scholarly journals Understanding photothermal interactions will help expand production range and increase genetic diversity of lentil (Lens culinaris Medik.)

2020 ◽  
Author(s):  
Derek M. Wright ◽  
Sandesh Neupane ◽  
Taryn Heidecker ◽  
Teketel A. Haile ◽  
Clarice J. Coyne ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Lens Culinaris ◽  
Photoperiod Sensitivity ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
List Type ◽  
Exotic Germplasm ◽  
Breeding Programs ◽  
Wide Range ◽  
Production Areas

SummaryLentil (Lens culinaris Medik.) is cultivated under a wide range of environmental conditions, which led to diverse phenological adaptations and resulted in a decrease in genetic variability within breeding programs due to reluctance in using genotypes from other environments.We phenotyped 324 genotypes across nine locations over three years to assess their phenological response to the environment of major lentil production regions and to predict days from sowing to flowering (DTF) using a photothermal model.DTF was highly influenced by the environment and is sufficient to explain adaptation. We were able to predict DTF reliably in most environments using a simple photothermal model, however, in certain site-years, results suggest there may be additional environmental factors at play. Hierarchical clustering of principal components revealed the presence of eight groups based on the responses of DTF to contrasting environments. These groups are associated with the coefficients of the photothermal model and revealed differences in temperature and photoperiod sensitivity.Expanding genetic diversity is critical to the success of a breeding program; understanding adaptation will facilitate the use of exotic germplasm. Future climate change scenarios will result in increase temperature and/or shifts in production areas, we can use the photothermal model to identify genotypes most likely to succeed in these new environments.

scholarly journals Trends in Molecular Diagnosis and Diversity Studies for Phytosanitary Regulated Xanthomonas

2021 ◽  
Vol 9 (4) ◽  
pp. 862
Author(s):  
Vittoria Catara ◽  
Jaime Cubero ◽  
Joël F. Pothier ◽  
Eran Bosis ◽  
Claude Bragard ◽  
...  
Keyword(s):  
Molecular Diagnosis ◽  
Bacterial Species ◽  
Management Strategies ◽  
Diagnostic Methods ◽  
Plant Diseases ◽  
Wild Plants ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Wide Range ◽  
Diversity Studies

Bacteria in the genus Xanthomonas infect a wide range of crops and wild plants, with most species responsible for plant diseases that have a global economic and environmental impact on the seed, plant, and food trade. Infections by Xanthomonas spp. cause a wide variety of non-specific symptoms, making their identification difficult. The coexistence of phylogenetically close strains, but drastically different in their phenotype, poses an added challenge to diagnosis. Data on future climate change scenarios predict an increase in the severity of epidemics and a geographical expansion of pathogens, increasing pressure on plant health services. In this context, the effectiveness of integrated disease management strategies strongly depends on the availability of rapid, sensitive, and specific diagnostic methods. The accumulation of genomic information in recent years has facilitated the identification of new DNA markers, a cornerstone for the development of more sensitive and specific methods. Nevertheless, the challenges that the taxonomic complexity of this genus represents in terms of diagnosis together with the fact that within the same bacterial species, groups of strains may interact with distinct host species demonstrate that there is still a long way to go. In this review, we describe and discuss the current molecular-based methods for the diagnosis and detection of regulated Xanthomonas, taxonomic and diversity studies in Xanthomonas and genomic approaches for molecular diagnosis.

scholarly journals Why and How to Switch to Genomic Selection: Lessons From Plant and Animal Breeding Experience

2021 ◽  
Vol 12 ◽  
Author(s):  
◽  
Aline Fugeray-Scarbel ◽  
Catherine Bastien ◽  
Mathilde Dupont-Nivet ◽  
Stéphane Lemarié
Keyword(s):  
Genetic Diversity ◽  
Genomic Selection ◽  
Plant Species ◽  
Animal Species ◽  
Animal Breeding ◽  
Breeding Cycle ◽  
Breeding Programs ◽  
The Third ◽  
Wide Range ◽  
Selection For

The present study is a transversal analysis of the interest in genomic selection for plant and animal species. It focuses on the arguments that may convince breeders to switch to genomic selection. The arguments are classified into three different “bricks.” The first brick considers the addition of genotyping to improve the accuracy of the prediction of breeding values. The second consists of saving costs and/or shortening the breeding cycle by replacing all or a portion of the phenotyping effort with genotyping. The third concerns population management to improve the choice of parents to either optimize crossbreeding or maintain genetic diversity. We analyse the relevance of these different bricks for a wide range of animal and plant species and sought to explain the differences between species according to their biological specificities and the organization of breeding programs.

scholarly journals Population structure and phylogenetic relationships in Brassica rapa L. subspecies by using isozyme markers

2020 ◽  
Author(s):  
R. H. Sammour ◽  
M. A. Karam ◽  
Y. S. Morsi ◽  
R. M. Ali
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Brassica Rapa ◽  
Phylogenetic Relationships ◽  
Fixation Index ◽  
Distribution Area ◽  
Enzyme Analysis ◽  
Breeding Programs ◽  
Expected Heterozygosity ◽  
Wide Range

Abstract The present study aimed to assess population structure and phylogenetic relationships of nine subspecies of Brassica rapa L. represented with thirty-five accessions cover a wide range of species distribution area using isozyme analysis in order to select more diverse accessions as supplementary resources that can be utilized for improvement of B. napus. Enzyme analysis resulted in detecting 14 putative polymorphic loci with 27 alleles. Mean allele frequency 0.04 (rare alleles) was observed in Cat4A and Cat4B in sub species Oleifera accession CR 2204/79 and in subspecies trilocularis accessions CR 2215/88 and CR 2244/88. The highest genetic diversity measures were observed in subspecies dichotoma, accession CR 1585/96 (the highest average of observed (H0) and expected heterozygosity (He), and number of alleles per locus (Ae)). These observations make this accession valuable genetic resource to be included in breeding programs for the improvement of oilseed B. napus. The average fixation index (F) is significantly higher than zero for the analysis accessions indicating a significant deficiency of heteozygosity. The divergence among subspecies indicated very great genetic differentiation (FST = 0.8972) which means that about 90% of genetic diversity is distributed among subspecies, while 10% of the diversity is distributed within subspecies. This coincides with low value of gene flow (Nm = 0.0287). B. rapa ssp. oleifera (turnip rape) and B. rapa ssp. trilocularis (sarson) were grouped under one cluster which coincides with the morphological classification.

scholarly journals Effects of Climatic Change on the Potential Distribution of Lycoriella Species (Diptera: Sciaridae) of Economic Importance

Insects ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 831
Author(s):  
Roberta Marques ◽  
Juliano Lessa Pinto Duarte ◽  
Adriane da Fonseca Duarte ◽  
Rodrigo Ferreira Krüger ◽  
Uemmerson Silva da Cunha ◽  
...  
Keyword(s):  
Climate Change ◽  
Range Expansion ◽  
Cold Climate ◽  
Future Climate Change ◽  
Economic Losses ◽  
Potential Range ◽  
Climate Change Scenarios ◽  
Ecological Niche Models ◽  
Greenhouse Production ◽  
Production Areas

Lycoriella species (Sciaridae) are responsible for significant economic losses in greenhouse production (e.g., mushrooms, strawberries, and nurseries). The current distributions of species in the genus are restricted to cold-climate countries. Three species of Lycoriella are of particular economic concern in view of their ability to invade areas in countries across the Northern Hemisphere. We used ecological niche models to determine the potential for range expansion under future climate change scenarios (RCP 4.5 and RCP 8.5) in the distribution of these three species of Lycoriella. Stable environmental suitability under climate change was a dominant theme in these species; however, potential range increases were noted in key countries (e.g., USA, Brazil, and China). Our results illustrate the potential for range expansion in these species in the Southern Hemisphere, including some of the highest greenhouse production areas in the world.

scholarly journals The role of glacier dynamics and threshold definition in the characterisation of future streamflow droughts in glacierised catchments

2017 ◽  
Author(s):  
Marit Van Tiel ◽  
Adriaan J. Teuling ◽  
Niko Wanders ◽  
Marc J. P. Vis ◽  
Kerstin Stahl ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Scales ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Glacier Area ◽  
Short Term ◽  
Drought Characteristics ◽  
Wide Range ◽  
Glacier Dynamics ◽  
The Future

Abstract. Glaciers are essential hydrological reservoirs, storing and releasing water at various time scales. Short-term variability in glacier melt is one of the causes of streamflow droughts, defined as below normal water availabilities. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long time scales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the HBV-light model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5). Two types of glacier modelling are applied, a constant and dynamical glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975–2004) and future (2071–2100) period. Two existing threshold approaches to define future droughts are employed, (1) the threshold from the historical period and (2) a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamical glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical threshold combined with a constant glacier area results in a drastic decrease of the number of droughts. The drought characteristics between future and historic periods are more similar when the transient threshold is used, for both glacier dynamics conceptualisations. With the transient threshold causing factors of future droughts, can be analysed. This study revealed the different effects of methodological choices on future streamflow drought projections and it highlights how the options can be used to analyse different aspects of future droughts: the transient threshold for analysing future drought processes, the historical threshold to assess changes between periods, the constant glacier area to analyse the effect of short term climate variability on droughts and the dynamical glacier area to model realistic future discharges under climate change.

Methods and uncertainties in bioclimatic envelope modelling under climate change

2006 ◽  
Vol 30 (6) ◽  
pp. 751-777 ◽  
Author(s):  
Risto K. Heikkinen ◽  
Miska Luoto ◽  
Miguel B. Araújo ◽  
Raimo Virkkala ◽  
Wilfried Thuiller ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climatic Factors ◽  
Future Climate Change ◽  
Future Research ◽  
Climate Change Scenarios ◽  
Distribution Models ◽  
Wide Range ◽  
Bioclimatic Modelling ◽  
Bioclimatic Envelope

Potential impacts of projected climate change on biodiversity are often assessed using single-species bioclimatic ‘envelope’models. Such models are a special case of species distribution models in which the current geographical distribution of species is related to climatic variables so to enable projections of distributions under future climate change scenarios. This work reviews a number of critical methodological issues that may lead to uncertainty in predictions from bioclimatic modelling. Particular attention is paid to recent developments of bioclimatic modelling that address some of these issues as well as to the topics where more progress needs to be made. Developing and applying bioclimatic models in a informative way requires good understanding of a wide range of methodologies, including the choice of modelling technique, model validation, collinearity, autocorrelation, biased sampling of explanatory variables, scaling and impacts of non-climatic factors. A key challenge for future research is integrating factors such as land cover, direct CO2 effects, biotic interactions and dispersal mechanisms into species-climate models. We conclude that, although bioclimatic envelope models have a number of important advantages, they need to be applied only when users of models have a thorough understanding of their limitations and uncertainties.

scholarly journals Making WAVES in Breedbase: An Integrated Spectral Data Storage and Analysis Pipeline for Plant Breeding Programs

2020 ◽  
Author(s):  
Jenna Hershberger ◽  
Nicolas Morales ◽  
Christiano C. Simoes ◽  
Bryan Ellerbrock ◽  
Guillaume Bauchet ◽  
...  
Keyword(s):  
Plant Breeding ◽  
Open Source ◽  
Spectral Data ◽  
Data Storage ◽  
Cross Validation ◽  
R Package ◽  
List Type ◽  
Breeding Programs ◽  
Wide Range ◽  
Prediction Functions

ABSTRACTVisible and near-infrared (vis-NIRS) spectroscopy is a promising tool for increasing phenotyping throughput in plant breeding programs, but existing analysis software packages are not optimized for a breeding context. Additionally, commercial software options are often outside of budget constraints for some breeding and research programs. To that end, we developed an open-source R package, waves, for the streamlined analysis of spectral data with several cross-validation schemes to assess prediction accuracy. Waves is compatible with a wide range of spectrometer models and performs visualization, filtering, aggregation, cross-validation set formation, model training, and prediction functions for the association of vis-NIRS spectra with reference measurements. Furthermore, we have integrated this package into the Breedbase family of open-source databases, expanding the analysis capabilities of this growing digital ecosystem to a number of crop species. Taken together, the standalone and Breedbase versions of waves enhance the accessibility of tools for the analysis of spectral data during the plant breeding process.Core ideaswaves is an open-source R package for spectral data analysis in plant breedingBreeding relevant cross-validation schemes to evaluate predictive accuracy of modelsExtension of Breedbase—an open-source database—to support spectral data storageGraphical user interface developed for implementation of waves in Breedbase

scholarly journals Evaluation of Genetic Diversity in Cultivated and Exotic Germplasm Sources of Faba Bean Using Important Morphological Traits

2020 ◽  
Author(s):  
Praveen Kumar ◽  
Prashant Kaushik
Keyword(s):  
Genetic Diversity ◽  
Food Security ◽  
Seed Yield ◽  
Faba Bean ◽  
Morphological Traits ◽  
Block Design ◽  
Exotic Germplasm ◽  
Randomized Block Design ◽  
Wide Range ◽  
Positive Effect

AbstractBackground and ObjectiveFaba bean is an important crop for achieving nutritional food security, but there is very limited diversity in the cultivated varieties of faba bean. Moreover, genetic diversity is vital for its use in faba bean genetic imporvement.Material and MethodsHere we determined the diversity in the sixty-four genotypes of faba bean of different agro-ecological origins. Plants were grown in randomized block design in three replications. Further, the genotypes were characterized based on the ten morphological traits.ResultsHighly significant differences were determined for all of the studied traits. Whereas, the number of cluster per plant was positively correlated with the pods per plants. Moreover, the trait number of cluster per plant determined the most substantial positive effect on seed yield.ConclusionsOverall, our results indicate a wide range of variability for further selection and improvement of faba bean ideotype.

scholarly journals The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests

2019 ◽  
Author(s):  
Christopher P. O. Reyer ◽  
Ramiro Silveyra Gonzalez ◽  
Klara Dolos ◽  
Florian Hartig ◽  
Ylva Hauf ◽  
...  
Keyword(s):  
Climate Change ◽  
Nitrogen Deposition ◽  
Forest Stand ◽  
Climate Impacts ◽  
Ecosystem Dynamics ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Flat File ◽  
Wide Range ◽  
Vegetation Models

Abstract. Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand-level, as well as remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction, and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a SQLite relational database or ASCII flat file version (at https://doi.org/10.5880/PIK.2019.008). The data policies of the individual, contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R-package (https://github.com/COST-FP1304-PROFOUND/ProfoundData), which provides basic functions to explore, plot, and extract the data for model set-up, calibration and evaluation.

scholarly journals The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests

2020 ◽  
Vol 12 (2) ◽  
pp. 1295-1320 ◽  
Author(s):  
Christopher P. O. Reyer ◽  
Ramiro Silveyra Gonzalez ◽  
Klara Dolos ◽  
Florian Hartig ◽  
Ylva Hauf ◽  
...  
Keyword(s):  
Climate Change ◽  
Nitrogen Deposition ◽  
Forest Stand ◽  
Climate Impacts ◽  
Ecosystem Dynamics ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
European Forests ◽  
Wide Range ◽  
Vegetation Models

Abstract. Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a “SQLite” relational database or “ASCII” flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.

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