Stomatal dynamics are regulated by leaf hydraulic traits and guard cell anatomy in nine true mangrove species

Stomatal regulation is critical for mangroves to survive in the hyper-saline intertidal zone where water stress is severe and water availability is highly fluctuant.However,very little is known about the stomatal sensitivity to vapour pressure deficit(VPD)in mangroves,and its co-ordination with stomatal morphology and leaf hydraulic traits.We measured the stomatal response to a step increase in VPD in situ,stomatal anatomy,leaf hydraulic vulnerability and pressure-volume traits in nine true mangrove species of five families and collected the data of genome size.We aimed to answer two questions:(1)Does stomatal morphology influence stomatal dynamics in response to a high VPD in mangroves?with a consideration of possible influence of genome size on stomatal morphology;and(2)do leaf hydraulic traits influence stomatal sensitivity to VPD in mangroves?We found that the stomata of mangrove plants were highly sensitive to a step rise in VPD and the stomatal responses were directly affected by stomatal anatomy and hydraulic traits.Smaller,denser stomata was correlated with faster stomatal closure at high VPD across the species of Rhizophoraceae,and stomata size negatively and vein density positively correlated with genome size.Less negative leaf osmotic pressure at the full turgor(πo)was related to higher operating steady-state stomatal conductance(gs);and a higher leaf capacitance(Cleaf)and more embolism resistant leaf xylem were associated with slower stomatal responses to an increase in VPD.In addition,stomatal responsiveness to VPD was indirectly affected by leaf morphological traits,which were affected by site salinity and consequently leaf water status.Our results demonstrate that mangroves display a unique relationship between genome size,stomatal size and vein packing,and that stomatal responsiveness to VPD is regulated by leaf hydraulic traits and stomatal morphology.Our work provides a quantitative framework to better understand of stomatal regulation in mangroves in an environment with high salinity and dynamic water availability.

Gene expression profiles in early leaf of rice(Oryza sativa)and foxtail millet(Setaria italica)

Plant anatomy is patterned early during leaf development which suggests studying the spatial–temporal transcriptomes of primordia will help identify critical regulative and functional genes.We successfully isolated the leaf primordia tissues from the C3grass rice and the C4grass foxtail millet by laser capture microdissection(LCM)and studied the gene expression throughout leaf developmental stages.Our data analysis uncovered the conserved expression patterns of certain gene clusters both in rice and foxtail millet during leaf development.We revealed genes and transcription factors involved in vein formation,stomatal development,and suberin accumulation.We identified 79 candidate genes associated with functional regulation of C4anatomy formation.Screening phenotype of the candidate genes revealed that knock-out of a putative polar auxin transport related gene NAL1 resulted significantly reduced veinal space in rice leaf.Our present work provides a foundation for future analyses of genes with novel functions in grasses and their role in leaf development,in particular the role in leaves with a contrasting C3vs.C4biosynthetic pathway.

Leaf Morphology Genes SRL1 and RENL1 Co-Regulate Cellulose Synthesis and Affect Rice Drought Tolerance

The morphological development of rice(Oryza sativa L.)leaves is closely related to plant architecture,physiological activities,and resistance.However,it is unclear whether there is a co-regulatory relationship between the morphological development of leaves and adaptation to drought environment.In this study,a drought-sensitive,roll-enhanced,and narrow-leaf mutant(renl1)was induced from a semi-rolled leaf mutant(srl1)by ethyl methane sulfonate(EMS),which was obtained from Nipponbare(NPB)through EMS.Map-based cloning and functional validation showed that RENL1 encodes a cellulose synthase,allelic to NRL1/OsCLSD4.The RENL1 mutation resulted in reduced vascular bundles,vesicular cells,cellulose,and hemicellulose contents in cell walls,diminishing the water-holding capacity of leaves.In addition,the root system of the renl1 mutant was poorly developed and its ability to scavenge reactive oxygen species(ROS)was decreased,leading to an increase in ROS after drought stress.Meanwhile,genetic results showed that RENL1 and SRL1 synergistically regulated cell wall components.Our results revealed a theoretical basis for further elucidating the molecular regulation mechanism of cellulose on rice drought tolerance,and provided a new genetic resource for enhancing the synergistic regulation network of plant type and stress resistance,thereby realizing simultaneous improvement of multiple traits in rice.

A growth-regulating factor 7(GRF7)-mediated gene regulatory network promotes leaf growth and expansion in sugarcane

Knowledge of the function of growth-regulating factors(GRFs)in sugarcane(Saccharum officinarum and S.spontaneum)growth and development could assist breeders in selecting desirable plant architectures.However,limited information about GRFs is available in Saccharum due to their polyploidy.In this study,22 GRFs were identified in the two species and their conserved domains,gene structures,chromosome location,and synteny were characterized.GRF7 expression varied among tissues and responded to diurnal rhythm.SsGRF7-YFP was localized preferentially in the nucleus and appears to act as a transcriptional cofactor.SsGRF7 positively regulated the size and length of rice leaves,possibly by regulating cell size and plant hormones.Of seven potential transcription factors binding to the SsGRF7 promoter in S.spontaneum,four showed positive expression patterns,and two showed negative expression patterns relative to SsGRF7.

Litter production and leaf nutrient concentration and remobilization in response to climate seasonality in the central Amazon

Litterfall is the largest source of nutrients to for-est soils of tropical rainforests.However,variability in lit-terfall production,nutrient remobilization,and changes in leaf nutrient concentration with climate seasonality remain largely unknown for the central Amazon.This study meas-ured litterfall production,leaf nutrient remobilization,and leaf area index on a forest plateau in the central Amazon.Litterfall was measured at monthly intervals during 2014,while nitrogen,phosphorus,potassium,calcium and mag-nesium concentrations of leaf litter and canopy leaves were measured in the dry and rainy seasons,and remobilization rates determined.Leaf area index was also recorded in the dry and rainy seasons.Monthly litterfall varied from 33.2(in the rainy season)to 87.6 g m^(-2) in the dry season,while leaf area index increased slightly in the rainy season.Climatic seasonality had no effect on concentrations of nitrogen,calcium,and magnesium,whereas phosphorous and potassium responded to rainfall seasonality oppositely.While phosphorous increased,potassium decreased during the dry season.Over seasons,nitrogen,potassium,and phosphorous decreased in leaf litter;calcium increased in leaf litter,while magnesium remained unaffected with leaf aging.Regardless,the five nutrients had similar remobilization rates over the year.The absence of climate seasonality on nutrient remobilization suggests that the current length of the dry season does not alter nutrient remobilization rates but this may change as dry periods become more prolonged in the future due to climate change.

Synergistic effects of planting density and nitrogen fertilization on chlorophyll degradation and leaf senescence after silking in maize

Regulating planting density and nitrogen(N)fertilization could delay chlorophyll(Chl)degradation and leaf senescence in maize cultivars.This study measured changes in ear leaf green area(GLA_(ear)),Chl content,the activities of Chl a-degrading enzymes after silking,and the post-silking dry matter accumulation and grain yield under multiple planting densities and N fertilization rates.The dynamic change of GLA_(ear)after silking fitted to the logistic model,and the GLA_(ear) duration and the GLAearat 42 d after silking were affected mainly by the duration of the initial senescence period(T_(1))which was a key factor of the leaf senescence.The average chlorophyllase(CLH)activity was 8.3 times higher than pheophytinase activity and contributed most to the Chl content,indicating that CLH is a key enzyme for degrading Chl a in maize.Increasing density increased the CLH activity and decreased the Chl content,T1,GLAear,and GLA_(ear) duration.Under high density,appropriate N application reduced CLH activity,increased Chl content,prolonged T1,alleviated high-density-induced leaf senescence,and increased post-silking dry matter accumulation and grain yield.

Rice melatonin deficiency causes premature leaf senescence via DNA methylation regulation

In a study of DNA methylation changes in melatonin-deficient rice mutants,mutant plants showed premature leaf senescence during grain-filling and reduced grain yield.Melatonin deficiency led to transcriptional reprogramming,especially of genes involved in chlorophyll and carbon metabolism,redox regulation,and transcriptional regulation,during dark-induced leaf senescence.Hypomethylation of mCG and mCHG in the melatonin-deficient rice mutants was associated with the expression change of both protein-coding genes and transposable element-related genes.Changes in gene expression and DNA methylation in the melatonin-deficient mutants were compensated by exogenous application of melatonin.A decreased S-adenosyl-L-methionine level may have contributed to the DNA methylation variations in rice mutants of melatonin deficiency under dark conditions.

Rice ONAC016 promotes leaf senescence through abscisic acid signaling pathway involving OsNAP

Senescence-induced NAC(senNAC)TFs play a crucial role in senescence during the final stage of leaf development.In this study,we identified a rice senNAC,ONAC016,which functions as a positive regulator of leaf senescence.The expression of ONAC016 increased rapidly in rice leaves during the progression of dark-induced and natural senescence.The onac016-1 knockout mutant showed a delayed leaf yellowing phenotype,whereas the overexpression of ONAC016 accelerated leaf senescence.Notably,ONAC016 expression was upregulated by abscisic acid(ABA),and thus detached leaves of the onac016-1 mutant remained green much longer under ABA treatment.Quantitative RT-PCR analysis showed that ONAC016 upregulates the genes associated with chlorophyll degradation,senescence,and ABA signaling.Yeast one-hybrid and dual-luciferase assays revealed that ONAC016 binds directly to the promoter regions of OsNAP,a key gene involved in chlorophyll degradation and ABA-induced senescence.Taken together,these results suggest that ONAC016 plays an important role in promoting leaf senescence through the ABA signaling pathway involving OsNAP.

Olive Leaf Disease Detection via Wavelet Transform and Feature Fusion of Pre-Trained Deep Learning Models

Olive trees are susceptible to a variety of diseases that can cause significant crop damage and economic losses.Early detection of these diseases is essential for effective management.We propose a novel transformed wavelet,feature-fused,pre-trained deep learning model for detecting olive leaf diseases.The proposed model combines wavelet transforms with pre-trained deep-learning models to extract discriminative features from olive leaf images.The model has four main phases:preprocessing using data augmentation,three-level wavelet transformation,learning using pre-trained deep learning models,and a fused deep learning model.In the preprocessing phase,the image dataset is augmented using techniques such as resizing,rescaling,flipping,rotation,zooming,and contrasting.In wavelet transformation,the augmented images are decomposed into three frequency levels.Three pre-trained deep learning models,EfficientNet-B7,DenseNet-201,and ResNet-152-V2,are used in the learning phase.The models were trained using the approximate images of the third-level sub-band of the wavelet transform.In the fused phase,the fused model consists of a merge layer,three dense layers,and two dropout layers.The proposed model was evaluated using a dataset of images of healthy and infected olive leaves.It achieved an accuracy of 99.72%in the diagnosis of olive leaf diseases,which exceeds the accuracy of other methods reported in the literature.This finding suggests that our proposed method is a promising tool for the early detection of olive leaf diseases.

Structural elucidation of mulberry leaf oligosaccharide and its selective promotion of gut microbiota to alleviate type 2 diabetes mellitus

Two oligosaccharide fractions(MLO 2-1 and 2-2)were purified from enzymatic hydrolysate of mulberry leaf polysaccharide.The results of simulated digestion showed that MLO 2-2 was a digestible oligosaccharide,which could be degraded by human digestive juice;while MLO 2-1 possessed the non-digestible property in the upper gastrointestinal tract and performed the function by regulating the gut microbiota.Hence,MLO 2-1 was selected for the further analysis.The structure of MLO 2-1 was elucidated as follow:α-T-Glcp-(1→3)-β-Glcp-(1→5)-α-Araf-(1→5)-α-Araf-1→5)-α-Araf-(1→3)-α-(2-OAc)-Glcp-1.The in vitro fecal fermentation results showed that MLO 2-1 could modulate the composition of gut microbiota.Meanwhile,MLO 2-1 was effectively metabolized by fecal bacteria to produce lactate and short chain fatty acids,especially acetate and butyrate.The specific metabolic pathways of MLO 2-1 by gut microbiota were further illuminated.Gut microbiota analysis revealed that MLO 2-1 selectively promoted the growth of Ligilactobacillus murinus,a commensal bacterium presented a reduced level in T2DM mice.Animal experiments indicated that MLO 2-1 and L.murinus exhibited hypoglycemic activities.These results demonstrated that MLO 2-1 might alleviate T2DM by selectively accelerating the proliferation of L.murinus.

Identification, pathogenicity, and fungicide sensitivity of Eutiarosporella dactylidis associated with leaf blight on maize in China

Maize(Zea mays L.) is an economically vital grain crop that is cultivated worldwide. In 2011, a maize foliar disease was detected in Lingtai and Lintao counties in Gansu Province, China. The characteristic signs and symptoms of this disease include irregular chlorotic lesions on the tips and edges of infected leaves and black punctate fruiting bodies in dead leaf tissues. Given favourable environmental conditions, this disease spread to areas surrounding Gansu. In this study, infected leaves were collected from Gansu and Ningxia Hui Autonomous Region between 2018and 2020 to identify the disease-causing pathogen. Based on morphological features, pathogenicity tests, and multilocus phylogenetic analysis involving internal transcribed spacer(ITS), 18S small subunit rDNA(SSU), 28S large subunit rDNA(LSU), translation elongation factor 1-alpha(TEF), and β-tubulin(TUB) sequences, Eutiarosporella dactylidis was identified as the causative pathogen of this newly discovered leaf blight. Furthermore, an in vitro bioassay was conducted on representative strains using six fungicides, and both fludioxonil and carbendazim were found to significantly inhibit the mycelial growth of E. dactylidis. The results of this study provide a reference for the detection and management of Eutiarosporella leaf blight.

Metabolic profiles and morphological characteristics of leaf tips among different sweet potato(Ipomoea batatas Lam.)varieties

Sweet potato leaf tips have high nutritional value,and exploring the differences in the metabolic profiles of leaf tips among different sweet potato varieties can provide information to improve their qualities.In this study,a UPLC-Q-Exactive Orbitrap/MS-based untargeted metabolomics method was used to evaluate the metabolites in leaf tips of 32 sweet potato varieties.Three varieties with distinct overall metabolic profiles(A01,A02,and A03),two varieties with distinct profiles of phenolic acids(A20 and A18),and three varieties with distinct profiles of flavonoids(A05,A12,and A16)were identified.In addition,a total of 163 and 29 differentially expressed metabolites correlated with the color and leaf shape of sweet potato leaf tips,respectively,were identified through morphological characterization.Group comparison analysis of the phenotypic traits and a metabolite-phenotypic trait correlation analysis indicated that the color differences of sweet potato leaf tips were markedly associated with flavonoids.Also,the level of polyphenols was correlated with the leaf shape of sweet potato leaf tips,with lobed leaf types having higher levels of polyphenols than the entire leaf types.The findings on the metabolic profiles and differentially expressed metabolites associated with the morphology of sweet potato leaf tips can provide useful information for breeding sweet potato varieties with higher nutritional value.

Coffee Leaf Rust(Hemileia vastatrix)Disease in Coffee Plants and Perspectives by the Disease Control

Coffee Leaf Rust(CLR)is caused by Hemileia vastatrix in Coffea spp.It is one of the most dangerous phytopathogens for coffee plantations in terms of coffee productivity and coffee cup quality.In this review,we resume the problem of CLR in Mexico and the pathogenesis of H.vastatrix.The review abord plant-pathogen interactions which lead a compatible or incompatible interactions and result in CLR disease or resistance,respectively.The review abord Coffea spp.defense response pathways involved in H.vastatrix pathogenicity.Additionally,current measures to control H.vastatrix proliferation and germination were aborded focused on phytosanitary actions,and biological and chemical control.Finally,new trendlines to reduce the impact of CLR as nanoparticles and nanotechnology were analyzed.

Improved multi-scale inverse bottleneck residual network based on triplet parallel attention for apple leaf disease identification

Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from image texture and structural information. The difficulties in disease feature extraction in complex backgrounds slow the related research progress. To address the problems, this paper proposes an improved multi-scale inverse bottleneck residual network model based on a triplet parallel attention mechanism, which is built upon ResNet-50, while improving and combining the inception module and ResNext inverse bottleneck blocks, to recognize seven types of apple leaf(including six diseases of alternaria leaf spot, brown spot, grey spot, mosaic, rust, scab, and one healthy). First, the 3×3 convolutions in some of the residual modules are replaced by multi-scale residual convolutions, the convolution kernels of different sizes contained in each branch of the multi-scale convolution are applied to extract feature maps of different sizes, and the outputs of these branches are multi-scale fused by summing to enrich the output features of the images. Second, the global layer-wise dynamic coordinated inverse bottleneck structure is used to reduce the network feature loss. The inverse bottleneck structure makes the image information less lossy when transforming from different dimensional feature spaces. The fusion of multi-scale and layer-wise dynamic coordinated inverse bottlenecks makes the model effectively balances computational efficiency and feature representation capability, and more robust with a combination of horizontal and vertical features in the fine identification of apple leaf diseases. Finally, after each improved module, a triplet parallel attention module is integrated with cross-dimensional interactions among channels through rotations and residual transformations, which improves the parallel search efficiency of important features and the recognition rate of the network with relatively small computational costs while the dimensional dependencies are improved. To verify the validity of the model in this paper, we uniformly enhance apple leaf disease images screened from the public data sets of Plant Village, Baidu Flying Paddle, and the Internet. The final processed image count is 14,000. The ablation study, pre-processing comparison, and method comparison are conducted on the processed datasets. The experimental results demonstrate that the proposed method reaches 98.73% accuracy on the adopted datasets, which is 1.82% higher than the classical ResNet-50 model, and 0.29% better than the apple leaf disease datasets before preprocessing. It also achieves competitive results in apple leaf disease identification compared to some state-ofthe-art methods.

Characterization of mulberry leaf instant tea and evaluation of its hypolipidemia effect via regulation of intestinal microbiota

The purpose of this study was to characterize mulberry leaf instant tea(MLIT)powder prepared from the'Longsang No.1'(Morus abla L.cv.Longsang 1)mulberry leaves in Heilongjiang Province(China)and assess its obesity-preventing/relieving effects.A total of 174 compounds including quercetin,chlorogenic acid,1-deoxyecomycin(1-DNJ)related to antihyperlipidemia effects were identified from the MLIT powder.MLIT treatment reversed the Lee's index,fat coefficient,and serum biochemical parameters in both the obesity relieving and obesity preventing mice fed with high-fat diet.In the obesity relieving experiment,the relative abundance of Desulfovibrio in mouse feces decreased after both 0.5%and 1%MLIT treatments.In obesity preventing experiments,mouse with different amount of MLIT treatments showed increased relative abundance of Akkermansia,Bifidobacterium and Lactobacillus,while Deferribacteres,Desulfobacterota decreased.The beneficial bacteria in the intestinal tract of mice treated with MLIT increased.This study proved that MLIT had antihyperlipidemia potential via modulating intestinal microbiota in mice.

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.

Overexpression of auxin/indole-3-acetic acid gene MdIAA24 enhances Glomerella leaf spot resistance in apple(Malus domestica)

Auxin is throughout the entire life process of plants and is involved in the crosstalk with other hormones,yet its role in apple disease resistance remains unclear.In this study,we investigated the function of auxin/indole-3-acetic acid(IAA)gene Md IAA24 overexpression in enhancing apple resistance to Glomerella leaf spot(GLS)caused by Colletotrichum fructicola(Cf).Analysis revealed that,upon Cf infection,35S::Md IAA24 plants exhibited enhanced superoxide dismutase(SOD)and peroxidase(POD)activity,as well as a greater amount of glutathione(reduced form)and ascorbic acid accumulation,resulting in less H_(2)O_(2)and superoxide anion(O_(2)^(-))in apple leaves.Furthermore,35S::Md IAA24 plants produced more protocatechuic acid,proanthocyanidins B1,proanthocyanidins B2 and chlorogenic acid when infected with Cf.Following Cf infection,35S::Md IAA24 plants presented lower levels of IAA and jasmonic acid(JA),but higher levels of salicylic acid(SA),along with the expression of related genes.The overexpression of Md IAA24 was observed to enhance the activity of chitinase andβ-1,3-glucanase in Cfinfected leaves.The results indicated the ability of Md IAA24 to regulate the crosstalk between IAA,JA and SA,and to improve reactive oxygen species(ROS)scavenging and defense-related enzymes activity.This jointly contributed to GLS resistance in apple.

Synergistic effects of three traditional herbs green tea,mulberry leaf and corn silk on glucose uptake level of L6 myoblasts and the hypoglycemic mechanism

Background:Green tea,mulberry leaf and corn silk are traditional herbs used in the prevention and treatment of diabetes in China for a long time,but their synergistic hypoglycemic effects and mechanisms remain unclear.Methods:The effective components of green tea,mulberry leaf and corn silk were extracted and enriched.Mixture design of experiments was used to study the influences of different combinations on the cell viability and glucose uptake level of L6 myoblasts,so as to determine the optimal synergistic hypoglycemic combination.The possible hypoglycemic mechanism of the optimal synergistic combination was explored by cytotoxicity assay,glucose uptake assay,and western blot.Results:Three polyphenol enrichment fractions of the herbs,30%ethanol elution fraction of green tea(GT),50%ethanol elution fraction of mulberry leaf(ML)and 60%ethanol elution fraction of corn silk(CS)were obtained.The antioxidant activities of GT-30%,ML-50%and CS-60%were superior to those of crude extracts,and showed strong potential inα-amylase andα-glucosidase inhibition activities.The optimal synergistic combination of crude extracts G7(crude extract of green tea:crude extract of mulberry leaf:crude extract of corn silk=1:5:3),polyphenol enrichment fractions R3(GT-30%:ML-50%:CS-60%=1:7:1)and monomers X2(epigallocatechin gallate:morusin:formononetin=3:1:2)were selected,respectively.G7,R3,and X2 showed promoting effects on the cell viability and glucose uptake of L6 myoblasts within the detected concentration range.In addition,G7,R3,and X2 could increase the expression levels of p-PI3K/PI3K and p-Akt/Akt in L6 myoblasts,and promote the translocation of Glut4,but G7 and R3 showed more significant effects.Conclusion:The synergistic hypoglycemic effects of green tea,mulberry leaf and corn silk had the characteristics of multiple-components and multiple-targets with p-PI3K/PI3K,p-Akt/Akt and the translocation of Glut4 signal pathways involved.The three traditional herbs might have the potential to be combined used for the prevention and treatment of diabetes based on the synergistic hypoglycemic effects.

Development of Spectral Features for Monitoring Rice Bacterial Leaf Blight Disease Using Broad-Band Remote Sensing Systems

As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv.oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result ofthe disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remotesensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutionsoffer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapiddispersal under suitable conditions, making it difficult to track the disease at a regional scale with a single sensorin practice. Therefore, it is necessary to identify or construct features that are effective across different sensors formonitoring RBLB. To achieve this goal, the spectral response of RBLB was first analyzed based on the canopyhyperspectral data. Using the relative spectral response (RSR) functions of four representative satellite or UAVsensors (i.e., Sentinel-2, GF-6, Planet, and Rededge-M) and the hyperspectral data, the corresponding broad-bandspectral data was simulated. According to a thorough band combination and sensitivity analysis, two novel spectralindices for monitoring RBLB that can be effective across multiple sensors (i.e., RBBRI and RBBDI) weredeveloped. An optimal feature set that includes the two novel indices and a classical vegetation index was formed.The capability of such a feature set in monitoring RBLB was assessed via FLDA and SVM algorithms. The resultdemonstrated that both constructed novel indices exhibited high sensitivity to the disease across multiple sensors.Meanwhile, the feature set yielded an overall accuracy above 90% for all sensors, which indicates its cross-sensorgenerality in monitoring RBLB. The outcome of this research permits disease monitoring with different remotesensing data over a large scale.

Genomic Selection for Frogeye Leaf Spot Resistance in Soybean

Soybean frogeye leaf spot(FLS) disease is a global disease affecting soybean yield, especially in the soybean growing area of Heilongjiang Province. In order to realize genomic selection breeding for FLS resistance of soybean, least absolute shrinkage and selection operator(LASSO) regression and stepwise regression were combined, and a genomic selection model was established for 40 002 SNP markers covering soybean genome and relative lesion area of soybean FLS. As a result, 68 molecular markers controlling soybean FLS were detected accurately, and the phenotypic contribution rate of these markers reached 82.45%. In this study, a model was established, which could be used directly to evaluate the resistance of soybean FLS and to select excellent offspring. This research method could also provide ideas and methods for other plants to breeding in disease resistance.