scholarly journals The World Vegetable Center Okra (Abelmoschus esculentus) Core Collection as a Source for Flooding Stress Tolerance Traits for Breeding

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 165
Author(s):  
Roland Schafleitner ◽  
Chen-Yu Lin ◽  
Ya-Ping Lin ◽  
Tien-Hor Wu ◽  
Cian-Huei Hung ◽  
...  
Keyword(s):  
Core Collection ◽  
Vegetation Index ◽  
Germplasm Collection ◽  
Growth Increment ◽  
Abelmoschus Esculentus ◽  
Daily Growth ◽  
Flooding Stress ◽  
The World ◽  
High Throughput Phenotyping ◽  
Traits For Breeding

Okra (Abelmoschus esculentus) is a heat tolerant vegetable crop with high economic and nutritional importance in parts of Asia, Africa, and America. The okra biodiversity held in gene bank collections could be mined for traits for breeding more stress tolerant and nutritional cultivars. An okra core collection of 166 accessions comprising A. esculentus, A. moschatus, A. caillei, and A. manihot has been assembled from the World Vegetable Center germplasm collection (840 accessions) based on diversity analysis with 20 microsatellite markers. A selection of A. esculentus accessions of the core collection (75 accessions) and 20 breeder-selected genotypes have been screened for variation of their response to flooding stress under field conditions using a high throughput phenotyping system. Growth increment per day and changes of physiological indices were measured before, during, and after application of 9 days of flooding stress. Several accessions showed only a small reduction in daily growth increment during flooding. Across the germplasm panel, maintained growth was correlated with maintained normalized differential vegetation index and was negatively correlated with plant senescence index. Accessions with maintained growth and health under flooding were selected for future further analysis and use in breeding.

A Core Collection for the United States Annual Medicago Germplasm Collection

Crop Science ◽  
1994 ◽  
Vol 34 (1) ◽  
pp. 279-285 ◽  
Author(s):  
Noa Diwan ◽  
Gary R. Bauchan ◽  
Marla S. McIntosh
Keyword(s):  
United States ◽  
Core Collection ◽  
Germplasm Collection ◽  
The United States ◽  
Annual Medicago

scholarly journals Validation of UAV-based alfalfa biomass predictability using photogrammetry with fully automatic plot segmentation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhou Tang ◽  
Atit Parajuli ◽  
Chunpeng James Chen ◽  
Yang Hu ◽  
Samuel Revolinski ◽  
...  
Keyword(s):  
Prediction Model ◽  
High Throughput ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Selection Process ◽  
Forage Legume ◽  
Breeding Programs ◽  
High Throughput Phenotyping ◽  
Fully Automatic ◽  
Uav Images

AbstractAlfalfa is the most widely cultivated forage legume, with approximately 30 million hectares planted worldwide. Genetic improvements in alfalfa have been highly successful in developing cultivars with exceptional winter hardiness and disease resistance traits. However, genetic improvements have been limited for complex economically important traits such as biomass. One of the major bottlenecks is the labor-intensive phenotyping burden for biomass selection. In this study, we employed two alfalfa fields to pave a path to overcome the challenge by using UAV images with fully automatic field plot segmentation for high-throughput phenotyping. The first field was used to develop the prediction model and the second field to validate the predictions. The first and second fields had 808 and 1025 plots, respectively. The first field had three harvests with biomass measured in May, July, and September of 2019. The second had one harvest with biomass measured in September of 2019. These two fields were imaged one day before harvesting with a DJI Phantom 4 pro UAV carrying an additional Sentera multispectral camera. Alfalfa plot images were extracted by GRID software to quantify vegetative area based on the Normalized Difference Vegetation Index. The prediction model developed from the first field explained 50–70% (R Square) of biomass variation in the second field by incorporating four features from UAV images: vegetative area, plant height, Normalized Green–Red Difference Index, and Normalized Difference Red Edge Index. This result suggests that UAV-based, high-throughput phenotyping could be used to improve the efficiency of the biomass selection process in alfalfa breeding programs.

Variability of in vitro ruminal fermentation and methanogenic potential in the pasture legume biserrula (Biserrula pelecinus L.)

2013 ◽  
Vol 64 (4) ◽  
pp. 409 ◽  
Author(s):  
Bidhyut Kumar Banik ◽  
Zoey Durmic ◽  
William Erskine ◽  
Phillip Nichols ◽  
Kioumars Ghamkhar ◽  
...  
Keyword(s):  
Core Collection ◽  
Volatile Fatty Acids ◽  
Germplasm Collection ◽  
Red Clover ◽  
Subterranean Clover ◽  
Ruminal Fermentation ◽  
Rumen Microbes ◽  
Pasture Legumes ◽  
Pasture Legume

Biserrula (Biserrula pelecinus L.) is an important annual pasture legume for the wheatbelt of southern Australia and has been found to have lower levels of methane output than other pasture legumes when fermented by rumen microbes. Thirty accessions of the biserrula core germplasm collection were grown in the glasshouse to examine intra-specific variability in in vitro rumen fermentation, including methane output. One biserrula cultivar (Casbah) was also grown at two field locations to confirm that low methanogenic potential was present in field-grown samples. All of the biserrula accessions had significantly reduced methane [range 0.5–8.4 mL/g dry matter (DM)] output compared with subterranean clover (28.4 mL/g DM) and red clover (36.1 mL/g DM). There was also significant variation in fermentability profiles (except for volatile fatty acids) among accessions of the core collection. Methanogenic potential exhibited 86% broad-sense heritability within the biserrula core collection. The anti-methanogenic and gas-suppressing effect of biserrula was also confirmed in samples grown in the field. In conclusion, biserrula showed variability in in vitro fermentation traits including reduced methane production compared with controls. This bioactivity of biserrula also persists in the field, indicating scope for further selection of biserrula as an elite methane-mitigating pasture.

scholarly journals Genetic diversity and population structure of a mini-core subset from the world cowpea (Vigna unguiculata (L.) Walp.) germplasm collection

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Christian Fatokun ◽  
Gezahegn Girma ◽  
Michael Abberton ◽  
Melaku Gedil ◽  
Nnanna Unachukwu ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Vigna Unguiculata ◽  
Germplasm Collection ◽  
Core Subset ◽  
The World

scholarly journals Scientometric analysis activity in the publication «life sciences» in the world and in Ukraine

2019 ◽  
pp. 23-33
Author(s):  
V.M. Yevtushenko
Keyword(s):  
Core Collection ◽  
Web Of Science ◽  
Journal Citation Report ◽  
Life Sciences ◽  
Scientometric Analysis ◽  
Research Areas ◽  
The World ◽  
Scientific Papers ◽  
Scientific Fields ◽  
The Web

The article is devoted to the study of the state and trends of the publishing activity of Ukrainian scientists and leading countries in the field of life sciences («Life sciences»). The Web of Science Core Collection (WoS CC), Journal Citation Report (JSR) and InCites, as well as classifications of scientific fields designed to structure the publication flow of scientific papers and journals in these information resources, are used for the research base – Web of Science Categories and Research Areas. The article presents the results of the author’s research on the publication indices of scientists of Ukraine and the leading countries of the world for the period 2008-2018 in the field of “Life Sciences” according to the international science-computer database of Web of Science. Conclusions about the growth of indicators of publication activity of scientific works in the field of “Life Sciences” are made. The tendency of a significant increase in their number in Ukraine has been revealed, but domestic studies do not represent all the areas of «Life Sciences» most popular in foreign scientists

scholarly journals Genotypic Characterization of the U.S. Peanut Core Collection

2020 ◽  
Vol 10 (11) ◽  
pp. 4013-4026
Author(s):  
Paul I. Otyama ◽  
Roshan Kulkarni ◽  
Kelly Chamberlin ◽  
Peggy Ozias-Akins ◽  
Ye Chu ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Core Collection ◽  
Regional Distribution ◽  
Country Of Origin ◽  
Snp Array ◽  
Germplasm Collection ◽  
Genotypic Diversity ◽  
Cultivated Peanut ◽  
Food And Feed ◽  
Genetic Clustering

Cultivated peanut (Arachis hypogaea) is an important oil, food, and feed crop worldwide. The USDA peanut germplasm collection currently contains 8,982 accessions. In the 1990s, 812 accessions were selected as a core collection on the basis of phenotype and country of origin. The present study reports genotyping results for the entire available core collection. Each accession was genotyped with the Arachis_Axiom2 SNP array, yielding 14,430 high-quality, informative SNPs across the collection. Additionally, a subset of 253 accessions was replicated, using between two and five seeds per accession, to assess heterogeneity within these accessions. The genotypic diversity of the core is mostly captured in five genotypic clusters, which have some correspondence with botanical variety and market type. There is little genetic clustering by country of origin, reflecting peanut’s rapid global dispersion in the 18th and 19th centuries. A genetic cluster associated with the hypogaea/aequatoriana/peruviana varieties, with accessions coming primarily from Bolivia, Peru, and Ecuador, is consistent with these having been the earliest landraces. The genetics, phenotypic characteristics, and biogeography are all consistent with previous reports of tetraploid peanut originating in Southeast Bolivia. Analysis of the genotype data indicates an early genetic radiation, followed by regional distribution of major genetic classes through South America, and then a global dissemination that retains much of the early genetic diversity in peanut. Comparison of the genotypic data relative to alleles from the diploid progenitors also indicates that subgenome exchanges, both large and small, have been major contributors to the genetic diversity in peanut.

scholarly journals Evaluation of Unsupervised Change Detection Methods Applied to Landslide Inventory Mapping Using ASTER Imagery

2018 ◽  
Vol 10 (12) ◽  
pp. 1987 ◽  
Author(s):  
Rocío Ramos-Bernal ◽  
René Vázquez-Jiménez ◽  
Raúl Romero-Calcerrada ◽  
Patricia Arrogante-Funes ◽  
Carlos Novillo
Keyword(s):  
Change Detection ◽  
Vegetation Index ◽  
Thermal Emission ◽  
Principal Component ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Data Types ◽  
Statistical Parameters ◽  
Wide Range ◽  
The World

Natural hazards include a wide range of high-impact phenomena that affect socioeconomic and natural systems. Landslides are a natural hazard whose destructive power has caused a significant number of victims and substantial damage around the world. Remote sensing provides many data types and techniques that can be applied to monitor their effects through landslides inventory maps. Three unsupervised change detection methods were applied to the Advanced Spaceborne Thermal Emission and Reflection Radiometer (Aster)-derived images from an area prone to landslides in the south of Mexico. Linear Regression (LR), Chi-Square Transformation, and Change Vector Analysis were applied to the principal component and the Normalized Difference Vegetation Index (NDVI) data to obtain the difference image of change. The thresholding was performed on the change histogram using two approaches: the statistical parameters and the secant method. According to previous works, a slope mask was used to classify the pixels as landslide/No-landslide; a cloud mask was used to eliminate false positives; and finally, those landslides less than 450 m2 (two Aster pixels) were discriminated. To assess the landslide detection accuracy, 617 polygons (35,017 pixels) were sampled, classified as real landslide/No-landslide, and defined as ground-truth according to the interpretation of color aerial photo slides to obtain omission/commission errors and Kappa coefficient of agreement. The results showed that the LR using NDVI data performs the best results in landslide detection. Change detection is a suitable technique that can be applied for the landslides mapping and we think that it can be replicated in other parts of the world with results similar to those obtained in the present work.

scholarly journals Genome-Wide Detection of SNP Markers Associated with Four Physiological Traits in Groundnut (Arachis hypogaea L.) Mini Core Collection

Agronomy ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 192 ◽  
Author(s):  
Abdulwahab S. Shaibu ◽  
Clay Sneller ◽  
Babu N. Motagi ◽  
Jackline Chepkoech ◽  
Mercy Chepngetich ◽  
...  
Keyword(s):  
Core Collection ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Canopy Temperature ◽  
Snp Markers ◽  
Physiological Traits ◽  
Area Index ◽  
Trait Association ◽  
Mini Core Collection ◽  
Genome Wide

In order to integrate genomics in breeding and development of drought-tolerant groundnut genotypes, identification of genomic regions/genetic markers for drought surrogate traits is essential. We used 3249 diversity array technology sequencing (DArTSeq) markers for a genetic analysis of 125 ICRISAT groundnut mini core collection evaluated in 2015 and 2017 for genome-wide marker-trait association for some physiological traits and to determine the magnitude of linkage disequilibrium (LD). Marker-trait association (MTA) analysis, probability values, and percent variation modelled by the markers were calculated using the GAPIT package via the KDCompute interface. The LD analysis showed that about 36% of loci pairs were in significant LD (p < 0.05 and r2 > 0.2) and 3.14% of the pairs were in complete LD. The MTAs studies revealed 20 significant MTAs (p < 0.001) with 11 markers. Four MTAs were identified for leaf area index, 13 for canopy temperature, one for chlorophyll content and two for normalized difference vegetation index. The markers explained 20.8% to 6.6% of the phenotypic variation observed. Most of the MTAs identified on the A subgenome were also identified on the respective homeologous chromosome on the B subgenome. This could be due to a common ancestor of the A and B genome which explains the linkage detected between markers lying on different chromosomes. The markers identified in this study can serve as useful genomic resources to initiate marker-assisted selection and trait introgression of groundnut for drought tolerance after further validation.

scholarly journals Exploring the genetic variability and diversity of pearl millet core collection germplasm for grain nutritional traits improvement

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mahalingam Govindaraj ◽  
Kedar N. Rai ◽  
Anand Kanatti ◽  
Hari D. Upadhyaya ◽  
Harshad Shivade ◽  
...  
Keyword(s):  
Genetic Variability ◽  
Pearl Millet ◽  
Core Collection ◽  
Germplasm Collection ◽  
Nutrient Content ◽  
Field Trials ◽  
Essential Nutrient ◽  
Micronutrient Malnutrition ◽  
Diverse Origin ◽  
Lower Magnitude

AbstractImproving essential nutrient content in staple food crops through biofortification breeding can overcome the micronutrient malnutrition problem. Genetic improvement depends on the availability of genetic variability in the primary gene pool. This study was aimed to ascertain the magnitude of variability in a core germplasm collection of diverse origin and predict pearl millet biofortification prospects for essential micronutrients. Germplasm accessions were evaluated in field trials at ICRISAT, India. The accessions differed significantly for all micronutrients with over two-fold variation for Fe (34–90 mg kg−1), Zn (30–74 mg kg−1), and Ca (85–249 mg kg−1). High estimates of heritability (> 0.81) were observed for Fe, Zn, Ca, P, Mo, and Mg. The lower magnitude of genotype (G) × environment (E) interaction observed for most of the traits implies strong genetic control for grain nutrients. The top-10 accessions for each nutrient and 15 accessions, from five countries for multiple nutrients were identified. For Fe and Zn, 39 accessions, including 15 with multiple nutrients, exceeded the Indian cultivars and 17 of them exceeded the biofortification breeding target for Fe (72 mg kg−1). These 39 accessions were grouped into 5 clusters. Most of these nutrients were positively and significantly associated among themselves and with days to 50% flowering and 1000-grain weight (TGW) indicating the possibility of their simultaneous improvement in superior agronomic background. The identified core collection accessions rich in specific and multiple-nutrients would be useful as the key genetic resources for developing biofortified and agronomically superior cultivars.

Sign in / Sign up

Export Citation Format

Share Document