Unveiling the adaptation strategies of woody plants in remnant forest patches to spatiotemporal urban expansion through leaf trait networks

Background:With the expansion of urban areas,the remnants of forested areas play a crucial role in preserving biodiversity in urban environments.This study aimed to explore the impact of spatiotemporal urban expansion on the networks of leaf traits in woody plants within remnant forest patches,thereby enhancing our understanding of plant adaptive strategies and contributing to the conservation of urban biodiversity.Methods:Our study examined woody plants within 120 sample plots across 15 remnant forest patches in Guiyang,China.We constructed leaf trait networks (LTNs) based on 26 anatomical,structural,and compositional leaf traits and assessed the effects of the spatiotemporal dynamics of urban expansion on these LTNs.Results and conclusions:Our results indicate that shrubs within these patches have greater average path lengths and diameters than trees.With increasing urban expansion intensity,we observed a rise in the edge density of the LTN-shrubs.Additionally,modularity within the networks of shrubs decreased as road density and urban expansion intensity increased,and increases in the average path length and average clustering coefficient for shrubs were observed with a rise in the composite terrain complexity index.Notably,patches subjected to‘leapfrog’expansion exhibited greater average patch length and diameter than those experiencing edge growth.Stomatal traits were found to have high degree centrality within these networks,signifying their substantial contribution to multiple functions.In urban remnant forests,shrubs bolster their resilience to variable environmental pressures by augmenting the complexity of their leaf trait networks.

AI-Driven Pattern Recognition in Medicinal Plants: A Comprehensive Review and Comparative Analysis

The pharmaceutical industry increasingly values medicinal plants due to their perceived safety and costeffectiveness compared to modern drugs.Throughout the extensive history of medicinal plant usage,various plant parts,including flowers,leaves,and roots,have been acknowledged for their healing properties and employed in plant identification.Leaf images,however,stand out as the preferred and easily accessible source of information.Manual plant identification by plant taxonomists is intricate,time-consuming,and prone to errors,relying heavily on human perception.Artificial intelligence(AI)techniques offer a solution by automating plant recognition processes.This study thoroughly examines cutting-edge AI approaches for leaf image-based plant identification,drawing insights from literature across renowned repositories.This paper critically summarizes relevant literature based on AI algorithms,extracted features,and results achieved.Additionally,it analyzes extensively used datasets in automated plant classification research.It also offers deep insights into implemented techniques and methods employed for medicinal plant recognition.Moreover,this rigorous review study discusses opportunities and challenges in employing these AI-based approaches.Furthermore,in-depth statistical findings and lessons learned from this survey are highlighted with novel research areas with the aim of offering insights to the readers and motivating new research directions.This review is expected to serve as a foundational resource for future researchers in the field of AI-based identification of medicinal plants.

Research Progress on Leaf Anatomical Structures of Plants Under Drought Stress

Plants usually suffer drought stress during their growth process. As the photosynthetic activity center of plants, the leaf is the most sensitive organ under drought stress. In order to support the research on drought resistance of higher plants, this study reviewed the adaptation response and damage performance of epidermal structure, palisade tissue and spongy tissue, thickness, veins and stomata of plant leaves under drought stress.

ORYZA SATIVA SPOTTED-LEAF 41(OsSPL41) Negatively Regulates Plant Immunity in Rice

Identification of immunity-associated leucine-rich repeat receptor-like protein kinases(LRR-RLK) is critical to elucidate the LRR-RLK mediated mechanism of plant immunity.Here,we reported the map-based cloning of a novel rice SPOTTED-LEAF 41(Os SPL41) encoding a putative LRR-RLK protein(Os LRR-RLK41/Os SPL41) that regulated disease responses to the bacterial blight pathogen Xanthomonas oryzae pv.oryzae(Xoo).An 8-bp insertion at position 865 bp in a mutant spotted-leaf 41(spl41) allele led to the formation of purple-brown lesions on leaves.Functional complementation by the wild type allele(Os SPL41) can rescue the mutant phenotype,and the complementary lines showed similar performance to wild type in a number of agronomic,physiological and molecular indices.Os SPL41 was constitutively expressed in all tissues tested,and Os SPL41 contains a typical transmembrane domain critical for its localization to the cell membrane.The mutant exhibited an enhanced level of resistance to Xoo in companion of markedly up-regulated expression of pathogenesis-related genes such as Os PR10a,Os PAL1 and Os NPR1,while the level of salicylic acid was significantly increased in spl41.In contrast,the over-expression lines exhibited a reduced level of H_(2)O_(2) and were much susceptible to Xoo with down-regulated expression of pathogenesis-related genes.These results suggested that Os SPL41 might negatively regulate plant immunity through the salicylic acid signaling pathway in rice.

Physicochemical characteristics of ambient particles settling upon leaf surfaces of urban plants in Beijing

Particulate pollution is a serious health problem throughout the world, exacerbating a wide range of respiratory and vascular illnesses in urban areas. Urban plants play an important role in reducing particulate pollution. Physicochemical characteristics of ambient particles settling upon leaf surfaces of eleven roadside plants at four sites of Beijing were studies. Results showed that density of particles on the leaf surfaces greatly varied with plant species and traffic condition. Fraxinus chiuensis, Sophora japonica Ailanthus altissima, Syringa oblata and Prunus persica, had larger densities of particles among the tall species. Due to resuspension of road dust, the densities of particles of Euonymus japonicns and Parthenocissus quinquefolia with low sampling height were 2-35 times to other taller tree species. For test plant species, micro-roughness of leaf surfaces and density of particles showed a close correlation. In general, the larger micro-roughness of leaf surfaces is, the larger density of particles is. Particles settling upon leaf surfaces were dominantly PM30 （particulate matter less than 10 μm in aerodynamic diameter; 98.4%） and PM2.5 （particulate matter less than 2.5 μm in aerodynamic diameter; 64.2%） which were closely relative to human health. Constant elements of particles were C, O, K, Ca, Si, Al, Mg, Na, Fe, S, Cl and minerals with higher content were SiO2, CaCO3, CaMg（CO3）2, NaCI and 2CASO4. H2O, SiO2. CaCO3 and CaMg（CO3）2 mainly came from resuspension of road dust. 2CaSO4. H2O was produced by the reaction between CaCO3 derived from earth dust or industrial emission and SO2, H2SO4 or sulfate. NaCl was derived from sea salt.

Changes in leaf vein traits among vein types of alpine grassland plants on the Tibetan Plateau

Vein traits influence photosynthesis and drought resistance and are sensitive to climate change.It is unclear whether vein traits,similar to other leaf traits,have obvious regional characteristics and covariance with other leaf traits,especially in Tibetan Plateau grasslands.We collected 66 species from 37 sites in late July of 2012 and early August of 2013 to investigate leaf vein traits and their relationships with other leaf traits in comparison with the available global database data and to elucidate vein investment of plants with different vein types.The average vein length per area(VLA)of plants in the Tibetan Plateau was within the range of the global dataset,and the relationships among vein traits and other leaf traits of alpine plants were consistent with the global models.The VLAs of parallel-veined grasses and pinnateveined forbs were significantly lower and higher than the global mean value,respectively.The leaf mass perarea and total nitrogen content of parallel-veined grasses were significantly lower and higher,respectively,than the global mean values;the opposite was observed in pinnate-veined forbs.The parallel-veined grasses exhibited almost a four-fold higher vein biomass investment(i.e.,vein mass per leaf mass)than pinnate-veined forbs in the same region.The average VLA and its relationships with other leaf traits of the alpine grassland plants on the Tibetan Plateau had no regional characteristics,suggesting a convergence in plant leaf functioning.Plants with different leaf types differ in their adaptation strategies to plateau environments,and this may relate to biomass investment into leaf veins.Our study fills the gap with regard to vein density in alpine grassland species and provides a new perspective for understanding plant physiology and ecology by calculating and comparing the proportion of vein investment among different vein types.

Nutrient resorption and its influencing factors of typical desert plants in different habitats on the northern margin of the Tarim Basin, China

The resorption of nutrients from senescent leaves allows plants to conserve and recycle nutrients. To explore the adaptation strategies of desert plants to nutrient-limited environments, we selected four typical desert plants(Populus euphratica Oliv., Tamarix ramosissima Ledeb., Glycyrrhiza inflata Batal., and Alhagi camelorum Fisch.) growing in the desert area of the northern margin of the Tarim Basin,China. The contents of nitrogen(N), phosphorus(P), potassium(K), calcium(Ca), magnesium(Mg), and Ferrum(Fe) in the leaves of these four typical desert plants and their resorption characteristics were analyzed. The relationship of nutrient resorption efficiency with leaf functional traits and soil physical-chemical properties in two different habitats(saline-alkali land and sandy land) was discussed.The results showed that the four plants resorbed most of the elements. Ca was enriched in the leaves of P.euphratica, G. inflate, and A. camelorum;Mg was enriched in the leaves of G. inflata;and Fe was enriched in the leaves of the four plants. The results of the redundancy analysis showed that leaf thickness, soil electrical conductivity, and soil P content were the major factors affecting the nutrient resorption efficiency of the four plants. Leaf thickness was negatively correlated with N resorption efficiency(NRE),P resorption efficiency, and Fe resorption efficiency;soil electrical conductivity was positively correlated with the resorption efficiency of most elements;and soil P content was negatively correlated with the resorption efficiency of most elements in the plant leaves. The results showed that soil physical-chemical properties and soil nutrient contents had an important impact on the nutrient resorption of plant leaves.The same species growing in different habitats also differed in their resorption of different elements. The soil environment of plants and the biological characteristics of plant leaves affected the resorption of nutrient elements in different plants. The purpose of this study is to provide small-scale data support for the protection of ecosystems in nutrient-deficient areas by studying leaf functional strategies and nutrient conservation mechanisms of several typical desert plants.

A Hybrid Deep Learning Approach to Classify the Plant Leaf Species

Many plant species have a startling degree of morphological similarity,making it difficult to split and categorize them reliably.Unknown plant species can be challenging to classify and segment using deep learning.While using deep learning architectures has helped improve classification accuracy,the resulting models often need to be more flexible and require a large dataset to train.For the sake of taxonomy,this research proposes a hybrid method for categorizing guava,potato,and java plumleaves.Two new approaches are used to formthe hybridmodel suggested here.The guava,potato,and java plum plant species have been successfully segmented using the first model built on the MobileNetV2-UNET architecture.As a second model,we use a Plant Species Detection Stacking Ensemble Deep Learning Model(PSD-SE-DLM)to identify potatoes,java plums,and guava.The proposed models were trained using data collected in Punjab,Pakistan,consisting of images of healthy and sick leaves from guava,java plum,and potatoes.These datasets are known as PLSD and PLSSD.Accuracy levels of 99.84%and 96.38%were achieved for the suggested PSD-SE-DLM and MobileNetV2-UNET models,respectively.

Influence of Planting Date on the Incidence and Severity of Leaf Spot Disease in Telfairia occidentalis Hook f.

Telfairia occidentalis Hook f. is attacked by a destructive fungal pathogen Epicoccum sorghinum which causes leaf spot disease in the field. In Came-roon, this critically important seed and leaf vegetable is predominantly culti-vated under natural environmental conditions. An experiment was conducted in 2019 and 2020 during the long and short rainy seasons in Santchou to de-termine the influence of planting dates between seasons on the incidence and severity of leaf spot disease. The design used was a 2 by 4 factorial random-ized complete block design with three replications and four sowing dates. Data for disease incidence and severity documented fortnightly, were submitted to analysis of variance using SPSS version 23, and the means were separated by Duncan’s multiple range test (DMRT) at a 95% confidence interval. Statistical analysis revealed that the long rainy season registered a significantly (p p < 0.05) disease incidences and severities to other planting dates investi-gated. We established that the first three planting dates in the long rainy season could be a management practice to reduce disease prevalence.

Extremely thin but very robust:Surprising cryptogam trait combinations at the end of the leaf economics spectrum

Leaf economics spectrum(LES)describes the fundamental trade-offs between leaf structural,chemical,and physiological investments.Generally,structurally robust thick leaves with high leaf dry mass per unit area(LMA)exhibit lower photosynthetic capacity per dry mass(Amass).Paradoxically,“soft and thinleaved”mosses and spikemosses have very low Amass,but due to minute-size foliage elements,their LMA and its components,leaf thickness(LT)and density(LD),have not been systematically estimated.Here,we characterized LES and associated traits in cryptogams in unprecedented details,covering five evolutionarily different lineages.We found that mosses and spikemosses had the lowest LMA and LT values ever measured for terrestrial plants.Across a broad range of species from different lineages,Amass and LD were negatively correlated.In contrast,Amass was only related to LMA when LMA was greater than 14 g cm^(-2).In fact,low Amass reflected high LD and cell wall thickness in the studied cryptogams.We conclude that evolutionarily old plant lineages attained poorly differentiated,ultrathin mesophyll by increasing LD.Across plant lineages,LD,not LMA,is the trait that represents the trade-off between leaf robustness and physiology in the LES.

Dominance of rock exposure and soil depth in leaf trait networks outweighs soil quality in karst limestone and dolomite habitats

Leaf trait networks(LTNs)visualize the intricate linkages reflecting plant trait-functional coordination.Typical karst vegetation,developed from lithological dolomite and limestone,generally exhibits differential communities,possibly due to habitat rock exposure,soil depth,and soil physicochemical properties variations,leading to a shift from plant trait variation to functional linkages.However,how soil and habitat quality affect the differentiation of leaf trait networks remains unclear.LTNs were constructed for typical dolomite and limestone habitats by analyzing twenty-one woody plant leaf traits across fifty-six forest subplots in karst mountains.The differences between dolomite and limestone LTNs were compared using network parameters.The network association of soil and habitat quality was analyzed using redundancy analysis(RDA),Mantle's test,and a random forest model.The limestone LTN exhibited significantly higher edge density with lower diameter and average path length when compared to the dolomite LTN.It indicates LTN differentiation,with the limestone network displaying a more compact architecture and higher connectivity than the dolomite network.The specific leaf phosphorus and leaf nitrogen contents of dolomite LTN,as well as the leaf mass and leaf carbon contents of limestone LTN,significantly contributed to network degree and closeness,serving as crucial node traits regulating LTN connectedness.Additionally,both habitat LTNs significantly correlated with soil nitrogen and phosphorus,stoichiometric ratios,pH,and organic carbon,as well as soil depth and rock exposure rates,with soil depth and rock exposure showing greater relative importance.Soil depth and rock exposure dominate trait network differentiation,with the limestone habitat exhibiting a more compact network architecture than the dolomite habitat.

Free proline accumulation in rice plants under different leaf water potential

Seedlings of drought-tolerance rice varieties Han 501and Han A03,and the drought sensitive varietiesNanjing 11 and Yanjing 2 were raised in a paddyfield and transplanted into pots at the age of 8leaves.Water stress started at the tillering stage byholding water from 0 MPa of the soil water potentialin pots till the leaves showed seriously wilting.

Investigation and Application of Colored-leaf Plants in Tibet

For the quantitative analysis of colored-leaf plants in Tibet,the five-point sampling method is used for stratified investigation of garden plant communities in Tibet.(i)There are a total of 46 families,76 genera and 110 species of garden colored-leaf plants in Tibet,including 56 kinds of trees,40 kinds of bushes,9 kinds of herbs,4 kinds of vines and 1 kind of bamboo.There are too few colored-leaf herbs and bamboos,and there is a serious imbalance between evergreen and deciduous trees,between coniferous and broad leaved forests.(ii)The most widely applied families include Rosaceae(26),Salicaceae(12),Fabaceae(6),Aceraceae(5),Oleaceae(4)and Elaeagnaceae(4),accounting for 23.64%,10.91%,5.46%,4.55%,3.64% and 3.64% of the investigated colored-leaf plants,respectively.(iii)In terms of color,there are 55 kinds of red plants,43 kinds of yellow plants and 12 kinds of plants with other colors,accounting for 50.00%,39.09%and 10.91% of colored-leaf plants,respectively.There are 9 kinds of spring color leaf plants,63 kinds of autumn color leaf plants,29 kinds of constant color leaf plants,7 kinds of double color leaf plants and 2 kinds of spot color leaf plants,accounting for 8.18%,57.27%,26.36%,6.36% and 1.82% of colored-leaf plants,respectively,indicating that it is dominated by autumn color leaf and constant color leaf plants.(iv)In terms of importance value of trees,the top two are Salix alba(37.623)and Prunus cerasifera f.atropurpurea(26.063); in terms of importance value of bushes,the top three are Ligustrum × vicaryi Hort(22.577),Berberis thunbergii‘atropurpurea Nana'(18.987)and Platycladus orientalis Franco cv.Sieboldii(10.529); in terms of importance value of herbs,the top two are Taraxacum sherriffii(0.915)and Oxalis triangu laris cv.purpurea(0.326).(v)In terms of species abundance of colored-leaf plants,it is in the order of Nyingchi(94)> Lhasa(47)> Qamdo(43)> Shannan(34)> Xigaze(21)> Ali(7)> Nagqu(5).There are great differences between regions: it is highest in Nyingchi while it is lowest in Nagqu.Based on the main problems in the application of colored-leaf plants in Tibet,this paper makes the corresponding recommendations.

Application of Colored-leaf Plants in Landscape Construction

With the gradual improvement of living standard, the public demands on landscaping have focused more on quality than on quantity, and plant furnishing has grown from singular green plants to colored-leaf plants with multiple layers. Confi guration of colored-leaf plants follows certain principles and patterns to enrich the beauty of plant landscaping, construct colorful urban green spaces, satisfy increasing application and aesthetic needs of the public, and reflect value of plant landscaping.

Quantity of plant leaf area on three major public squares in Kunming City, China

Regressive formulae to calculate the quantity of plant leaf area for 13 species of ornamental plants were set up based on investigation data of 30 species on 3 major public squares (Dongfeng square, Shengli square and Guandu square) in Kun-ming City, China, which were applied to calculate quantities of plant leaf area of these 13 species. The quantities of plant leaf area for the other 17 ornamental plant species on these squares were directly measured, and the total quantity of plant leaf area of each studied square was obtained individually. The results showed that the quantity of plant leaf area on Shengli square with ornamental plants structure composed of arbor tree species, shrub tree species and turf grass was highest among the three squares. It is believed that the design model of multi-storied vertical structure and proper tending of plant community could not only increase the quantity of plant leaf area, but also play an important role in generating ecological and landscaping benefits. Some corresponding suggestions were put forward on the basis of comprehensive analyses on the plant leaf area quantity of the three representative squares in Kunming urban area.

Leaf N and P stoichiometry of 57 plant species in the Karamori Mountain Ungulate Nature Reserve,Xinjiang,China

Nitrogen （N） and phosphorus （P） are the major nutrients that constrain plant growth and development, as well as the structure and function of ecosystems. Hence, leaf N and P patterns can contribute to a deep understanding of plant nutrient status, nutrient limitation type of ecosystems, plant life-history strategy and differentiation of functional groups. However, the status and pattern of leaf N and P stoichiometry in N-deficiency desert ecosystems remain unclear. Under this context, the leaf samples from 57 plant species in the Karamori Mountain Ungulate Nature Reserve, eastern Junggar Desert, China were investigated and the patterns and interrelations of leaf N and P were comparatively analyzed. The results showed that the average leaf N concentration, P concentration, and N：P ratio were 30.81 mg/g, 1.77 mg/g and 17.72, respectively. This study found that the leaf N concentration and N：P ratio were significantly higher than those of studies conducted at global, national and regional scales; however, the leaf P concentration was at moderate level. Leaf N concentration was allometrically correlated with leaf P and N：P ratio across all species. Leaf N, P concentrations and N：P ratio differed to a certain extent among plant functional groups. C4 plants and shrubs, particularly shrubs with assimilative branches, showed an obviously lower P concentration than those of C3 plants, herbs and shrubs without assimilative branches. Shrubs with assimilative branches also had lower N concentration. Fabaceae plants had the highest leaf N, P concentrations （as well as Asteraceae） and N：P ratio; other families had a similar N, P-stoichiometry. The soil in this study was characterized by a lack of N （total N：P ratio was 0.605）, but had high N availability compared with P （i.e. the available N：P ratio was 1.86）. This might explain why plant leaves had high N concentration （leaf N：P ratio〉16）. In conclusion, the desert plants in the extreme environment in this study have formed their intrinsic and special stoichiometric characteristics in relation to their life-history strategy.

Differences in leaf functional traits between exotic and native Compositae plant species

This study aims to determine the differences in leaf functional traits and phenotypic plasticity of leaf functional traits between exotic and native Compositae plant species. Leaf width of exotic plants was significantly lower than that of native species. Leaf length, specific leaf area(SLA), single-leaf wet and dry weights, leaf moisture, and leaf thickness of exotic plants were also lower than those of native species but not significantly. The leaf shape index of exotic plants was higher than that of native species but not significantly. This implies that the relatively low leaf construction cost for exotic plants may play an important role in the success of their invasions. The higher leaf shape index and lower leaf width of exotic plants can enhance the efficiency of resource capture(especially sunlight capture) via adjustments to leaf shape and size, thereby increasing the survival of exotic plants. The plasticity indices of single-leaf wet weight and leaf thickness of exotic plants were significantly lower than those of native species. The lower phenotypic plasticity of single-leaf wet weight and leaf thickness of exotic plants may be the result of a cost to plasticity. That is, if the plasticity is too high, the fitness of plant species might be reduced sharply under unfavorable environments. Thus, lower plasticity of leaf functional traits may compensate for the negative impact of adverse environments and stabilize leaf construction costs for exotic plants. Moreover, reduced phenotypic plasticity might be one of the key competitive strategies by which exotic plants successfully invade new habitats. Overall, exotic plants did not always exhibit higher values of leaf functional traits or increased phenotypic plasticity of leaf functional traits compared with native species.

Seedling and adult plant resistance to leaf rust in 46 Chinese bread wheat landraces and 39 wheat lines with known Lr genes

Wheat leaf rust,caused by Puccinia triticina(Pt),is an important foliar disease that has an important influence on wheat yield.The most economic,safe and effective way to control the disease is growing resistant cultivars.In the present study,a total of 46 wheat landraces and 34 wheat lines with known Lr(leaf rust resistance)genes were inoculated with 16Pt pathotypes for postulating seedling resistance gene(s)in the greenhouse.These cultivars and five wheat differential lines with adult plant resistance(APR)genes(Lr12,Lr22b,Lr34,Lr35 and Lr37)were also evaluated for identification of slow rusting resistance in the field trials in Baoding,Hebei Province of China in the 2014–2015 and 2015–2016 cropping seasons.Furthermore,10 functional molecular markers closely linked to 10 known Lr genes were used to detect all the wheat genotypes.Results showed that most of the landraces were susceptible to most of the Pt pathotypes at seedling stage.Nonetheless,Lr1 was detected only in Hongtangliangmai.The field experimental test of the two environments showed that 38 landraces showed slow rusting resistance.Seven cultivars possessed Lr34 but none of the landraces contained Lr37 and Lr46.Lr genes namely,Lr9,Lr19,Lr24,Lr28,Lr29,Lr47,Lr51 and Lr53 were effective at the whole plant stage.Lr18,Lr36 and Lr45 had lost resistance to part of pathotypes at the seedling stage but showed high resistance at the adult plant stage.Lr34 as a slowing rusting gene showed good resistance in the field.Four race-specific APR genes Lr12,Lr13,Lr35 and Lr37 conferred good resistance in the field experiments.Seven race-specific genes,Lr2b,Lr2c,Lr11,Lr16,Lr26,Lr33 and LrB had lost resistance.The 38 landraces showed slow rusting resistance to wheat leaf rust can be used as resistance resources for wheat resistance breeding in China.

Artificial Neural Network to Predict Leaf Population Chlorophyll Content from Cotton Plant Images

Leaf population chlorophyll content in a population of crops, if obtained in a timely manner, served as a key indicator for growth management and diseases diagnosis. In this paper, a three-layer multilayer perceptron （MLP） artificial neural network （ANN） based prediction system was presented for predicting the leaf population chlorophyll content from the cotton plant images. As the training of this prediction system relied heavily on how well those leaf green pixels were separated from background noises in cotton plant images, a global thresholding algorithm and an omnidirectional scan noise filtering coupled with the hue histogram statistic method were designed for leaf green pixel extraction. With the obtained leaf green pixels, the system training was carried out by applying a back propagation algorithm. The proposed system was tested to predict the chlorophyll content from the cotton plant images. The results using the proposed system were in sound agreement with those obtained by the destructive method. The average prediction relative error for the chlorophyll density （μg cm^-2） in the 17 testing images was 8.41%.

Increasing photosynthetic performance and post-silking N uptake by moderate decreasing leaf source of maize under high planting density

To date,little attention has been paid to the effects of leaf source reduction on photosynthetic matter production,root function and post-silking N uptake characteristics at different planting densities.In a 2-year field experiment,Xianyu 335,a widely released hybrid in China,was planted at 60 000 plants ha^(–1 )(conventional planting density,CD) and 90 000 plants ha^(–1) (high planting density,HD),respectively.Until all the filaments protruded from the ear,at which point the plants were subjected to the removal of 1/2 (T1),1/3 (T2) and 1/4 (T3) each leaf length per plant,no leaf removal served as the control(CK).We evaluated the leaf source reduction on canopy photosynthetic matter production and N accumulation of different planting densities.Under CD,decreasing leaf source markedly decreased photosynthetic rate (P_(n)),effective quantum yield of photosystem II (ΦPSII) and the maximal efficiency of photosystem II photochemistry (F_(v)/F_(m)) at grain filling stage,reduced post-silking dry matter accumulation,harvest index (HI),and the yield.Compared with the CK,the 2-year average yields of T1,T2 and T3 treatments decreased by 35.4,23.8 and 8.3%,respectively.Meanwhile,decreasing leaf source reduced the root bleeding sap intensity,the content of soluble sugar in the bleeding sap,post-silking N uptake,and N accumulation in grain.The grain N accumulation in T1,T2 and T3 decreased by 26.7,16.5 and 12.8% compared with CK,respectively.Under HD,compared to other treatments,excising T3 markedly improved the leaf P_(n),ΦPSII and F_(v)/F_(m) at late-grain filling stage,increased the post-silking dry matter accumulation,HI and the grain yield.The yield of T3 was 9.2,35.7 and 20.1% higher than that of CK,T1 and T2 on average,respectively.The T3 treatment also increased the root bleeding sap intensity,the content of soluble sugar in the bleeding sap and post-silking N uptake and N accumulation in grain.Compared with CK,T1 and T2 treatments,the grain N accumulation in T3 increased by 13.1,40.9 and 25.2% on average,respectively.In addition,under the same source reduction treatment,the maize yield of HD was significantly higher than that of CD.Therefore,planting density should be increased in maize production for higher grain yield.Under HD,moderate decreasing leaf source improved photosynthetic performance and increased the post-silking dry matter accumulation and HI,and thus the grain yield.In addition,the improvement of photosynthetic performance improved the root function and promoted postsilking N uptake,which led to the increase of N accumulation in grain.