low nitrogen stress was studied to provide molecular basis for improving the absorption and utilization efficiency of nitrogen fertilizer in rice. The agilent rice genome arrays were used to study the varied expression of transcription factor genes in two rice varieties （SN 196 and Toyonishhiki） with different chlorophyll contents under low nitrogen stress. The results showed that a total of 53 transcription factor genes （35 down-regulated and 18 up-regulated genes at the transcription level） in flag leaves of super-green rice SN196 and 27 transcription factor genes （21 down-regulated and 6 up-regulated genes at the transcription level） in flag leaves of Toyonishiki were affected by low nitrogen stress. Among those nitrogen-responsive genes, 48 transcription factor genes in SN196 and 22 in Toyonishiki were variety-specific. There were overlapped transcription factor genes responded to low nitrogen stress between SN196 and Toyonishiki, with 1 up-regulated and 4 down-regulated at the transcription level. Distributions of low nitrogen responsive genes on chromosomes were different in two rice varieties.
基金funded by the National Key Research and Development Program of China(2022YFD1900401)the Chinese Universities Scientific Fund(2452020018)。
文摘Remote sensing has been increasingly used for precision nitrogen management to assess the plant nitrogen status in a spatial and real-time manner.The nitrogen nutrition index(NNI)can quantitatively describe the nitrogen status of crops.Nevertheless,the NNI diagnosis for cotton with unmanned aerial vehicle(UAV)multispectral images has not been evaluated yet.This study aimed to evaluate the performance of three machine learning models,i.e.,support vector machine(SVM),back propagation neural network(BPNN),and extreme gradient boosting(XGB)for predicting canopy nitrogen weight and NNI of cotton over the whole growing season from UAV images.The results indicated that the models performed better when the top 15 vegetation indices were used as input variables based on their correlation ranking with nitrogen weight and NNI.The XGB model performed the best among the three models in predicting nitrogen weight.The prediction accuracy of nitrogen weight at the upper half-leaf level(R^(2)=0.89,RMSE=0.68 g m^(-2),RE=14.62%for calibration and R^(2)=0.83,RMSE=1.08 g m^(-2),RE=19.71%for validation)was much better than that at the all-leaf level(R^(2)=0.73,RMSE=2.20 g m^(-2),RE=26.70%for calibration and R^(2)=0.70,RMSE=2.48 g m^(-2),RE=31.49%for validation)and at the plant level(R^(2)=0.66,RMSE=4.46 g m^(-2),RE=30.96%for calibration and R^(2)=0.63,RMSE=3.69 g m^(-2),RE=24.81%for validation).Similarly,the XGB model(R^(2)=0.65,RMSE=0.09,RE=8.59%for calibration and R^(2)=0.63,RMSE=0.09,RE=8.87%for validation)also outperformed the SVM model(R^(2)=0.62,RMSE=0.10,RE=7.92%for calibration and R^(2)=0.60,RMSE=0.09,RE=8.03%for validation)and BPNN model(R^(2)=0.64,RMSE=0.09,RE=9.24%for calibration and R^(2)=0.62,RMSE=0.09,RE=8.38%for validation)in predicting NNI.The NNI predictive map generated from the optimal XGB model can intuitively diagnose the spatial distribution and dynamics of nitrogen nutrition in cotton fields,which can help farmers implement precise cotton nitrogen management in a timely and accurate manner.
基金The work was financially supported by the National Natural Science Foundation of China(No.31971636)Yong Elite Scientists Sponsorship Program by CAST(2018QNRC001)the Fundamental Research Fund for the Central Universities(2572018CG03).
文摘Investigating the effects of ontogenetic stage and leaf age on leaf traits is important for understanding the utilization and distribution of resources in the process of plant growth.However,few studies have been conducted to show how traits and trait-trait relationships change across a range of ontogenetic stage and leaf age for evergreen coniferous species.We divided 67 Pinus koraiensis Sieb.et Zucc.of various sizes(0.3-100 cm diameter at breast height,DBH)into four ontogenetic stages,i.e.,young trees,middle-aged trees,mature trees and over-mature trees,and measured the leaf mass per area(LMA),leaf dry matter content(LDMC),and mass-based leaf nitrogen content(N)and phosphorus content(P)of each leaf age group for each sampled tree.One-way analysis of variance(ANOVA)was used to describe the variation in leaf traits by ontogenetic stage and leaf age.The standardized major axis method was used to explore the effects of ontogenetic stage and leaf age on trait-trait relationships.We found that LMA and LDMC increased significantly and N and P decreased significantly with increases in the ontogenetic stage and leaf age.Most trait-trait relationships were consistent with the leaf economic spectrum(LES)at a global scale.Among them,leaf N content and LDMC showed a significant negative correlation,leaf N and P contents showed a significant positive correlation,and the absolute value of the slopes of the trait-trait relationships showed a gradually increasing trend with an increasing ontogenetic stage.LMA and LDMC showed a significant positive correlation,and the slopes of the trait-trait relationships showed a gradually decreasing trend with leaf age.Additionally,there were no significant relationships between leaf N content and LMA in most groups,which is contrary to the expectation of the LES.Overall,in the early ontogenetic stages and leaf ages,the leaf traits tend to be related to a"low investment-quick returns"resource strategy.In contrast,in the late ontogenetic stages and leaf ages,they tend to be related to a"high investment-slow returns"resource strategy.Our results reflect the optimal allocation of resources in Pinus koraiensis according to its functional needs during tree and leaf ontogeny.
基金funded by the National Natural Science Foundation of China (30771277, 30771279)
文摘Nitrogen（N） fertilizer experiments were conducted to investigate the optimal subtending leaf N concentration for fiber strength,and its relationship with activities of key enzymes（sucrose synthase and β-1,3-glucanase） and contents of key constituents（sucrose and β-1,3-glucan） involved in fiber strength development in the lower,middle and upper fruiting branches of two cotton cultivars（Kemian 1 and NuCOTN 33B）.For each sampling day,we simulated changes in fiber strength,activity of sucrose synthase and β-1,3-glucanase and levels of sucrose and β-1,3-glucan in response to leaf N concentration using quadratic eqs.;the optimal subtending leaf N concentrations were deduced from the eqs.For the same fruiting branch,changes in the optimal leaf N concentration based on fiber development（DPA） could be simulated by power functions.From these functions,the average optimal subtending leaf N concentrations during fiber development for the cultivar,Kemian 1,were 2.84% in the lower fruiting branches,3.15% in the middle fruiting branches and 3.04% in the upper fruiting branches.For the cultivar,NuCOTN 33B,the optimum concentrations were 3.04,3.28 and 3.18% in the lower,middle and upper fruiting branches,respectively.This quantification may be used as a monitoring index for evaluating fiber strength and its related key enzymes and constituents during fiber formation at the lower,middle and upper fruiting branches.
