Effect of Experimental Blocking on the Suppression of Spatial Dependence Potentially Attributable to Physicochemical Properties of Soils

One of the basic principles of experimental design is blocking, which is an important factor in the treatment of the systematic spatial variability that can be found in the edaphic properties where agricultural experiments are conducted. Blocking has a mitigating or suppressing effect on the spatial dependence in the residuals of a model, something desirable in standard linear modeling, specifically in design models. Some computer programs yield a p value associated with the blocking effect in the analysis of variance table that in many cases has been incorrectly used to discard it, and although it may improve some properties of the analysis, it may affect the independence assumption required in several models. Therefore, the present research recommends the use of the H statistic associated with the corrected blocking efficiency to show the role of blocking in modeling with the incorporation of an additional advantage rarely considered related to the suppression or mitigation of spatial dependence. With the use of the Moran index, the spatial dependence of the residuals was studied in a simple factorial design in a completely randomized and blocking field layout, which evidenced the advantages of blocking in the mitigation or suppression of the spatial dependence despite the apparently little or no importance it seems to show in the analysis of variance table.

Expected mean squares.

This chapter focuses on expected mean squares. Expected mean squares are formulas based on statistical theory identifying the components of variability in sources of variation of an ANOVA (analysis of variance) table. Their theoretical derivation is beyond the scope of this text, thus they are presented in a simpler way here, providing a method for deriving expected mean squares without a background in statistical theory. The productivity of 10 cultivars of snap beans was used as an example.

Environmental and genetic interaction of some Oat genotypes under the influence of different types of irrigation water

In this study, ten oat genotypes (Alguda , Anatolia , Pimula ,Genzania ,Hamel, Icarda short ,Kangaroo ,Icarda tall ,Mitika and Possum) were used under the impact of three irrigation water types and two agricultural seasons. Performance and genetic and environmental interaction were studied according to Eberhart and Russel and cluster analysis for Days to anthesis , plant height ,flag leaf area,no.effective tillers , no.grains.panicul , 1000 grains weight and grain yield (t.he-1), We reached the most important results that was through obtaining statistically significant in analysis of variance table of the sources of difference in environments, genotypes and the interaction between them for all characteristics under study. Genotype (6) distinguished in no.effective tillers (141.06 tiller.m-2 ), no.grains.panicul-1 (66.89 grain.panicul-1) and grain yield (1.48 t.he-1) and genotype (1) in days to anthesis (110.70 day) and no.effective tillers (136.67 tiller.m-2) and the interaction between fourth environment and genotype (6) for no.grains.panicul (66.67 grains,panicul-1) .In addition to this uniqueness in performance, genotype (6) proved its stability for plant height, 1000 grains weight and grain yield (t.he-1) .These indices are feasible with evidence that they coincided with yield and some of its components, as well as to high stability to be implemented in future after testing with other factors. In addition to that, obtaining the state of the genetic distance between genotypes tested across environments, in particular genotype (8) with genotypes (6 and 7) and hence can be used in breeding programs, especially hybridization.

Random effects models for complex designs

Plaid designs are characterised by having one set of treatments applied to rows and another set of treatments applied to columns. In a 2003 publication, Farewell and Herzberg presented an analysis of variance structure for such designs. They presented an example of a study in which medical practitioners, trained in different ways, evaluated a series of videos of patients obtained under a variety of conditions. However, their analysis did not take full account of all error terms. In this paper, a more comprehensive analysis of this study is presented, informed by the recognition that the study can also be regarded as a two-phase design. The development of random effects models is outlined and the potential importance of block-treatment interactions is highlighted. The use of a variety of techniques is shown to lead to a better understanding of the study. Examination of the variance components involved in the expected mean squares is demonstrated to have particular value in identifying appropriate error terms for F-tests derived from an analysis of variance table. A package such as ASReml can also be used provided an appropriate error structure is specified. The methods presented can be applied to the design and analysis of other complex studies in which participants supply multiple measurements under a variety of conditions.

Selecting Yield and Nutritional Traits in Sphenostylis stenocarpa Landraces for Food Improvement

Background: Sphenostylis stenocarpa is an underexploited African indigenous food crop that is enriched in nutritional quality. Objective: Exploring the robust genetic base of this landrace can help to maximize the benefit of the agricultural sector on the economy through production that is enhanced by packaging and patent. This as well will increase the quality of food production and promote African campaign on food sustainability. Methods: Upon this, this research made use of multiple statistics to identify S. stenocarpa yield and nutritional trait relatedness that supported selection for maximum yield and nutritional trait output. Yield and related traits including protein and oil contents of twenty-three Sphenostylis stenocarpa landraces were studied under a four year planting seasons in Teaching and Research farm of Landmark University, Nigeria. Results: Trait variances from Landrace × Year (L × Y) interaction, Principal Component and Cluster analyses were evaluated and the variation patterns were identified. Some vegetative (maturity phase, height and branching) and yield traits (Pod traits, seed yield and oil content) correlated significantly (p < 0.05) in the L × Y interactions. This suggests the usefulness of these traits in improving S. stenocarpa grain and oil quality yield. Tuber and nodule yield including protein content did not differ significantly in the variance table. Conclusion: The result indicates that one location trial is insufficient to determine such trait performance. The first four PCs that accounted for 51 percent of the total variations were traceable to branching, maturity date, pod numbers, seed and oil content as main contributors to yield.

Fixed Doses of Anticoagulants Cause Wide Variation of Thrombin Generation

Current practice in the prevention of venous thromboembolism (VTE) is either controlled dosage of vitamin K antagonists (VKA) or standard dosage of a low molecular weight heparin (LMWH) or an orally administrated direct inhibitor of thrombin or factor Xa (DOACs). This is justified by clinical trials showing the non-inferiority of standard dosage to VKA treatment - disregarding that the latter could be improved upon. Whether standard dosage is optimal for the individual patient depends upon how well (s)he is represented by the "average" patient that meets the inclusion criteria of the trial. Here we show that in a set of normal plasmas the individual thrombin generating power (the endogenous thrombin potential: ETP), after spiking with a fixed concentration (~ IC50) of different anticoagulants show such a wide variation that, even when plasma levels would be identical, a considerable percentage of patients could be over- or under-anticoagulated. Consequently adapted doses must be considered if better results than those with VKA are our aim. We recall that the ETP is close to constant in the individual person but varies in the population with a broad log-normal distribution (CV 16%). The ETP is highly correlated to the risk of thrombosis: The relative risk of VTE in the upper quartile being 5 - 7 times higher than that in the lower one (Winckers K., et al., poster PO617, ISTH 2015, Toronto). Reducing the ETP is the common feature of all antithrombotic therapy. The desired range of reduction is not exactly known. In congenital bleeding disorders bleeding risks increase sharply at ETP below 33%. In monitoring VKA treatment an INR below 2, which corresponds to an ETP > 66% of normal, is generally considered inadequate. We therefore arbitrarily choose the range 33 - 66% of normal, as a target range (TR). Experimental: Individual plasmas from 60 normal healthy volunteers were spiked with a fixed amount of either unfractionated heparin (UFH), low molecular weight heparin (LMWH), antithrombin binding pentasaccharide (penta), DOAC acting on thrombin or DOAC acting on factor Xa. We found the residual ETP to be highly variable (table column 3), obviously because the variation in susceptibility to the inhibitor superimposes upon the natural variation. Using these CVs we calculated what % falls either above or below the target range. The total variance of the ETP under treatment is the combined effect of natural variance, the pharmacokinetic- and the pharmacodynamic -variance. Here we determined pharmacodynamic effects only and calculated the % of ETP values that would fall outside the target range A: if there would be no pharmacokinetic variance (table column 4 & 5) and B: If the pharmacokinetic variance would equal the pharmacodynamic variance (table column 6 & 7). It is seen that in any case over 15% of the population will be outside the target range and that in the more likely case that pharmacokinetic variation counts as much as pharmacodynamic variation does around half of all patients will be outside the safe range. This could be avoided by measuring the effect of a standard dose of anticoagulant on the ETP once and increasing the dose in those with an ETP > 66% and decreasing it in those with ETP < 33%. The present work is meant to provide the rationale for starting clinical studies on the actual variation of the ETP attained under standard dosage of different anticoagulants and the effects thereon of personalised dose adjustment. Table Table. Disclosures Hemker: Diagnostica Stago: Consultancy.

A Note on the Analysis of Designed Experiments with Complex Treatment Structure

Many experiments involve a complex treatment structure, and it is not always immediately obvious how such experiments should be analysed. This paper shows by way of three examples how a suitable linear model can be formulated that provides a meaningful analysis of variance table and allows mean comparisons of interest to be obtained in a straightforward manner. Possible advantages of this approach compared to the use of linear contrasts are discussed. It is concluded that a well-chosen model can often considerably simplify the analysis and lead to useful statistical inferences. The approach advocated in this paper is going to be strongest when there is good design structure present.

Data Collection and Statistical Topics for the Preparation and Review of Manuscripts

The challenges encountered and discussions generated during the review process of the manuscripts submitted to the Variety Trials category of HortTechnology have revealed the need to review issues encountered during manuscript preparation and to provide flexible guidelines for authors and reviewers. Using a question/answer format, this manuscript discusses issues related to data collection and statistical methods available to compare varieties. Clear objectives and conclusions, adequate plot size, careful selection of entries, and sound statistical procedures are considered essential. Several additional factors (following standard production practices, using multiple seed sources, reporting analysis of variance table and mean square error, reporting multiyear/multilocation trials) are regarded as desirable, with different degrees of desirability, depending on the crop. These flexible guidelines should be viewed as recommendations for authors and reviewers rather than requirements. While defining the state-of-the-art in variety trialing is of interest to all those involved, it may be difficult to achieve when resources are limiting. It is ultimately the prerogative and responsibility of the author(s) to ensure that the work is scientifically sound.

Using the randomisation in specifying the ANOVA model and table for properly and improperly replicated grazing trials

Summary. A method for deriving the analysis of variance for an experiment is presented and applied to grazing trials. A special feature of grazing trials, specifically utilised by our method, is that they involve at least 2 randomisations: treatments are randomised to field units (for example paddocks or plots), and field units are randomised to animals. Randomisation results in the confounding (‘mixing up’) of terms and our method includes separate terms in the analysis of variance table for confounded terms so that all sources of variability in the experiment have terms for them included in the table and the confounding between the sources of variability in the experiment is explicitly displayed in the table. This information is used in determining the valid error terms and we will present examples that show how to ascertain these for effects of interest and hence which effects can be tested. In this it fulfils the same role as the contentious process of identifying the experimental unit. It will be demonstrated that the inclusion of separate terms for confounded terms results in improper replication in grazing trials being automatically signalled, and makes its ramifications clear.