Characteristics of life-form and growth-form of plant species in an alpine ecosystem of North-West Himalaya

The present study was conducted in the alpine pastures of Tungnath （30° 14＇ N and 79° 13＇ E） to observe life-form and growth-form patterns of alpine plant species under grazed and ungrazed conditions and to work out the plant life form spectrum. Species were categorized as plant habit, height and length of growth-cycle and life-form classes according to Raunkiaer＇s system. The results show that in total of 68 species at grazed site, hemicryptophytes （He） accounted for 50.00% species, followed by cryptophytes （26.47%）, chamaephytes （16.18%）, phanemphytes （4.41%） and therophytes （2.94%）. At the ungrazed site in 65 plant species, hemicryptophytes （He） accounted fo＇r 49.23% species, cryptophytes （26.15%）, chamaephytes （15.38%）, phanerophytes （6.15%） and ther6phytes （3.08 % species）. In general, hemicrptophyte are dominant^in both sites i.e. graged and ungrazed. Growth form categories were classified as forbs, shrubs, grasses and sedges＇and undershrubs, according to plant habit and height. On the basis of length of the growth cycle, species were categorized as plant species of short growth cycle, intermediate growth cycle and long growth cycle. The short forbs of plant habit and height, had the highest emergence, and grasses and sedges had the lowest emergence in representative species. Percentage of species with long growth cycle was highest in both sites.

Ecological features of Aconitum balfourii (Bruhl) Muk.-an endangered medicinal plant in the northwest Himalaya

Aconitum balfourii （Bruhl） Muk. （Ranunculaceae） is an en- dangered medicinal plant. Natural populations were surveyed in the northwest Himalaya for population estimation and evaluation of elite germplasm. Vegetation sampling of quadrats was conducted using the vertical belt transect method in areas supporting A. balfourii. Plant den- sity and relative dominance ofA. balfourii were low compared with other alpine species. Threat status was determined on a site-by-site basis as well as for entire western Himalaya..4. balfourii was generally classified as endangered on the basis of geographic distribution and critically en- dangered on the basis of abundance. We found the natural geographic distribution of.4. balfourii to be diminishing due to habitat destruction. Immediate corrective management measures are needed for sustainable utilization and long-term conservation of the species in the wild.

Vascular plants distribution in relation to topography and environmental variables in alpine zone of Kedarnath Wild Life Sanctuary,West Himalaya

The present study was carried out in Tungnath alpine meadows of Kedarnath Wild Life Sanctuary, Western Himalaya from subalpine to upper alpine zone. A total of four summits were selected along an altitudinal gradient and sampled for detailed vegetation analysis using multi summit approach as per Global observation research initiative in alpine environments(GLORIA). Species richness, diversity, and evenness among four summits as well as the interaction between environmental variables with plant communities were assessed. Monthly mean soil temperature was calculated using data retrieved from geo-precision temperature logger in order to identify the trend of soil temperature among different season and altitudinal gradient and its implications to plant communities. Soil samples were analyzed fromeach summit by collecting randomized composite soil samples. The indirect non-metric multidimensional scaling(NMDS) and direct canonical correspondence analysis(CCA) tools of ordination techniques to determine the linkage between plant species from various sample summits and biotic/abiotic environmental gradients were used in the present study. The results of the study demonstrated increase in species richness as soil temperature increases, the ecotone representing summits were found most warm summits followed by highest species richness. Annual soil temperature increased by 1.43°C at timberline ecotone. Whereas, at upper alpine zone the soil temperature increased by 0.810 C from year 2015 to 2016. S?rensen's similarity index was found to be increased between subalpine and upper alpine zone with increase in the presence of subalpine plant species at upper alpine zone. Both the ordination tools separate the subalpine summit and their respective vegetation from summits representingtimberline ecotone and upper alpine zone. Soil p H, altitude, soil cation exchange capacity were found as the key abiotic drivers for distribution of plant species.

Assessing anthropogenic pressure and threats on Paeonia emodi Wall.ex Royle habitats in Garhwal Himalaya

The Garhwal Himalaya is among the major repositories of immensely valuable wild edible plants and provides food security to the local population.Among the valuable plant species that grow in this region,Paeonia emodi(family Paeoniaceae)is an important wild edible species that found in temperate regions with an altitude range between 1800 and 2800 m.The species is facing a severe threat to its sustainability due to overharvesting,habitat disturbances,and a lack of effort regarding conservation.For the first time,this study investigated anthropogenic pressure,population decline perceptions in the natural habitat,and vulnerability assessment of P.emodi under selected study sites(n=23 villages).A semi structured questionnaire was used to interview approximately 45%of the local inhabitants,including herbal practitioners(Vaidhyas or Dais)of each village.On the basis of demographic characteristics,the perceptions and responses of 464 local people were documented regarding potential causes of deterioration and feasible options for sustainable utilization.Using the weight survey method,we estimated the actual amount of collection based on personal interaction and direct observation.In order to determine the threats status,a rapid vulnerability assessment(RVA)was performed and were used based on the current exploitation and usage.The present study revealed that leaf(100%)was the most frequently harvested part,followed by stem(95.65%),seed(26.09%),root(21.74%)and flower(13.04%).The village Triyuginarayan and Pothivasa recorded the highest collection scores while the purpose of the collection was mostly edible(100%),medicinal(100%),and least commercial(8.70%).According to the literature review and the present survey,the RVA(total=21)is categorized as category II(intermediate side of the RVA index),indicating a degree of vulnerability.The study revealed that P.emodi faces extinction in the Garhwal Himalayas.Growing this species through agro-production techniques may alleviate the pressure on the existing population as a result of the availability of raw materials for commercial and household uses.These findings will provide an effective framework for conservation and management decisions and plans.

Multiomic investigation of Sugarcane mosaic virus resistance in sugarcane

Sugarcane mosaic virus(SCMV)is the main etiological agent of sugarcane mosaic disease,which affects sugarcane and other grass crops.Despite the extensive characterization of quantitative trait loci controlling resistance to SCMV in maize,the genetic basis of this trait in sugarcane is largely unexplored.Here,a genome-wide association study was performed and machine learning coupled with feature selection was used for genomic prediction of resistance to SCMV in a diverse sugarcane panel.Nine single-nucleotide polymorphisms(SNPs)explained up to 29.9%of the observed phenotypic variance and a 73-SNP set predicted resistance with high accuracy,precision,recall,and F1 scores(the harmonic mean of precision and recall).Both marker sets were validated in additional sugarcane genotypes,in which the SNPs explained up to 23.6%of the phenotypic variation and predicted resistance with a maximum accuracy of 69.1%.Synteny analyses suggested that the gene responsible for the majority of SCMV resistance in maize is absent in sugarcane,explaining why this major resistance source has not been identified in this crop.Finally,using sugarcane RNA-Seq data,markers associated with resistance to SCMV were annotated,and a gene coexpression network was constructed to identify the predicted biological processes involved in resistance.This network allowed the identification of candidate resistance genes and confirmed the involvement of stress responses,photosynthesis,and the regulation of transcription and translation in resistance to SCMV.These results provide a practical marker-assisted breeding approach for sugarcane and identify target genes for future studies of SCMV resistance.

Multi-omics:Powerful accelerator for uncovering plant specialized metabolic pathways:The case of leonurine

As sessile organisms,plants employ a unique adaptive strategy to survive harsh terrestrial environments and defend against or interact with coevolving animals and microorganisms.This strategy involves expanding their metabolic systems,resulting in the production of plant specialized metabolites(PSMs)or natural products.Chemically,PSMs constitute a highly diverse group of compounds based on their common core structure,comprising terpenoids,phenylpropanoids,benzenoids,alkaloids and nitrogen-containing compounds,glucosinolates,indoles and sulfur-containing indole compounds,phenolics,and fatty acid derivatives(Garagounis et al.,2021).

中间偃麦草的GISH分析

以染色体组为 Ee Ee 的二倍体长穗偃麦草 (Thinopyrum elongatum,2 n=2 x=1 4)、染色体组为 Eb Eb的二倍体比萨偃麦草 (Th.bessarabicum,2 n=2 x=1 4)、染色体组为 St St St St的四倍体拟鹅冠草 (Pseudoroegneiria strigosa,2 n=4x=2 8)的总基因组 DNA为探针 ,对中间偃麦草 (Th.intermedium)进行 GISH分析。结果表明 ,中间偃麦草是由 2个亲缘关系较近的染色体组、1个亲缘关系较远的染色体组构成 ;中间偃麦草所含的亲缘关系较近的染色体组分别与二倍体长穗偃麦草染色体组 Ee、比萨偃麦草染色体组 Eb、以及 1个亲缘关系较远的染色体组与拟鹅冠草染色体组 St 基本相似 ,但不完全一样。因而 ,中间偃麦草的染色体组用Eet Eet Ebt Ebt St

A genetic linkage map with 178 SSR and 1901 SNP markers constructed using a RIL population in wheat (Triticum aestivum L.)

The construction of high density genetic linkage map provides a powerful tool to detect and map quantitative trait loci(QTLs) controlling agronomically important traits. In this study, simple sequence repeat(SSR) markers and Illumina 9K i Select single nucleotide polymorphism(SNP) genechip were employed to construct one genetic linkage map of common wheat(Triticum aestivum L.) using 191 recombinant inbred lines(RILs) derived from cross Yu 8679×Jing 411. This map included 1 901 SNP loci and 178 SSR loci, covering 1 659.9 c M and 1 000 marker bins, with an average interval distance of 1.66 c M. A, B and D genomes covered 719.1, 703.5 and 237.3 c M, with an average interval distance of 1.66, 1.45 and 2.9 c M, respectively. Notably, the genetic linkage map covered 20 chromosomes, with the exception of chromosome 5D. Bioinformatics analysis revealed that 1 754(92.27%) of 1 901 mapped SNP loci could be aligned to 1 215 distinct wheat unigenes, among which 1 184(97.4%) were located on o ne single chromosome, and the rest 31(2.6%) were located on 2 to 3 chromosomes. By performing in silico comparison, 214 chromosome deletion bin-mapped expressed sequence tags(ESTs), 1 043 Brachypodium genes and 1 033 rice genes were further added onto the genetic linkage map. This map not only integrated genetic and physical maps, SSR and SNP loci, respectively, but also provided the information of Brachypodium and rice genes corresponding to 1 754 SNP loci. Therefore, it will be a useful tool for comparative genomics analysis, fine mapping of QTL/gene controlling agronomically important traits and marker-assisted selection breeding in wheat.

Effectiveness of Beauveria bassiana Native Isolates in the Biological Control of the Med-iterranean Fruit Fly (Ceratitis capitata)

The effectiveness of native entomopathogenic Beauveria bassiana isolates in the biological control of the Mediterranean fruit fly (Ceratitis capitata) was evaluated under laboratory and field conditions. Local isolates (P. Bv32, P. Bv39, P. Bv41, P. Bv51, and P. Bv52) of the fungus B. bassiana induced higher adult mortalities (77%, 65%, 65%, 65%, and 58%, respectively) than a control against the Mediterranean fruit fly under laboratory conditions. Adult mortality increased by increasing the conidial concentrations. In addition, the lethal time (LT50) for killing adult C. capitata ranged from 3.91 to 5.60 days, and the logged lethal concentration (LC50) ranged from 3.80 to 10.50, depending on the isolate. Furthermore, the contact application method induced significantly higher mortality than feeding alone, compared with the control. In addition, spraying peaches with a conidial suspension of the isolates P. Bv32 and P. Bv39 significantly reduced infestation by the fruit fly, compared with the control. The isolates grew well at a temperature range of 25°C - 30°C;germination of the conidia occurred at 15°C - 30°C, and sporulation occurred at 20°C - 25°C. High Mediterranean fruit fly mortalities were induced at 15°C - 30°C, with significant differences among the isolates. However, the isolates failed to grow, germinate, or sporulate above 35°C or below 10°C. Under field conditions, a formula of the bioinsecticide containing the isolate P. Bv32 of B. bassiana significantly reduced peach infestation with Medfly maggots by 25% compared with the control, and by 30% when combined with a low dose of the commercial insecticide Confidor&reg.

Proteomic Identification of Rhythmic Proteins in Maize Seedling Leaves

Plant leaves respond to day/night cycling in a number of physiological ways. At the mRNA level, the expression of some genes changes during the 24 h period. To determine which proteins exhibited a rhythmic pattern of expression, proteomic profiles in maize seedling leaves were analyzed by high-throughput two-dimensional gel electrophoresis, combined with MALDI-TOF MS technology. Of the 464 proteins that were detected with silver staining in a pH range of 4-7, 17 （3.66%） showed clock rhythmicity in their abundance. These proteins belonged to diverse functional groups and proteins involved in photosynthesis and carbon metabolism were over-represented. These findings provide a new perspective on the relationship between the physiological functions of leaves and the clock rhythmic system.

Combining computer vision and deep learning to enable ultra-scale aerial phenotyping and precision agriculture:A case study of lettuce production

Aerial imagery is regularly used by crop researchers,growers and farmers to monitor crops during the growing season.To extract meaningful information from large-scale aerial images collected from the field,high-throughput phenotypic analysis solutions are required,which not only produce high-quality measures of key crop traits,but also support professionals to make prompt and reliable crop management decisions.Here,we report AirSurf,an automated and open-source analytic platform that combines modern computer vision,up-to-date machine learning,and modular software engineering in order to measure yield-related phenotypes from ultra-large aerial imagery.To quantify millions of in-field lettuces acquired by fixed-wing light aircrafts equipped with normalised difference vegetation index(NDVI)sensors,we customised AirSurf by combining computer vision algorithms and a deep-learning classifier trained with over 100,000 labelled lettuce signals.The tailored platform,AirSurf-Lettuce,is capable of scoring and categorising iceberg lettuces with high accuracy(>98%).Furthermore,novel analysis functions have been developed to map lettuce size distribution across the field,based on which associated global positioning system(GPS)tagged harvest regions have been identified to enable growers and farmers to conduct precision agricultural practises in order to improve the actual yield as well as crop marketability before the harvest.

Development of Soybean EST-SSR Markers and Their Use to Assess Genetic Diversity in the Subgenus Soja

Developing expressed sequence tag-derived SSR （EST-SSR） markers is imperative in genetic research. In this paper, we reported 37 EST-SSR markers which were developed from 286 unigenes obtained from soybean cDNA library. Among the 286 markers designed for the 4 accessions of Glycine max and 6 of its wild progenitor （G. soja） within the subgenus Soja, 209 markers amplified DNA fragments, taking 73.1% and 37 markers appeared to be polymorphic, which was 12.9% of the total. The 37 loci detected a total of 142 alleles, while the PIC values varied from 0.194 to 0.794. Both the number of alleles per locus and PIC value were significantly related to the SSR motif. Six EST-SSR loci may be fixed for different alleles between G. max and G. soja since they were particularly polymorphic among the 6 G. soja accessions. A neighbor-joining tree placed the G. max accessions together as a group within the G. soja, though the average genetic distance among G. soja accessions was much higher. These new EST-SSRs markers will be useful for genetic diversity analysis, genetic mapping construction and gene discovery in Soja subgenus.

Deciphering the contributions of spectral and structural data to wheat yield estimation from proximal sensing

Accurate, efficient, and timely yield estimation is critical for crop variety breeding and management optimization. However, the contributions of proximal sensing data characteristics(spectral, temporal, and spatial) to yield estimation have not been systematically evaluated. We collected long-term, hypertemporal, and large-volume light detection and ranging(Li DAR) and multispectral data to(i) identify the best machine learning method and prediction stage for wheat yield estimation,(ii) characterize the contribution of multisource data fusion and the dynamic importance of structural and spectral traits to yield estimation, and(iii) elucidate the contribution of time-series data fusion and 3 D spatial information to yield estimation. Wheat yield could be accurately(R^(2)= 0.891) and timely(approximately-two months before harvest) estimated from fused Li DAR and multispectral data. The artificial neural network model and the flowering stage were always the best method and prediction stage, respectively. Spectral traits(such as CIgreen) dominated yield estimation, especially in the early stage, whereas the contribution of structural traits(such as height) was more stable in the late stage. Fusing spectral and structural traits increased estimation accuracy at all growth stages. Better yield estimation was realized from traits derived from complete 3 D points than from canopy surface points and from integrated multi-stage(especially from jointing to heading and flowering stages) data than from single-stage data. We suggest that this study offers a novel perspective on deciphering the contributions of spectral, structural, and timeseries information to wheat yield estimation and can guide accurate, efficient, and timely estimation of wheat yield.

Integrated Analysis of the Trees and Associated UnderCanopy Species in a Subalpine Forest of Western Himalaya,Uttarakhand, India

Subalpine forests are known as outstanding habitats due to co-existence of both temperate and alpine vegetation and are classic example of ecotonal zones. Limited but diverse physiognomy of trees inhabiting in subalpine forest results in variability within under-canopy habitat conditions. Studies were undertaken to assess population status, habitat preference and interferences to the trees and associated undercanopy herbs in a subalpine forest of western Himalaya. A total of 10 woody and 23 under-canopy herbs were recorded in the selected subalpine forest area. At each stand, the number of tree species and under-canopy herbs ranged from 2 to 4 and 8 to 10 respectively. Abies spectabilis, Acer caesium, Quercus floribunda, Q. semecarpifolia and Rhododendron arboreum were key tree species in this area. The density of main woody species was 280 to 1190 individuals ha-1 at different stands. Herbaceous plants with rosette and clump growth habits were observed to have higher values for total basal cover and importance value index. Presence of some undercanopy herbs like; Dactylorhiza hatagirea, Malaxis muscifera, Picrorhiza kurrooa, Polygonatumcirrhifolium and Skimmia laureola in the specific habitats also showed that they are habitat specific.However, the presence of Frageria nubicola and Viola sp. was common in the selected stands. Felling of trees for timber, construction of temporary huts,fuel wood and lopping for fodder were main interferences for trees. On the other hand, trampling driven damage due to grazing, habitats degradation and overexploitation were observed key threats for under-canopy herbs. Integrated analysis including population studies, habitats preference and interferences to the trees and under-canopy herbs in this sensitive and important ecosystem will be useful for determining the conservation plans and ecosystem management.

Diversity and species-specificity of brood pollination of leafflower trees(Phyllanthaceae:Glochidion)by leafflower moths(Lepidoptera:Epicephala)in tropical Southeast Asia(Cambodia)

Glochidion(Phyllanthaceae;leafflower trees)is a genus of trees which is widely reported to be pollinated by leafflower moths(Gracillariidae:Epicephala)in temperate and subtropical Asia,Australia,and the Pacific islands.However,the pollination ecology of Glochidion is not well described from tropical Asia,the region where it is most species-rich at both local(<9 spp.)and regional(~200 spp.)scales.Here we report investigations of pollination biology and species-specificity of five Glochidion species in tropical Southeast Asia(Cambodia).Through nocturnal observations and fruit dissections,we find that at least three and likely five Glochidion species in Cambodia are pollinated by seed-parasitic leafflower moths.We find no evidence that any of these leafflower moths are non-mutualistic parasites,despite known examples of such parasites of this mutualism elsewhere in Asia.While the presence of a single larva in a fruit results in only a fraction of seeds being consumed,the presence of more than one larva per fruit-a frequent occurrence in some species—can result in almost all seeds within the fruit being infested.Multilocus phylogenetic analysis indicates that there are five different minimally monophyletic leafflower moth clades,each of which pollinates a unique Glochidion host species.Our results indicate that in its center of diversity in tropical Asia this system is an obligate pollination mutualism as previously described at the global margins of its distribution.These findings provide insights into the processes that generate and maintain biodiversity and maintain mutualism stability in plant-insect interactions in this biodiversity hotspot.

Allometry-based estimation of forest aboveground biomass combining LiDAR canopy height attributes and optical spectral indexes

Accurate estimates of forest aboveground biomass(AGB)are essential for global carbon cycle studies and have widely relied on approaches using spectral and structural information of forest canopies extracted from various remote sensing datasets.However,combining the advantages of active and passive data sources to improve estimation accuracy remains challenging.Here,we proposed a new approach for forest AGB modeling based on allometric relationships and using the form of power-law to integrate structural and spectral information.Over 60 km^(2) of drone light detection and ranging(LiDAR)data and 1,370 field plot measurements,covering the four major forest types of China(coniferous forest,sub-tropical broadleaf forest,coniferous and broadleaf-leaved mixed forest,and tropical broadleaf forest),were collected together with Sentinel-2 images to evaluate the proposed approach.The results show that the most universally useful structural and spectral metrics are the average values of canopy height and spectral index rather than their maximum values.Compared with structural attributes used alone,combining structural and spectral information can improve the estimation accuracy of AGB,increasing R^(2) by about 10%and reducing the root mean square error by about 22%;the accuracy of the proposed approach can yield a R^(2) of 0.7 in different forests types.The proposed approach performs the best in coniferous forest,followed by sub-tropical broadleaf forest,coniferous and broadleaf-leaved mixed forest,and then tropical broadleaf forest.Furthermore,the simple linear regression used in the proposed method is less sensitive to sample size and outperforms statistically multivariate machine learning-based regression models such as stepwise multiple regression,artificial neural networks,and Random Forest.The proposed approach may provide an alternative solution to map large-scale forest biomass using space-borne LiDAR and optical images with high accuracy.

Correction to:Transient expression of SbDhr2 and MeHNL in Gossypium hirsutum for herbivore deterrence assay with Spodoptera litura

Correction to:J Cotton Res 3,2(2020)https://doi.org/10.1186/s42397-020-0044-z We would like to correct the authorship of our article(Mahajan et al.2020)to include RAWAL Shuban,PYATI Prashant,PANDA Bhuban and LOMATE Purushottam.The updated authorship,affiliations and contributions can be seen below.Also,we would like to gratefully acknowledge Mr.Sameer MULAY,Managing Director of Ajeet Seeds Pvt.Ltd.for providing resources to carry out the research at Plant Biotechnology Research Centre,Gangapur.

Self-Supervised Plant Phenotyping by Combining Domain Adaptation with 3D Plant Model Simulations: Application to Wheat Leaf Counting at Seedling Stage

The number of leaves at a given time is important to characterize plant growth and development.In this work,we developed a high-throughput method to count the number of leaves by detecting leaf tips in RGB images.The digital plant phenotyping platform was used to simulate a large and diverse dataset of RGB images and corresponding leaf tip labels of wheat plants at seedling stages(150,000 images with over 2 million labels).The realism of the images was then improved using domain adaptation methods before training deep learning models.The results demonstrate the efficiency of the proposed method evaluated on a diverse test dataset,collecting measurements from 5 countries obtained under different environments,growth stages,and lighting conditions with different cameras(450 images with over 2,162 labels).Among the 6 combinations of deep learning models and domain adaptation techniques,the Faster-RCNN model with cycle-consistent generative adversarial network adaptation technique provided the best performance(R^(2)=0.94,root mean square error=8.7).Complementary studies show that it is essential to simulate images with sufficient realism(background,leaf texture,and lighting conditions)before applying domain adaptation techniques.Furthermore,the spatial resolution should be better than 0.6 mm per pixel to identify leaf tips.The method is claimed to be self-supervised since no manual labeling is required for model training.The self-supervised phenotyping approach developed here offers great potential for addressing a wide range of plant phenotyping problems.The trained networks are available at https://github.com/YinglunLi/Wheat-leaf-tip-detection.