scholarly journals Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

2015 ◽  
Vol 66 (9) ◽  
pp. 947 ◽  
Author(s):  
Joanne De Faveri ◽  
Arūnas P. Verbyla ◽  
Wayne S. Pitchford ◽  
Shoba Venkatanagappa ◽  
Brian R. Cullis
Keyword(s):  
Statistical Methods ◽  
Temporal Correlation ◽  
Field Trials ◽  
Model Fit ◽  
Natural Sources ◽  
Variety Selection ◽  
Sources Of Variation ◽  
Harvest Data ◽  
Insight Into

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.

Depression: An insight into Heterocyclic and Cyclic Hydrocarbon Compounds inspired from Natural Sources

2021 ◽  
Vol 19 ◽  
Author(s):  
Abdul Jalil Shah ◽  
Reyaz Hassan Mir ◽  
Roohi Mohi-ud-din ◽  
Faheem Hyder Pottoo ◽  
Mubashir Hussain Masoodi ◽  
...  
Keyword(s):  
Gaba Receptors ◽  
Herbal Medicines ◽  
Aminobutyric Acid ◽  
Cyclic Hydrocarbon ◽  
Natural Sources ◽  
Drug Candidates ◽  
Signalling Molecules ◽  
Symptoms Of Depression ◽  
Insight Into

: Depression, a well know mental disorder has global prevalence, nearly affecting 17% of population. Due to various limitations of the currently available drugs, people have been adopting traditional herbal medicines to alleviate the symptoms of depression. It is notable to mention that natural products, their derivatives, and their analogs are the main source for new drug candidates in depression. The mechanisms include interplay with γ-aminobutyric acid (GABA) receptors, serotonergic, dopaminergic noradrenergic systems, and elevation of BDNF levels. The focus of this review is to revisit the role of signalling molecules in depression and highlight the use of plant-derived natural compounds to counter depression in the CNS.

Tolerance of 12 Sugarbeet Varieties to Applications ofs-Metolachlor and Dimethenamid-P

2008 ◽  
Vol 22 (4) ◽  
pp. 699-706 ◽  
Author(s):  
Scott L. Bollman ◽  
Christy L. Sprague
Keyword(s):  
Disease Resistance ◽  
Weed Control ◽  
Herbicide Tolerance ◽  
Field Trials ◽  
Sugar Yield ◽  
Varietal Differences ◽  
Leaf Stage ◽  
Variety Selection

Sugarbeet varieties vary in their response to herbicides.s-Metolachlor and dimethenamid-P were recently registered for use in sugarbeet. Field trials were conducted in Michigan in 2004, 2005, and 2006 to evaluate the response of 12 sugarbeet varieties tos-metolachlor and dimethenamid-P applied PRE and POST to two-leaf and four-leaf stage sugarbeet.s-Metolachlor and dimethenamid-P reduced sugarbeet density when rainfall occurred within 7 d of the PRE applications. Dimethenamid-P PRE caused the most injury across all varieties followed bys-metolachlor PRE. Applying dimethenamid-P POST to two-leaf sugarbeet injured plants more thans-metolachlor applied POST to two- and four-leaf stage sugarbeet. The least amount of sugarbeet injury from dimethenamid-P was from POST applications at the four-leaf stage. Sugarbeet varietal differences were most pronounced from PRE applications of both herbicides and from the POST two-leaf application of dimethenamid-P. Of the 12 sugarbeet varieties evaluated, Hilleshog 2771RZ and Beta 5833R were the most tolerant, whereas Hilleshog 7172RZ was typically the most sensitive variety to these herbicides. Growers will probably not choose varieties based on herbicide tolerance alone, but instead base variety selection on sugar yield and disease resistance. However, if a grower has chosen a particular variety, this information could assist in assessing the risk of usings-metolachlor or dimethenamid-P for weed control.

Performance Analysis of OWC Using NOP Technique

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Ghanendra Kumar ◽  
Chakresh Kumar
Keyword(s):  
Performance Analysis ◽  
Statistical Methods ◽  
Expectation Maximization ◽  
Communication System ◽  
Review Paper ◽  
Temporal Correlation ◽  
Step Algorithm

AbstractIn this review paper, the turbulence of the channel through which the light photons are scattered has been modeled. The channel here is essentially the lower lithosphere. A two-step algorithm called the Method of Expectation–Maximization has been used for the analysis and calculations of the parameters involved. Statistical methods have been used to check temporal correlation and the tolerance of the communication system involved. The simulations and results have been presented and the conclusions show decent performance. The approaches have been applied to the UV scattering channel experiment, NLOS experiment and for link gain at a distance of 0.5 km.

scholarly journals Keyword Categorization using Statistical Methods

TEM Journal ◽  
2021 ◽  
pp. 1377-1384
Author(s):  
Dominika Krasňanská ◽  
Silvia Komara ◽  
Mária Vojtková
Keyword(s):  
Machine Learning ◽  
Detailed Analysis ◽  
Search Engine ◽  
Statistical Methods ◽  
Online Advertising ◽  
The Internet ◽  
Keyword Analysis ◽  
Total Analysis Time ◽  
Total Analysis ◽  
Insight Into

Keyword analysis is a way to gain insight into market behaviour. It is a detailed analysis of words and phrases that are relevant to the selected area. Keyword analysis should be the first step in any search engine optimization, as it reveals what keywords users enter into search engines when searching the Internet. The keyword categorization process takes up almost half of the total analysis time, as it is not automated. There is currently no known tool in the online advertising market that facilitates keyword categorization. The main goal of this paper is to streamline the process of keyword analysis using selected statistical methods of machine learning applied in the categorization of a specific example.

scholarly journals Environmental inactivation and irrigation-mediated regrowth of Escherichia coli O157:H7 on romaine lettuce when inoculated in a fecal slurry matrix

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6591 ◽  
Author(s):  
Jennifer A. Chase ◽  
Melissa L. Partyka ◽  
Ronald F. Bond ◽  
Edward R. Atwill
Keyword(s):  
Escherichia Coli ◽  
Field Trials ◽  
Inactivation Rate ◽  
Bacterial Inactivation ◽  
Romaine Lettuce ◽  
E Coli ◽  
Log Reduction ◽  
Salinas Valley ◽  
Kinetics Of ◽  
Insight Into

Field trials were conducted in July–August and October 2012 to quantify the inactivation rate of Escherichia coli O157:H7 when mixed with fecal slurry and applied to romaine lettuce leaves. Lettuce was grown under commercial conditions in Salinas Valley, California. One-half milliliter of rabbit, chicken, or pig fecal slurry, containing an average of 4.05 × 107 CFU E. coli O157:H7 (C0), was inoculated onto the upper (adaxial) surface of a lower leaf on 288 heads of lettuce per trial immediately following a 2.5 h irrigation event. To estimate the bacterial inactivation rate as a function of time, fecal matrix, irrigation and seasonal climate effects, sets of lettuce heads (n = 28) were sampled each day over 10 days and the concentration of E. coli O157:H7 (Ct) determined. E. coli O157:H7 was detected on 100% of heads during the 10-day duration, with concentrations ranging from ≤340 MPN/head (∼5-log reduction) to >3.45 × 1012 MPN/head (∼5-log growth). Relative to C0, on day 10 (Ct = 12) we observed an overall 2.6-log and 3.2-log mean reduction of E. coli O157:H7 in July and October, respectively. However, we observed relative maximum concentrations due to bacterial growth on day 6 (maximum Ct = 8) apparently stimulated by foliar irrigation on day 5. From this maximum there was a mean 5.3-log and 5.1-log reduction by day 10 (Ct = 12) for the July and October trials, respectively. This study provides insight into the inactivation and growth kinetics of E. coli O157:H7 on romaine lettuce leaves under natural field conditions. This study provides evidence that harvesting within 24 h post irrigation has the potential to increase the concentration of E. coli O157:H7 contamination, if present on heads of romaine lettuce; foliar irrigation can temporarily stimulate substantial regrowth of E. coli O157:H7.

scholarly journals Insight into regional similarities of Serbian districts using appropriate statistical methods

2017 ◽  
Vol 14 (2) ◽  
pp. 23-42
Author(s):  
Blazenka Popovic ◽  
Radojka Maletic
Keyword(s):  
Statistical Methods ◽  
Insight Into

scholarly journals Robust modeling of additive and nonadditive variation with intuitive inclusion of expert knowledge

Genetics ◽  
2021 ◽  
Author(s):  
Ingeborg Gullikstad Hem ◽  
Maria Lie Selle ◽  
Gregor Gorjanc ◽  
Geir-Arne Fuglstad ◽  
Andrea Riebler
Keyword(s):  
Expert Knowledge ◽  
Future Research ◽  
Central Component ◽  
Research Areas ◽  
Model Parameterization ◽  
Parent Selection ◽  
Variety Selection ◽  
Sources Of Variation ◽  
Likelihood Approach

Abstract We propose a novel Bayesian approach that robustifies genomic modeling by leveraging expert knowledge (EK) through prior distributions. The central component is the hierarchical decomposition of phenotypic variation into additive and nonadditive genetic variation, which leads to an intuitive model parameterization that can be visualized as a tree. The edges of the tree represent ratios of variances, for example broad-sense heritability, which are quantities for which EK is natural to exist. Penalized complexity priors are defined for all edges of the tree in a bottom-up procedure that respects the model structure and incorporates EK through all levels. We investigate models with different sources of variation and compare the performance of different priors implementing varying amounts of EK in the context of plant breeding. A simulation study shows that the proposed priors implementing EK improve the robustness of genomic modeling and the selection of the genetically best individuals in a breeding program. We observe this improvement in both variety selection on genetic values and parent selection on additive values; the variety selection benefited the most. In a real case study, EK increases phenotype prediction accuracy for cases in which the standard maximum likelihood approach did not find optimal estimates for the variance components. Finally, we discuss the importance of EK priors for genomic modeling and breeding, and point to future research areas of easy-to-use and parsimonious priors in genomic modeling.

A Nordic heavy haul experience and best practices

2017 ◽  
Vol 231 (7) ◽  
pp. 794-804 ◽  
Author(s):  
Matthias Asplund ◽  
Stephen M Famurewa ◽  
Wolfgang Schoech
Keyword(s):  
Best Practice ◽  
Rolling Contact Fatigue ◽  
Contact Fatigue ◽  
Field Trials ◽  
Rolling Contact ◽  
Traffic Load ◽  
Seasonal Impact ◽  
Heavy Haul ◽  
Insight Into

This article summarizes the experiences gained at the Nordic heavy haul line “Malmbanan” located in Northern Sweden and Norway during the years 2007 to 2015 and the resulting best practice. Unique long-term information of field trials and monitoring from the on-going development for maintenance of rail and wheel has been described. The reported results come from the rail profile measurements using MiniProf and HC-recordings with Eddy-current devices and visual inspection on 43 test sections. The monitoring has been continuous since the project started, to reveal a deep insight into the complex wheel–rail interaction and provide understanding of the effect of applying optimized specifications. This was particularly important in view of the increasing traffic load that contributed to doubling of the yearly grinding campaigns. This article presents in particular the new MB5 profile, the wear rate behaviour between two different curves, impacts of gauge widening on rail rolling contact fatigue and the speed of gauge widening as well as the seasonal impact on the crack propagation. The presently applied maintenance strategy is discussed together with other experiences. The article finishes with some conclusions and an outlook into further work.

scholarly journals Potential distribution of invasive boxwood blight pathogen (Calonectria pseudonaviculata) as predicted by process-based and correlative models

2021 ◽  
Author(s):  
Brittany Barker ◽  
Leonard Coop ◽  
Chuanxue Hong
Keyword(s):  
Potential Distribution ◽  
Climatic Factors ◽  
Model Performance ◽  
Model Fit ◽  
Model Predictions ◽  
Correlative Models ◽  
Response Measures ◽  
Ascomycete Fungi ◽  
Reliability And Robustness ◽  
Insight Into

Boxwood blight, caused by the ascomycete fungi Calonectria pseudonaviculata and C. henricotiae, is an emerging plant disease of boxwood (Buxus spp.) that has had devastating impacts on the health and productivity of boxwood in both the horticultural sector and native ecosystems. In this study, we predicted the potential distribution of C. pseudonaviculata at regional and global scales and explored how climatic factors shape its known range limits. Our workflow combined multiple modeling algorithms to enhance the reliability and robustness of predictions. We produced a process-based climatic suitability model in the CLIMEX program and combined outputs of six different correlative modeling algorithms to generate an ensemble correlative model. All models were fit and validated using an occurrence record dataset (N = 292 records from 24 countries) comprised of positive detections of C. pseudonaviculata from across its entire known invaded range. Evaluations of model performance provided validation of good model fit for all models. A consensus map of CLIMEX and ensemble correlative model predictions indicated that not-yet-invaded areas in eastern and southern Europe and in the southeastern, midwestern, and Pacific coast regions of North America are climatically suitable for establishment. Most regions of the world where Buxus and its congeners are native are also at risk of establishment, which suggests that C. pseudonaviculata should be able to significantly expand its range globally if susceptible hosts exist. Our findings provide the first insight into the global invasion threat of boxwood blight, and are valuable to stakeholders who need to know where to focus surveillance efforts for early detection and rapid response measures to prevent or slow the spread of the disease.

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