scholarly journals A stochastic process modelling of maize phyllochron enables to characterize environmental and genetic effects

2021 ◽  
Author(s):  
S. Plancade ◽  
E. Marchadier ◽  
S. Huet ◽  
A. Ressayre ◽  
C. Noûs ◽  
...  
Keyword(s):  
Stochastic Process ◽  
Hypothesis Testing ◽  
Flowering Time ◽  
Growth Parameters ◽  
Divergent Selection ◽  
Accurate Estimation ◽  
Vegetative Development ◽  
Data Set ◽  
Maize Plants ◽  
The Impact

AbstractWe propose a flexible statistical model for phyllochron that enables to seasonal variations analysis and hypothesis testing, and demonstrate its efficiency on a data set from a divergent selection experiment on maize.The time between appearance of successive leaves or phyllochron enables to characterize the vegetative development of maize plants which determines their flowering time. Phyllochron is usually considered as constant over the development of a given plant, even though studies have demonstrated response of growth parameters to environmental variables. In this paper, we proposed a novel statistical approach for phyllochron analysis based on a stochastic process, which combines flexibility and a more accurate modelling than existing regression models. The model enables accurate estimation of the phyllochron associated with each leaf rank and enables hypothesis testing. We applied the model on an original maize dataset collected in fields from plants belonging to closely related genotypes originated from divergent selection experiments for flowering time conducted on two maize inbred lines. We showed that the main differences in phyllochron were not observed between selection populations (Early or Late), but rather ancestral lines, years of experimentation, and leaf ranks. Finally, we showed that phyllochron variations through seasons could be related to climate variations, even if the impact of each climatic variables individually was not clearly elucidated. All script and data can be found at https://doi.org/10.15454/CUEHO6

scholarly journals Maximum Likelihood Estimation of the VAR(1) Model Parameters with Missing Observations

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Helena Mouriño ◽  
Maria Isabel Barão
Keyword(s):  
Stochastic Process ◽  
Missing Data ◽  
Maximum Likelihood ◽  
Moving Average ◽  
Practical Importance ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Missing Observations ◽  
Data Set ◽  
The Impact

Missing-data problems are extremely common in practice. To achieve reliable inferential results, we need to take into account this feature of the data. Suppose that the univariate data set under analysis has missing observations. This paper examines the impact of selecting an auxiliary complete data set—whose underlying stochastic process is to some extent interdependent with the former—to improve the efficiency of the estimators for the relevant parameters of the model. The Vector AutoRegressive (VAR) Model has revealed to be an extremely useful tool in capturing the dynamics of bivariate time series. We propose maximum likelihood estimators for the parameters of the VAR(1) Model based on monotone missing data pattern. Estimators’ precision is also derived. Afterwards, we compare the bivariate modelling scheme with its univariate counterpart. More precisely, the univariate data set with missing observations will be modelled by an AutoRegressive Moving Average (ARMA(2,1)) Model. We will also analyse the behaviour of the AutoRegressive Model of order one, AR(1), due to its practical importance. We focus on the mean value of the main stochastic process. By simulation studies, we conclude that the estimator based on the VAR(1) Model is preferable to those derived from the univariate context.

scholarly journals Estimation of Staphylococcus aureus Growth Parameters from Turbidity Data: Characterization of Strain Variation and Comparison of Methods

2006 ◽  
Vol 72 (7) ◽  
pp. 4862-4870 ◽  
Author(s):  
R. Lindqvist
Keyword(s):  
Staphylococcus Aureus ◽  
Growth Rates ◽  
Growth Parameters ◽  
Growth Models ◽  
Viable Count ◽  
Detection Methods ◽  
Accurate Estimation ◽  
Data Set ◽  
Time To Detection ◽  
Strain Variability

ABSTRACT Turbidity methods offer possibilities for generating data required for addressing microorganism variability in risk modeling given that the results of these methods correspond to those of viable count methods. The objectives of this study were to identify the best approach for determining growth parameters based on turbidity data and use of a Bioscreen instrument and to characterize variability in growth parameters of 34 Staphylococcus aureus strains of different biotypes isolated from broiler carcasses. Growth parameters were estimated by fitting primary growth models to turbidity growth curves or to detection times of serially diluted cultures either directly or by using an analysis of variance (ANOVA) approach. The maximum specific growth rates in chicken broth at 17°C estimated by time to detection methods were in good agreement with viable count estimates, whereas growth models (exponential and Richards) underestimated growth rates. Time to detection methods were selected for strain characterization. The variation of growth parameters among strains was best described by either the logistic or lognormal distribution, but definitive conclusions require a larger data set. The distribution of the physiological state parameter ranged from 0.01 to 0.92 and was not significantly different from a normal distribution. Strain variability was important, and the coefficient of variation of growth parameters was up to six times larger among strains than within strains. It is suggested to apply a time to detection (ANOVA) approach using turbidity measurements for convenient and accurate estimation of growth parameters. The results emphasize the need to consider implications of strain variability for predictive modeling and risk assessment.

scholarly journals Effects of Fusarium verticillioides and Lactobacillus Strains Inoculation on Growth and Antioxidant Enzymes Activity of Zea mays Plants

2017 ◽  
Vol 25 (2) ◽  
pp. 67-74 ◽  
Author(s):  
Zohreh Akhavan Kharazian ◽  
Mahnaz Aghdasi ◽  
Gholamreza Salehi Jouzan ◽  
Majid Zamani
Keyword(s):  
Enzyme Activity ◽  
Antioxidant Enzymes ◽  
Growth Parameters ◽  
Fusarium Verticillioides ◽  
Maize Seedlings ◽  
Lactobacillus Pentosus ◽  
Enzymes Activity ◽  
Maize Plants ◽  
The Impact

Abstract The current research based on greenhouse experiment evaluates the impact of the Lactobacillus strains (Lactobacillus plantarum, Lactobacillus paralimentaris, Lactobacillus fermentum, Lactobacillus pentosus, and Lactobacillus buchneri) previously isolated from maize silage on the Fusarium verticillioides-infected maize plants. The growth parameters as well as catalase, superoxide dismutase, ascorbate peroxidase, and peroxidase antioxidant enzymes activity were investigated in one-month old seedlings, after inoculations with Fusarium or co-inoculations with Fusarium and the Lactobacillus strains. Application of Lactobacillus strains in maize seedlings significantly enhanced the plant growth and biomass. The best effect was observed when the L. buchneri was applied. It was revealed that inoculation with Fusarium stimulated antioxidant enzyme activity and co-inoculation with Lactobacillus strains reduced the enzyme activity, compared to Fusarium treatment alone. This is the first report that revealed the bioprotective role of Lactobacillus strains against F. verticillioides.

scholarly journals Simulation Model for Time to Flowering with Climatic and Genetic Inputs for Wild Chickpea

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1389
Author(s):  
Andrey Ageev ◽  
Abdulkadir Aydogan ◽  
Eric Bishop-von Wettberg ◽  
Sergey V. Nuzhdin ◽  
Maria Samsonova ◽  
...  
Keyword(s):  
Simulation Model ◽  
Flowering Time ◽  
Climatic Factors ◽  
Analytic Form ◽  
Day Length ◽  
Climate Change Scenarios ◽  
Data Set ◽  
Lower Elevation ◽  
River Valleys ◽  
The Impact

Accurate prediction of flowering time helps breeders to develop new varieties that can achieve maximal efficiency in a changing climate. A methodology was developed for the construction of a simulation model for flowering time in which a function for daily progression of the plant from one to the next phenological phase is obtained in analytic form by stochastic minimization. The resulting model demonstrated high accuracy on the recently assembled data set of wild chickpeas. The inclusion of genotype-by-climatic factors interactions accounted to 77% of accuracy in terms of root mean square error. It was found that the impact of minimal temperature is positively correlated with the longitude at primary collection sites, while the impact of day length is negatively correlated. It was interpreted as adaptation of accessions from highlands to lower temperatures and those from lower elevation river valleys to shorter days. We used bootstrap resampling to construct an ensemble of models, taking into account the influence of genotype-by-climatic factors interactions and applied it to forecast the time to flowering for the years 2021–2099, using generated daily weather in Turkey, and for different climate change scenarios. Although there are common trends in the forecasts, some genotypes and SNP groups have distinct trajectories.

scholarly journals Mitigation of adverse effects of salt stress on germination, growth, photosynthetic efficiency and yield in maize (Zea mays L.) through magnetopriming

2019 ◽  
Vol 72 (1) ◽  
Author(s):  
Lokesh Baghel ◽  
Sunita Kataria ◽  
Meeta Jain
Keyword(s):  
Salt Stress ◽  
Growth Parameters ◽  
Photosynthetic Performance ◽  
Physiological Characteristic ◽  
Tolerance Index ◽  
Seedling Vigor ◽  
Maize Seeds ◽  
Psii Photochemistry ◽  
Maize Plants ◽  
The Impact

The efficiency of magnetopriming was evaluated for mitigation of the detrimental effects of salt stress on maize germination, growth, photosynthesis, and yield of maize plants. Maize seeds were pretreated with 200 mT of static magnetic field (SMF) for 1 h to assess the impact of SMF on the germination, seedling vigor, growth of plant, photosynthetic performance, ROS content, and yield under salt stress. The seedling characteristics of maize were negatively influenced by salt stress. However, SMF-pretreated maize seeds showed relatively higher germination percentage and germination stress tolerance index as compared to untreated seeds in saline and nonsaline conditions. The detrimental effect of NaCl induced salt stress was also observed on growth, yield, and different physiological characteristic of maize plants. The results showed that SMF-pretreated seeds enhanced seedling vigor, growth parameters such as plant height, leaf area, and biomass accumulation at different concentrations of NaCl (0, 25, 50, 75, and 100 mM) as compared to untreated seeds. Photosynthetic pigments, quantum yield of PSII photochemistry (Fv/Fm), phenomenological fluxes such as electron transport per leaf CS (ETo/CSm) and density of reaction centers (RC/CSm), the performance index (PI) were high in the leaves of plants that emerged from SMF-pretreated seeds as compared to untreated seeds. This stimulatory effect of SMF treatment of seeds was also revealed in the rate of photosynthesis and stomatal conductance, which results in improved yield of maize plants under saline conditions. The leaves from plants of SMF-treated seeds showed decreased hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) when compared with untreated seeds in both conditions. SMF ameliorates the adverse effect of salt stress in maize plants, by reducing H<sub>2</sub>O<sub>2</sub> and increasing growth, photosynthetic performance, and yield under salt stress. For improvement of salt tolerance, magnetopriming with SMF of 200 mT for 1 h to dry seeds of maize can be efficiently used as a presowing treatment.

Age at Exposure to Parental Suicide and the Subsequent Risk of Suicide in Young People

Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kuan-Ying Lee ◽  
Chung-Yi Li ◽  
Kun-Chia Chang ◽  
Tsung-Hsueh Lu ◽  
Ying-Yeh Chen
Keyword(s):  
Young People ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Birth Registry ◽  
Data Set ◽  
Parental Suicide ◽  
The Impact ◽  
Age At Exposure

Abstract. Background: We investigated the age at exposure to parental suicide and the risk of subsequent suicide completion in young people. The impact of parental and offspring sex was also examined. Method: Using a cohort study design, we linked Taiwan's Birth Registry (1978–1997) with Taiwan's Death Registry (1985–2009) and identified 40,249 children who had experienced maternal suicide (n = 14,431), paternal suicide (n = 26,887), or the suicide of both parents (n = 281). Each exposed child was matched to 10 children of the same sex and birth year whose parents were still alive. This yielded a total of 398,081 children for our non-exposed cohort. A Cox proportional hazards model was used to compare the suicide risk of the exposed and non-exposed groups. Results: Compared with the non-exposed group, offspring who were exposed to parental suicide were 3.91 times (95% confidence interval [CI] = 3.10–4.92 more likely to die by suicide after adjusting for baseline characteristics. The risk of suicide seemed to be lower in older male offspring (HR = 3.94, 95% CI = 2.57–6.06), but higher in older female offspring (HR = 5.30, 95% CI = 3.05–9.22). Stratified analyses based on parental sex revealed similar patterns as the combined analysis. Limitations: As only register-­based data were used, we were not able to explore the impact of variables not contained in the data set, such as the role of mental illness. Conclusion: Our findings suggest a prominent elevation in the risk of suicide among offspring who lost their parents to suicide. The risk elevation differed according to the sex of the afflicted offspring as well as to their age at exposure.

State Medical Boards' Perceptions of a Minimum Data Set and Current Practices for Collecting Physician Information

2013 ◽  
Vol 99 (4) ◽  
pp. 40-45 ◽  
Author(s):  
Aaron Young ◽  
Philip Davignon ◽  
Margaret B. Hansen ◽  
Mark A. Eggen
Keyword(s):  
Media Coverage ◽  
The United States ◽  
Minimum Data Set ◽  
Direct Patient Care ◽  
Physician Workforce ◽  
Data Set ◽  
Minimum Data ◽  
State Medical Boards ◽  
The Impact ◽  
Current Practices

ABSTRACT Recent media coverage has focused on the supply of physicians in the United States, especially with the impact of a growing physician shortage and the Affordable Care Act. State medical boards and other entities maintain data on physician licensure and discipline, as well as some biographical data describing their physician populations. However, there are gaps of workforce information in these sources. The Federation of State Medical Boards' (FSMB) Census of Licensed Physicians and the AMA Masterfile, for example, offer valuable information, but they provide a limited picture of the physician workforce. Furthermore, they are unable to shed light on some of the nuances in physician availability, such as how much time physicians spend providing direct patient care. In response to these gaps, policymakers and regulators have in recent years discussed the creation of a physician minimum data set (MDS), which would be gathered periodically and would provide key physician workforce information. While proponents of an MDS believe it would provide benefits to a variety of stakeholders, an effort has not been attempted to determine whether state medical boards think it is important to collect physician workforce data and if they currently collect workforce information from licensed physicians. To learn more, the FSMB sent surveys to the executive directors at state medical boards to determine their perceptions of collecting workforce data and current practices regarding their collection of such data. The purpose of this article is to convey results from this effort. Survey findings indicate that the vast majority of boards view physician workforce information as valuable in the determination of health care needs within their state, and that various boards are already collecting some data elements. Analysis of the data confirms the potential benefits of a physician minimum data set (MDS) and why state medical boards are in a unique position to collect MDS information from physicians.

Impact of Pseudomonas putida on the Growth Parameters of Fenugreek (Trigonella foenum- graecum L.): A Traditional Herbal Boon for Rural Areas

2017 ◽  
Vol 5 (2) ◽  
pp. 93-96
Author(s):  
Shashi Kant Shukla ◽  
◽  
Awadhesh Kumar ◽  
Anupam Dikshit ◽  
◽  
...  
Keyword(s):  
Pseudomonas Putida ◽  
Rural Areas ◽  
Growth Parameters ◽  
Leguminous Plant ◽  
Food Protein ◽  
Botany Department ◽  
Medicinal Value ◽  
Randomized Design ◽  
Trigonella Foenum Graecum L ◽  
The Impact

The present study aims the impact of Pseudomonas putida on different growth parameters of Trigonella sp., a leguminous plant to support the requirement of food, protein along with their medicinal value in the rural areas of India. A pot experiment was arranged based on completely randomized design with four replications at Biological Product Laboratory, Botany Department, University of Allahabad. Treatments were given at the seed level with one of control. Results indicated that application of P. putida significantly improved vegetative growth and showed an edge on the growth of the fenugreek as compared to the control.

The Impact of Green Labels on U.S. Hotel Net Operating Income: Operating Statements Analyses

2019 ◽  
Vol 11 (1) ◽  
pp. 156-173
Author(s):  
Spenser Robinson ◽  
A.J. Singh
Keyword(s):  
Environmental Design ◽  
Green Buildings ◽  
Small Sample ◽  
Sample Survey ◽  
Data Set ◽  
Operating Income ◽  
Energy Star ◽  
The Impact ◽  
Industry Professionals

This paper shows Leadership in Energy and Environmental Design (LEED) certified hospitality properties exhibit increased expenses and earn lower net operating income (NOI) than non-certified buildings. ENERGY STAR certified properties demonstrate lower overall expenses than non-certified buildings with statistically neutral NOI effects. Using a custom sample of all green buildings and their competitive data set as of 2013 provided by Smith Travel Research (STR), the paper documents potential reasons for this result including increased operational expenses, potential confusion with certified and registered LEED projects in the data, and qualitative input. The qualitative input comes from a small sample survey of five industry professionals. The paper provides one of the only analyses on operating efficiencies with LEED and ENERGY STAR hospitality properties.

Does Tax Increment Financing Pass the “But-for” Test in Missouri?

2019 ◽  
Vol 33 (3) ◽  
pp. 187-202
Author(s):  
Ahmed Rachid El-Khattabi ◽  
T. William Lester
Keyword(s):  
Economic Development ◽  
Kansas City ◽  
Time Series Data ◽  
Local Level ◽  
Conclusive Evidence ◽  
Series Data ◽  
Tax Increment Financing ◽  
Data Set ◽  
Development Indicators ◽  
The Impact

The use of tax increment financing (TIF) remains a popular, yet highly controversial, tool among policy makers in their efforts to promote economic development. This study conducts a comprehensive assessment of the effectiveness of Missouri’s TIF program, specifically in Kansas City and St. Louis, in creating economic opportunities. We build a time-series data set starting 1990 through 2012 of detailed employment levels, establishment counts, and sales at the census block-group level to run a set of difference-in-differences with matching estimates for the impact of TIF at the local level. Although we analyze the impact of TIF on a wide set of indicators and across various industry sectors, we find no conclusive evidence that the TIF program in either city has a causal impact on key economic development indicators.

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