scholarly journals Construction of Genetic Linkage Map and QTL Analysis of Sink-Size Traits in Pearl Millet (Pennisetum glaucum)

ISRN Genetics ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
V. Vengadessan ◽  
K. N. Rai ◽  
J. R. Kannan Bapu ◽  
C. T. Hash ◽  
R. Bhattacharjee ◽  
...  
Keyword(s):  
Grain Size ◽  
Linkage Map ◽  
Pearl Millet ◽  
Phenotypic Variation ◽  
Mapping Population ◽  
Pennisetum Glaucum ◽  
Data Sets ◽  
Panicle Length ◽  
Data Set ◽  
Sink Size

A linkage map, primarily based on SSCP-SNP markers, was constructed using 188 F2:3 mapping population progenies produced from a cross between two pearl millet inbred lines having diverse parentage. The skeleton linkage map covered 1019 cM and it comprised of 44 markers distributed across the seven linkage groups. Average adjacent-marker intervals ranged from 14 cM on LG1 to 38 cM on LG6, with an overall mean of 23 cM. Using the F2 linkage map and phenotypic data from the F2 and F2:3 generations of the mapping population, a total of 18 putative QTLs were detected for the three sink-size components. Eight QTLs explained 42.7% of observed phenotypic variation for panicle length using the F2:3 data set. For panicle diameter, 5 QTLs explained 45.8% of observed phenotypic variation. Similarly for grain size, 5 QTLs explained 29.6% of phenotypic variation. Genomic regions associated with panicle length, panicle diameter, and grain size were comapped on LG6 between Xpsms88 and Xpsms2270, indicating the existence of a gene or gene cluster. The QTLs for panicle length on LG2 and LG6 (LOD>3 in both F2 and F2:3 data sets), for panicle diameter on LG2 and LG3 (LOD>14 in the F2:3 data set), and for grain size on LG3 and LG6 (LOD>3 in both F2 and F2:3 data sets) were identified as promising candidates for validation prior to possible application in marker-assisted breeding.

scholarly journals Effects of Variety and Nitrogen Levels on the Performance of Pearl Millet: Pennisetum Glaucum (L.) R. BR.

2020 ◽  
Vol 1 (4) ◽  
pp. 188-196
Author(s):  
S. Isah ◽  
A. U. Gbanguba ◽  
Y. Abdullah ◽  
T. S. Bubuche ◽  
T. Mohammed
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Pearl Millet ◽  
Full Text ◽  
Pennisetum Glaucum ◽  
Panicle Length ◽  
Dry Land ◽  
Nitrogen Levels ◽  
Cropping Seasons ◽  
Panicle Weight

The trials were conducted in 2010 and 2011 rainy seasons at Usmanu Danfodiyo University, Sokoto Teaching and Research Dry Land Farm, Dundaye, Nigeria to determine the effects of variety and nitrogen levels on performance of  (SOSAT c-88 and Zango millet varieties). Data collected were on Stand count, tiller count, plant height and panicle length. Others included panicle weight and grain yield. All data collected were subjected to analysis of variance (ANOVA). The results SOSAT c-88 and Zango millet indicated that millet varieties have no significant effect on both stand and tiller production throughout the sampling periods though nitrogen levels has significant on tiller production at 6 weeks after planting of both 2010 and 2011 cropping seasons. Panicle length was affected by millet varieties and nitrogen levels in both cropping seasons. Improve millet variety Sosat c-88 gave higher grain yield while 80 kg ha-1 and 120 kg ha-1produced significant higher millet grain yield hence should be practiced. Doi: 10.28991/HEF-2020-01-04-04 Full Text: PDF

scholarly journals Pearl millet [Pennisetum glaucum (L.) R. Br.] consensus linkage map constructed using four RIL mapping populations and newly developed EST-SSRs

BMC Genomics ◽  
2013 ◽  
Vol 14 (1) ◽  
pp. 159 ◽  
Author(s):  
Vengaldas Rajaram ◽  
Thirunavukkarasu Nepolean ◽  
Senapathy Senthilvel ◽  
Rajeev K Varshney ◽  
Vincent Vadez ◽  
...  
Keyword(s):  
Linkage Map ◽  
Pearl Millet ◽  
Pennisetum Glaucum ◽  
Mapping Populations

scholarly journals Performance of Different Pearl Millet Genotypes under Irrigated Conditions

2014 ◽  
Vol 3 (3) ◽  
pp. 154-163
Author(s):  
Jamal Ishaq ◽  
Silvestro Meseka
Keyword(s):  
Grain Yield ◽  
Pearl Millet ◽  
Yield Components ◽  
Pennisetum Glaucum ◽  
Block Design ◽  
Broad Sense Heritability ◽  
Panicle Length ◽  
Randomized Complete Block Design ◽  
Head Weight ◽  
Coefficient Of Variability

Thirty four genotypes of pearl millet( Pennisetum glaucum (L.) R. Br) were evaluated at Sudan. Including two released varieties, Ugandi and Ashana at Gezira Research Farm (GRF) and Rahad Research Farm(RRS) in the autumn of 2009. The experiment was arranged in randomized complete block design with three replications. Grain yield and some yield components including number of productive tillers and panicle length, varied significantly among the thirty four genotypes. Mean of grain yield for all genotypes across sites was 1.3 t/ ha-1. Sadag Togo had the highest grain yield (1.7 ha-1) followed by Okashana-3 (1.6 t/ha-1), while IP 19745 had lowest grain yield (0.8 t/ha-1) across tow site.Okashana-3 out yielded the best than check (Ashana). The combined Result for Genotypic coefficient of variability and broad sense heritability estimates grain yield and head weight varied significantly among the thirty four genotypes. DOI: http://dx.doi.org/10.3126/ije.v3i3.11075 International Journal of Environment Vol.3(3) 2014: 154-163

scholarly journals Transition From Wild to Domesticated Pearl Millet (Pennisetum glaucum) Revealed in Ceramic Temper at Three Middle Holocene Sites in Northern Mali

2021 ◽  
Author(s):  
Dorian Q. Fuller ◽  
Aleese Barron ◽  
Louis Champion ◽  
Christian Dupuy ◽  
Dominique Commelin ◽  
...  
Keyword(s):  
Grain Size ◽  
Pearl Millet ◽  
Pennisetum Glaucum ◽  
Morphological Evolution ◽  
Average Width ◽  
The Third ◽  
Western Africa ◽  
Average Grain Size ◽  
Third Millennium ◽  
Third Millennium Bc

AbstractImprints of domesticated pearl millet (Pennisetum glaucum (L.) R. Br.) spikelets, observed as temper in ceramics dating to the third millennium BC, provide the earliest evidence for the cultivation and domestication process of this crop in northern Mali. Additional sherds from the same region dating to the fifth and fourth millennium BC were examined and found to have pearl millet chaff with wild morphologies. In addition to studying sherds by stereomicroscopy and subjecting surface casts to scanning electron microscopy (SEM), we also deployed X-ray microcomputed tomography (microCT) on eleven sherds. This significantly augmented the total dataset of archaeological pearl millet chaff remains from which to document the use of the wild pearl millet as ceramic temper and the evolution of its morphology over time. Grain sizes were also estimated from spikelets preserved in the ceramics. Altogether, we are now able to chart the evolution of domesticated pearl millet in western Africa using three characteristics: the evolution of nonshattering stalked involucres; the appearance of multiple spikelet involucres, usually paired spikelets; and the increase in grain size. By the fourth millennium BC, average grain breadth had increased by 28%, although spikelet features otherwise resemble the wild type. In the third millennium BC, the average width of seeds is 38% greater than that of wild seeds, while other qualitative features of domestication are indicated by the presence of paired spikelets and the appearance of nondehiscent, stalked involucres. Nonshattering spikelets had probably become fixed by around 2000 BC, while increases in average grain size continued into the second millennium BC. These data now provide a robust sequence for the morphological evolution of domesticated pearl millet, the first indigenous crop domesticated in western Africa.

scholarly journals Application of the mineral liberation analysis (MLA) for extraction of grain size and shape measurements in siliciclastic sedimentary rocks

2018 ◽  
Vol 66 ◽  
pp. 02002
Author(s):  
Joanna Pszonka ◽  
Dariusz Sala
Keyword(s):  
Grain Size ◽  
Computer Software ◽  
Data Sets ◽  
Data Set ◽  
X Ray ◽  
Mineral Liberation ◽  
Gravity Flows ◽  
Backscattered Electron ◽  
Grain Size And Shape ◽  
Liberation Analysis

The mineral liberation analysis setup (MLA) consists of a scanning electron microscope (SEM) - based backscattered electron (BSE) image with an energy dispersive X-ray system (EDX) for elemental analysis and a computer software that integrates images and X-ray identification of minerals and maps their distribution. Thereby, various quantitative and qualitative data sets are collected including grain size distribution and shape parameters such as aspect ratio, shape factor and angularity. Other techniques, e.g. the Gazzi-Dickinson point counting method or frequently questionable image analysis software to extract data for textural analysis are time consuming, strenuous and with limitations that need to be addressed. Significant productivity of the mineral liberation analysis provides statistical representation and thereby stringent arguments to detect and suggest some potential solving in uncertainty and complexity of the submarine gravity flows phenomenon that is extremely difficult to monitor, however volumetrically the most significant processes moving sediments on Earth. The mineral liberation analysis seems to be one of the most suitable method to acquire such data set.

Analysis of genetic variability and correlation among traits in exotic germplasm of pearl millet [Pennisetum glaucum (L.) R. Br.]

2016 ◽  
Vol 50 (1) ◽  
Author(s):  
Om Vir Singh ◽  
A. K. Singh
Keyword(s):  
Genetic Variability ◽  
Grain Yield ◽  
Pearl Millet ◽  
Pennisetum Glaucum ◽  
Block Design ◽  
Correlation Coefficients ◽  
Genetic Advance ◽  
Panicle Length ◽  
Hot Arid Climate ◽  
High Heritability

The 27 accessions of pearl millet of African origin were studied during <italic>kharif</italic> 2013 and 2014 in a randomized complete block design in the hot arid climate of Rajasthan. The study was conducted to assess the magnitude of presence of genetic variability and associations among characters namely, grain yield per plant (gm.), number of tillers per plant, plant height (cm), panicle length (cm), panicle diameter (cm), number of leaves per plant, days to 50% flowering and test weight(gm.). The result showed that genetic variability was present among the accessions for all studied characters. The estimated PCV (%) and GCV (%) were high for all characters. The broad sense heritability (%) and genetic advance (% of mean) estimates were also high for all studied characters. The number of tillers per plant, panicle length (cm), panicle diameter (cm) and days to 50% flowering had positive and significant genotypic, phenotypic and environmental correlation coefficients with grain yield per plant. The presence of genetic variability, high heritability and genetic advance and association with grain yield of number of tillers per plant, panicle length (cm), panicle diameter (cm) and days to 50% flowering amenable them for selection and enhancement of grain yield.

The social wasp Vespula germanica (Fabricius) (Hymenoptera: Vespidae) population dynamics in England over 39 years.

2018 ◽  
Vol 154 (2) ◽  
pp. 149-155
Author(s):  
Michael Archer
Keyword(s):  
Population Dynamics ◽  
Population Dynamic ◽  
Ecological Factors ◽  
Social Wasp ◽  
Data Sets ◽  
Data Set ◽  
Vespula Germanica ◽  
The Social ◽  
Minimum Number ◽  
Suction Traps

1. Yearly records of worker Vespula germanica (Fabricius) taken in suction traps at Silwood Park (28 years) and at Rothamsted Research (39 years) are examined. 2. Using the autocorrelation function (ACF), a significant negative 1-year lag followed by a lesser non-significant positive 2-year lag was found in all, or parts of, each data set, indicating an underlying population dynamic of a 2-year cycle with a damped waveform. 3. The minimum number of years before the 2-year cycle with damped waveform was shown varied between 17 and 26, or was not found in some data sets. 4. Ecological factors delaying or preventing the occurrence of the 2-year cycle are considered.

Predictive and Descriptive CoMFA Models: The Effect of Variable Selection

2018 ◽  
Vol 21 (2) ◽  
pp. 117-124 ◽  
Author(s):  
Bakhtyar Sepehri ◽  
Nematollah Omidikia ◽  
Mohsen Kompany-Zareh ◽  
Raouf Ghavami
Keyword(s):  
Variable Selection ◽  
Predictive Power ◽  
Selection Method ◽  
Data Sets ◽  
Data Set ◽  
Comfa Model ◽  
Variable Selection Method

Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Materials & Methods: Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Result & Conclusion: Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields.

Human Activity Recognition using Fourier Transform Inspired Deep Learning Combination Model

2019 ◽  
Vol 9 (1) ◽  
pp. 16-31
Author(s):  
Kyungkoo Jun
Keyword(s):  
Fourier Transform ◽  
Deep Learning ◽  
Short Term Memory ◽  
Window Size ◽  
Sensor Data ◽  
Data Sets ◽  
Data Set ◽  
Proposed Model ◽  
Testing Data ◽  
Labeling Scheme

Background & Objective: This paper proposes a Fourier transform inspired method to classify human activities from time series sensor data. Methods: Our method begins by decomposing 1D input signal into 2D patterns, which is motivated by the Fourier conversion. The decomposition is helped by Long Short-Term Memory (LSTM) which captures the temporal dependency from the signal and then produces encoded sequences. The sequences, once arranged into the 2D array, can represent the fingerprints of the signals. The benefit of such transformation is that we can exploit the recent advances of the deep learning models for the image classification such as Convolutional Neural Network (CNN). Results: The proposed model, as a result, is the combination of LSTM and CNN. We evaluate the model over two data sets. For the first data set, which is more standardized than the other, our model outperforms previous works or at least equal. In the case of the second data set, we devise the schemes to generate training and testing data by changing the parameters of the window size, the sliding size, and the labeling scheme. Conclusion: The evaluation results show that the accuracy is over 95% for some cases. We also analyze the effect of the parameters on the performance.

scholarly journals An Algorithm for the Removal of Cosmic Ray Artifacts in Spectral Data Sets

2019 ◽  
Vol 73 (8) ◽  
pp. 893-901
Author(s):  
Sinead J. Barton ◽  
Bryan M. Hennelly
Keyword(s):  
Cosmic Ray ◽  
Data Sets ◽  
Biological Cells ◽  
Statistical Classification ◽  
Signal To Noise ◽  
Multivariate Statistical ◽  
Data Set ◽  
Artefact Removal ◽  
Single Capture ◽  
Acquisition Method

Cosmic ray artifacts may be present in all photo-electric readout systems. In spectroscopy, they present as random unidirectional sharp spikes that distort spectra and may have an affect on post-processing, possibly affecting the results of multivariate statistical classification. A number of methods have previously been proposed to remove cosmic ray artifacts from spectra but the goal of removing the artifacts while making no other change to the underlying spectrum is challenging. One of the most successful and commonly applied methods for the removal of comic ray artifacts involves the capture of two sequential spectra that are compared in order to identify spikes. The disadvantage of this approach is that at least two recordings are necessary, which may be problematic for dynamically changing spectra, and which can reduce the signal-to-noise (S/N) ratio when compared with a single recording of equivalent duration due to the inclusion of two instances of read noise. In this paper, a cosmic ray artefact removal algorithm is proposed that works in a similar way to the double acquisition method but requires only a single capture, so long as a data set of similar spectra is available. The method employs normalized covariance in order to identify a similar spectrum in the data set, from which a direct comparison reveals the presence of cosmic ray artifacts, which are then replaced with the corresponding values from the matching spectrum. The advantage of the proposed method over the double acquisition method is investigated in the context of the S/N ratio and is applied to various data sets of Raman spectra recorded from biological cells.

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