Consideration of Nonparametric Approaches for Assessing Genotype-by-Environment (G × E) Interaction with Disease Severity Data

Determination of host genotype-by-environment (G × E) interaction is needed to assess the stability of cultivar traits such as plant disease resistance and to reveal differences in aggressiveness or virulence of pathogen strains among locations. Here we explored the use of rank-based methodology to quantify the concordance (or discordance) of disease responses of host genotypes across environments, based on the Kendall coefficient of concordance (W) and ancillary test statistics, in order to determine the extent to which environment affected rankings of genotypes. An analysis of four data sets for disease severity of gray leaf spot of maize (with genotypes planted in as many as 11 locations in a given year) revealed highly significant concordance (P ≤ 0.001) overall, indicating that genotypes varied little in within-environment rankings. This suggests that the G × E interaction was small or nonexistent (in terms of rankings). A novel rank-based method by Piepho was evaluated to further elucidate the interaction (if any) through a test for variance homogeneity. The Piepho test statistic was not significant (P > 0.25) for any of the gray leaf spot data sets, confirming the stability of genotypes across environments for this pathosystem; however, analysis of published data sets for other pathosystems indicated significant results. The relationship shown by Hühn, Lotito, and Piepho between the ratio of genotype and residual variances of the original data and the rank-based W statistic was evaluated using Monte Carlo simulations. A more general functional relationship was developed that is applicable over a wide range of number of genotypes and environments in the analyzed studies. This confirms previously shown linkages between rankings of genotypes within environments and variability in the original (unranked) data, thus permitting ease of interpretation of parametric and nonparametric results.

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Relationships of Environmental and Cultural Factors with Severity of Gray Leaf Spot in Maize

Plant Disease ◽

10.1094/pdis.2002.86.10.1127 ◽

2002 ◽

Vol 86 (10) ◽

pp. 1127-1133 ◽

Cited By ~ 12

Author(s):

Alka Bhatia ◽

G. P. Munkvold

Keyword(s):

Relative Humidity ◽

Disease Severity ◽

Leaf Spot ◽

Cultural Influences ◽

The United States ◽

Gray Leaf Spot ◽

Planting Date ◽

Time Duration ◽

Best Fitting ◽

Fitting Model

Gray leaf spot of maize caused by Cercospora zeae-maydis is a major foliar disease in the United States and other parts of the world. Efficient management of gray leaf spot is hindered by a lack of quantitative information regarding environmental and cultural influences on disease severity. We collected environmental, cultural, and disease severity data in southern Iowa at 13 locations in 1998 and 11 locations in 1999. The independent variables that we considered included temperature, relative humidity, leaf wetness, percent maize residue cover, distance to nearest maize residue, planting date, and previous crop. A time-duration value (TDV) variable was created to represent cumulative hours of favorable temperature (22 ≤ T ≤ 30°C) and relative humidity (≥95%). Disease severity was assessed at 2-week intervals on three to eight maize genotypes differing in gray leaf spot resistance and maturity at each location. Environmental, cultural, and disease data were summarized for four different periods during the growing season and analyzed by stepwise multiple linear regression in order to determine which variables significantly contributed to gray leaf spot severity at the dough or dent growth stages of maize. In 1998, genotype resistance, planting date, distance to nearest maize residue, wetness duration, and TDV had significant effects on disease severity. R2 values were similar among the four periods. The best-fitting model for the 1998 data had an R2 of 0.65. With 1998 and 1999 data combined, results were similar except that percent maize residue cover was significant rather than distance to nearest maize residue. The best-fitting model had an R2 of 0.55. The 2-year model utilizing only the weather variables from emergence to 2 weeks before silking had an R2 value of 0.43. Strong linear relationships existed between gray leaf spot severity and genotype resistance, maize surface residue, planting date, and TDV. These results can serve as a foundation for the development of a prediction model for gray leaf spot severity on maize.

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Prevalence, Incidence, and Severity of Sorghum Diseases in Western Kenya

Plant Disease ◽

10.1094/pdis.2002.86.1.65 ◽

2002 ◽

Vol 86 (1) ◽

pp. 65-70 ◽

Cited By ~ 27

Author(s):

H. K. Ngugi ◽

S. B. King ◽

G. O. Abayo ◽

Y. V. R. Reddy

Keyword(s):

Disease Severity ◽

Leaf Spot ◽

Gaussian Model ◽

Gray Leaf Spot ◽

Distribution Functions ◽

Leaf Blight ◽

Yield Reduction ◽

Production Environment ◽

Head Smut ◽

Western Kenya

To assess the prevalence and severity of sorghum diseases in western Kenya, a 2-year survey was conducted (July 1995 and 1996), in 91 and 109 farmers' fields, respectively. Fields were generally <0.5 ha and production environment ranged from warm-humid to warm-semi-arid. Fourteen foliar and six panicle diseases were observed, with limited variation in disease prevalence and severity between the 2 years. The most common foliar diseases observed were (in decreasing order of prevalence) oval leaf spot (Ramulispora sorghicola), rust (Puccinia purpurea), ladder leaf spot (Cercospora fusimaculans), zonate leaf spot (Gloeocercospora sorghi), gray leaf spot (Cercospora sorghi), leaf blight (Exserohilum turcicum), and anthracnose (Colletotrichum sublineolum); with prevalence ranging from 95 to 97% of fields for oval leaf spot, and 44 to 65% of fields for anthracnose. Head smut (Sporisorium reilianum), was observed in 73 to 75% of fields, covered kernel smut (S. sorghi) 42 to 43% of fields, and loose smut (S. cruenta) 14 to 24% of fields. Head smut incidence was >25% in 3% of fields surveyed. Grain yield reduction from smut diseases alone was estimated to be 5%. Out of eight probability distribution functions compared, the double Gaussian model best described the frequency of disease severity levels for most diseases. Based on the best-fitting model, the proportion of fields with disease severity level thought to cause yield loss (severity rating >5 on a 1 to 9 scale, where 1 = no disease) was calculated as 26.6% for oval leaf spot, 15.3% for rust, 14.8% for anthracnose, 4.8% for ladder leaf spot, and 1.5% for leaf blight. The production environment influenced the prevalence of disease severity. Severe anthracnose, leaf blight, and ladder leaf spot were confined to fields in the humid LM1 and LM2 agro-ecological zones, rust was ubiquitous, and severe gray leaf spot was more prevalent in the dryer LM4 zone.

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First Report of Gray Leaf Spot Caused by Pyricularia grisea on Lolium perenne in Illinois

Plant Disease ◽

10.1094/pdis.2000.84.10.1151b ◽

2000 ◽

Vol 84 (10) ◽

pp. 1151-1151 ◽

Cited By ~ 12

Author(s):

D. K. Pedersen ◽

R. T. Kane ◽

H. T. Wilkinson

Keyword(s):

Disease Severity ◽

Lolium Perenne ◽

Perennial Ryegrass ◽

Leaf Spot ◽

Gray Leaf Spot ◽

Pyricularia Grisea ◽

Conidial Suspension ◽

First Report ◽

Severity Rating ◽

Plastic Bags

Each year from 1991 to 1999, a disease matching the description of gray leaf spot (1) was observed in the central and north central regions of Illinois. Disease severity was low (<10% blight) from 1991 to 1994 and 1999 and was severe (>50% blight in some areas) from 1995 to 1998. The disease was observed on Lolium perenne (perennial ryegrass) golf course fairways and sports fields. Isolations of Pyricularia grisea were made from L. perenne collected from golf courses in Bloomington, Decatur, Kankakee, Pekin, Urbana, and Moline, IL. All isolates were collected from surface-sterilized, symptomatic leaves. Cultures were maintained on one-fifth strength potato-dextrose agar (PDA) and induced to sporulate on full-strength oatmeal agar. All isolates in culture displayed vegetative and conidial characteristics similar to those previously described for P. grisea (1). Twenty-five different L. perenne germ plasms were inoculated with isolate WF9826 (Kankakee) using a suspension of 1 × 105 conidia per milliliter. The 4-week-old lawns (100 plants per 3-cm-diameter cone-tainer) of each ryegrass germ plasm were inoculated by spraying foliage with the conidial suspension until runoff. Inoculated and uninoculated lawns were enclosed in plastic bags and placed in an incubator (16 h light; 28°C) for 7 days. Disease severity was rated using a scale of 0 to 10 (10 = 100% blight). Each treatment was replicated three times, and all experiments were repeated four times. Small blue-gray, water-soaked lesions with dark brown borders were observed on leaves of all inoculated ryegrass germ plasms. Advanced symptoms included blighting of much of the leaves. The mean disease severity rating was 3.8 (range 2 to 7) for all experimental units and all 25 germ plasms. P. grisea was isolated from leaves that were inoculated with WF9826. This is the first report of gray leaf spot of perennial ryegrass caused by P. grisea in Illinois. Reference: (1) P. J. Landschoot et al. Plant Dis. 76:1280, 1992.

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Influence of Cultural Practices on the Development of Gray Leaf Spot (GLS) on Maize at Bako, Western Ethiopia

International Journal of Phytopathology ◽

10.33687/phytopath.001.01.0012 ◽

2012 ◽

Vol 1 (1) ◽

pp. 19-26

Author(s):

Aschalew Sisay ◽

Fekede Abebe ◽

Kedir Wako

Keyword(s):

Grain Yield ◽

Disease Severity ◽

Leaf Spot ◽

Seed Weight ◽

Conservation Tillage ◽

Gray Leaf Spot ◽

Minimum Tillage ◽

Tillage Practices ◽

Sowing Dates ◽

Thousand Seed Weight

The experiment was conducted at Bako Agricultural Research Center from 2008 to 2009 cropping seasons in order to evaluate the effect of sowing dates and ploughing frequency on the development of Grey Leaf Spot (GLS) on maize. The susceptible variety Phb 3253, with three sowing dates (early, optimum and late at 10 days interval) and three ploughing treatments: Minimum tillage (once), farmer’s practice (three times ploughing) and four times ploughing were used. All plots were uniformly treated with GLS infected crop residue before first ploughing. Trial was laid out in factorial arrangement in Randomized Complete Block Design (RCBD) with three replications. Among the planting dates, the highest disease severity of 7.60, 7.44 7.00, (1-9 scale) and Area Under Disease Progress Curve (AUDPC) 305.83, 280.1 and 280.33 were recorded in early sown minimum (conservation) tillage practices, while the lowest was with AUDPC 161.50, 196.50 and 222.67 in four times ploughed plots in 2007, 2008 and 2009 years respectively. The highest thousand seed weight and grain yield was observed in four times ploughed and in early sown plots, while the lowest thousand seed weights and grain yield were recorded in the conservation tillage practice. Four times ploughed and early sown fields had a mean yield advantage of 474.73kg (6.66%) and a total yield advantage 2020.77kg (36.23.6%) over three times ploughed and minimum tillage practices for the three seasons 2008-2009. In general higher disease severity, low thousand seed weight and grain yield were recorded for the conservation tillage compared to other practices. The overall results showed that four times ploughing result in superior maize grain yield performance compared to others as it has resulted in reducing the disease development.

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Assessment of the Effects of Fertilizer Applications on Gray Leaf Spot and Yield in Maize

Plant Disease ◽

10.1094/pdis.2002.86.8.859 ◽

2002 ◽

Vol 86 (8) ◽

pp. 859-866 ◽

Cited By ~ 5

Author(s):

P. M. Caldwell ◽

J. M. J. Ward ◽

N. Miles ◽

M. D. Laing

Keyword(s):

Grain Yield ◽

Disease Severity ◽

Leaf Spot ◽

Gray Leaf Spot ◽

Small Scale ◽

Grain Yields ◽

Disease Progress Curve ◽

Disease Progress ◽

Progress Curve ◽

Maize Grain

The effects of the application of 0, 60, and 120 kg N ha-1 and of 0, 25, 50, and 150 kg K ha-1 on final disease severity, standardized area under disease progress curve, and grain yield were investigated at Cedara, South Africa, on a maize (Zea mays) hybrid susceptible to gray leaf spot (GLS), caused by Cercospora zeae-maydis. The trial was a randomized 3 × 4 factor design, split for fungicide treatments, and replicated three times. With increased N and K levels, final percent leaf blighting and the standardized area under disease progress curve were higher. In fungicide-treated maize, grain yields increased with increasing levels of N and K, as expected. In non-fungicide-treated maize, grain yield increased significantly with increased levels of N, despite increased disease severity. This was in contrast to small increases in grain yields from non-fungicide-treated maize with increased K levels, which were not significant. This was probably because grain yield response, which should have occurred at higher K applications, was reduced by increased disease severity. The effect of N, P, and K on GLS wasinvestigated at Ahrens. Maize was grown in a 4 × 4 × 4 N-P-K factorial, in a randomized complete block design. Fertilizer was applied at 0, 60, 120, and 180 kg N ha-1, 0, 30, 60, and 120 kg P ha-1, and 0, 50, 100, and 150 kg K ha-1. No fungicides were applied. A single disease assessment at physiological maturity showed that final disease severity increased with increasing levels of N, P, and K. These results have implications for small-scale farmers who are encouraged to fertilize for increased grain yields but may not have the resources to apply fungicide sprays to control fungal diseases.

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AMMI VERSUS NONPARAMETRIC ANALYSIS FOR INVESTIGATION OF GE INTERACTION OF PLANT DISEASE EVALUATION

AGROFOR ◽

10.7251/agreng1601157s ◽

2016 ◽

Vol 1 (1) ◽

Cited By ~ 1

Author(s):

Naser Sabaghnia

Keyword(s):

Disease Severity ◽

Plant Disease Resistance ◽

Plant Disease ◽

Gray Leaf Spot ◽

Multivariate Statistical Methods ◽

Ge Interaction ◽

Multivariate Statistical ◽

Stability Parameters ◽

Multivariate Procedures ◽

Selection Of

In breeding for plant disease resistance programs, a large number of new improvedgenotypes are tested over a range of test pathogens or environments and theunderlying statistics used to model this system may be rather complicated. Due toordinal nature of most measured traits of disease responses, some nonparametricmethods used for analyzing genotype × environment (GE) interaction in twodatasets for disease severity of gray leaf spot of maize (with ten genotypes plantedin 10 and 11 environments). Usually, the presence of the GE interaction effectcomplicates the selection of the most favorable genotypes and there are severalstatistical procedures available to analyze these dataset including a range ofunivariate, nonparametric and multivariate procedures. Present analysis separatednonparametric methods based on dynamic concept from those which are based onthe static type indicated that RS statistic following to S6, NP2, NP3 and RSstatistics were found to be useful in detecting the non-complicated phenotypicstability in disease severity dataset. In complicated GE interaction, the ability ofAMMI stability parameters especially SPC1, SPCF, D1, DF, EV1, EVF and ASVstatistics were high in the detection of stability in complicated GE interaction. Ingeneral, nonparametric methods are useful alternatives to parametric methods andallow drawing valid conclusions with considerably better chances of detecting theGE interaction in experiments of plant pathology. Also, in some cases the GEinteraction structure is too complex to be summarized by only one parameter andso, it is essential to use multivariate statistical methods like AMMI.

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Performance of Electronic Structure Methods for the Description of Hückel-Möbius Interconversions in Extended π-Systems

10.26434/chemrxiv.10564115 ◽

2019 ◽

Author(s):

Tatiana Woller ◽

Ambar Banerjee ◽

Nitai Sylvetsky ◽

Xavier Deraet ◽

Frank De Proft ◽

...

Keyword(s):

Electronic Structure ◽

Basis Set ◽

Dft Methods ◽

Molecular Switching ◽

Wide Range ◽

Electronic Structure Methods ◽

Explicitly Correlated ◽

Relative Errors ◽

The Stability ◽

Basis Set Expansion

Expanded porphyrins provide a versatile route to molecular switching devices due to their ability to shift between several π-conjugation topologies encoding distinct properties. Taking into account its size and huge conformational flexibility, DFT remains the workhorse for modeling such extended macrocycles. Nevertheless, the stability of Hückel and Möbius conformers depends on a complex interplay of different factors, such as hydrogen bonding, p···p stacking, steric effects, ring strain and electron delocalization. As a consequence, the selection of an exchange-correlation functional for describing the energy profile of topological switches is very difficult. For these reasons, we have examined the performance of a variety of wavefunction methods and density functionals for describing the thermochemistry and kinetics of topology interconversions across a wide range of macrocycles. Especially for hexa- and heptaphyrins, the Möbius structures have a pronouncedly stronger degree of static correlation than the Hückel and figure-eight structures, and as a result the relative energies of singly-twisted structures are a challenging test for electronic structure methods. Comparison of limited orbital space full CI calculations with CCSD(T) calculations within the same active spaces shows that post-CCSD(T) correlation contributions to relative energies are very minor. At the same time, relative energies are weakly sensitive to further basis set expansion, as proven by the minor energy differences between MP2/cc-pVDZ and explicitly correlated MP2-F12/cc-pVDZ-F12 calculations. Hence, our CCSD(T) reference values are reasonably well-converged in both 1-particle and n-particle spaces. While conventional MP2 and MP3 yield very poor results, SCS-MP2 and particularly SOS-MP2 and SCS-MP3 agree to better than 1 kcal mol-1 with the CCSD(T) relative energies. Regarding DFT methods, only M06-2X provides relative errors close to chemical accuracy with a RMSD of 1.2 kcal mol-1. While the original DSD-PBEP86 double hybrid performs fairly poorly for these extended p-systems, the errors drop down to 2 kcal mol-1 for the revised revDSD-PBEP86-NL, again showing that same-spin MP2-like correlation has a detrimental impact on performance like the SOS-MP2 results.

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It is better an approximate answer to the right question than the exact answer to the wrong question : the case of the psychometric analysis of the ASQ:SE

10.31234/osf.io/a5tdf ◽

2020 ◽

Author(s):

Luis Anunciacao ◽

janet squires ◽

J. Landeira-Fernandez

Keyword(s):

Internal Structure ◽

Statistical Methods ◽

Principal Component ◽

Psychological Theory ◽

Published Data ◽

Multivariate Statistical ◽

Exact Answer ◽

Wide Range ◽

Ages And Stages Questionnaire ◽

The Right

One of the main activities in psychometrics is to analyze the internal structure of a test. Multivariate statistical methods, including Exploratory Factor analysis (EFA) and Principal Component Analysis (PCA) are frequently used to do this, but the growth of Network Analysis (NA) places this method as a promising candidate. The results obtained by these methods are of valuable interest, as they not only produce evidence to explore if the test is measuring its intended construct, but also to deal with the substantive theory that motivated the test development. However, these different statistical methods come up with different answers, providing the basis for different analytical and theoretical strategies when one needs to choose a solution. In this study, we took advantage of a large volume of published data (n = 22,331) obtained by the Ages and Stages Questionnaire Social-Emotional (ASQ:SE), and formed a subset of 500 children to present and discuss alternative psychometric solutions to its internal structure, and also to its subjacent theory. The analyses were based on a polychoric matrix, the number of factors to retain followed several well-known rules of thumb, and a wide range of exploratory methods was fitted to the data, including EFA, PCA, and NA. The statistical outcomes were divergent, varying from 1 to 6 domains, allowing a flexible interpretation of the results. We argue that the use of statistical methods in the absence of a well-grounded psychological theory has limited applications, despite its appeal. All data and codes are available at https://osf.io/z6gwv/.

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Insights into Potent Therapeutical Antileukemic Agent L-glutaminase Enzyme Under Solid-state Fermentation: A Review

Current Drug Metabolism ◽

10.2174/1389200221666200421122147 ◽

2020 ◽

Vol 21 (3) ◽

pp. 211-220 ◽

Cited By ~ 1

Author(s):

Chandrasai Potla Durthi ◽

Madhuri Pola ◽

Satish Babu Rajulapati ◽

Anand Kishore Kola

Keyword(s):

Solid State ◽

Solid State Fermentation ◽

Food Industry ◽

Energy Requirement ◽

Production Studies ◽

Wide Range ◽

Hybridoma Technology ◽

Bacteria And Fungi ◽

The Stability ◽

Glutaminase Activity

Aim & objective: To review the applications and production studies of reported antileukemic drug L-glutaminase under Solid-state Fermentation (SSF). Overview: An amidohydrolase that gained economic importance because of its wide range of applications in the pharmaceutical industry, as well as the food industry, is L-glutaminase. The medical applications utilized it as an anti-tumor agent as well as an antiretroviral agent. L-glutaminase is employed in the food industry as an acrylamide degradation agent, as a flavor enhancer and for the synthesis of theanine. Another application includes its use in hybridoma technology as a biosensing agent. Because of its diverse applications, scientists are now focusing on enhancing the production and optimization of L-glutaminase from various sources by both Solid-state Fermentation (SSF) and submerged fermentation studies. Of both types of fermentation processes, SSF has gained importance because of its minimal cost and energy requirement. L-glutaminase can be produced by SSF from both bacteria and fungi. Single-factor studies, as well as multi-level optimization studies, were employed to enhance L-glutaminase production. It was concluded that L-glutaminase activity achieved by SSF was 1690 U/g using wheat bran and Bengal gram husk by applying feed-forward artificial neural network and genetic algorithm. The highest L-glutaminase activity achieved under SSF was 3300 U/gds from Bacillus sp., by mixture design. Purification and kinetics studies were also reported to find the molecular weight as well as the stability of L-glutaminase. Conclusion: The current review is focused on the production of L-glutaminase by SSF from both bacteria and fungi. It was concluded from reported literature that optimization studies enhanced L-glutaminase production. Researchers have also confirmed antileukemic and anti-tumor properties of the purified L-glutaminase on various cell lines.

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mtDNAcombine: tools to combine sequences from multiple studies

BMC Bioinformatics ◽

10.1186/s12859-021-04048-0 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Eleanor F. Miller ◽

Andrea Manica

Keyword(s):

Sequence Data ◽

Data Extraction ◽

Bayesian Skyline Plot ◽

Model Organisms ◽

Data Sets ◽

Data Handling ◽

Online Database ◽

Genetic Studies ◽

Wide Range ◽

Existing Data

Abstract Background Today an unprecedented amount of genetic sequence data is stored in publicly available repositories. For decades now, mitochondrial DNA (mtDNA) has been the workhorse of genetic studies, and as a result, there is a large volume of mtDNA data available in these repositories for a wide range of species. Indeed, whilst whole genome sequencing is an exciting prospect for the future, for most non-model organisms’ classical markers such as mtDNA remain widely used. By compiling existing data from multiple original studies, it is possible to build powerful new datasets capable of exploring many questions in ecology, evolution and conservation biology. One key question that these data can help inform is what happened in a species’ demographic past. However, compiling data in this manner is not trivial, there are many complexities associated with data extraction, data quality and data handling. Results Here we present the mtDNAcombine package, a collection of tools developed to manage some of the major decisions associated with handling multi-study sequence data with a particular focus on preparing sequence data for Bayesian skyline plot demographic reconstructions. Conclusions There is now more genetic information available than ever before and large meta-data sets offer great opportunities to explore new and exciting avenues of research. However, compiling multi-study datasets still remains a technically challenging prospect. The mtDNAcombine package provides a pipeline to streamline the process of downloading, curating, and analysing sequence data, guiding the process of compiling data sets from the online database GenBank.

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