Bayesian approach, traditional method, and mixed models for multienvironment trials of soybean

Silva, Alysson Jalles da; Sanches, Adhemar; Andrade, Andréa Carla Bastos; Oliveira, Gustavo Hugo Ferreira de; Mauro, Antônio Orlando Di

doi:10.1590/s0100-204x2018001000002

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…In turn, the Bayesian approach has advantages such as allowing the incorporation of previous distributions into the model, especially when the availability of information is limited (Silva et al 2018). In addition to these techniques, post-hoc blocking Row-Col emerges as another promising strategy to control the local effect.…”

Section: Ao Souza Et Almentioning

confidence: 99%

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Row-col method associated with frequentist and Bayesian statistics in a passion fruit population

Souza,

Viana,

Silva

et al. 2023

Crop Breed. Appl. Biotechnol.

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This study was conducted to test the significance of adding row and column factors in the frequentist and Bayesian models used in the evaluation of a population of Passiflora edulis, as well as selecting promising genotypes to form the next generation. The following parameters were evaluated: number of fruits, yield, fruit weight, transverse fruit diameter, longitudinal fruit diameter, pulp percentage, skin thickness and total soluble solids. For the Bayesian model, two priors were considered, namely, inverse gamma and a priori distribution with extended parameters. The model with a priori distribution with extended parameters showed lower root mean square error and higher correlation coefficient between observed and predicted values than the inverse gamma model. Furthermore, for a selection intensity of 37%, the mixed and Bayesian models selected practically the same progenies in both experiments. The use of the 5-fold cross-validation technique indicated that both tested models were efficient.

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Section: Ao Souza Et Almentioning

confidence: 99%

“…) and predictive ability coefficient PC = 100. ( cov(y predicted ;y observed ) S ypredicted .S yobserved ) were considered as described by Silva al. (2018).…”

mentioning

confidence: 99%

Row-col method associated with frequentist and Bayesian statistics in a passion fruit population

Souza,

Viana,

Silva

et al. 2023

Crop Breed. Appl. Biotechnol.

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“…The Bayesian approach has been frequently applied in several agronomic studies (Teodoro et al 2015, Silva et al 2018b, Blind et al 2020, demonstrating more sensitivity to indicate differences between treatments, when compared to other parametric and non-parametric statistical methods (Rossi & Gasparini 2012). The Bayesian statistics has many advantages, including application in several areas, from the simple comparison of averages to the adjustment of breeding models, with lower restrictions on frequent assumptions (Rossi 2011, Rossi et al 2016.…”

Section: Palavras-chavementioning

confidence: 99%

Frequentist and Bayesian inference for gas exchanges of drip-irrigated bell pepper1

Santos

Rezende

Wenneck

et al. 2021

Pesqui. Agropecu. Trop.

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The water deficit or excess may cause undesirable changes in yield and physiological aspects of irrigated crops. Considering the analysis of experimental data, the use of classical statistical methods may not be sufficient to detect morphological and physiological effects resulting from the conditions employed, being interesting the use of new procedures, such as the Bayesian inference. This study aimed to evaluate the gas exchanges in the bell pepper crop under irrigation depths and different irrigation times, in a protected environment, by applying the parametric and Bayesian methods. The experiment was conducted in a completely randomized design, arranged in a 5 x 2 factorial scheme, with five irrigation depths (60, 80, 100, 120 and 140 % of the crop evapotranspiration) and two irrigation times (8 a.m. and 2 p.m.), with five replications. The stomatal conductance, transpiration rate, photosynthetic rate, intrinsic water-use efficiency, ratio between the photosynthetic rate and the transpiration rate, and total dry matter were evaluated. The gas exchanges were affected by water replacement depths, with little interference from the irrigation times. The linear regression models, according to the irrigation depths, for transpiration rate, stomatal conductance and total dry matter were significant for both the statistical methods, suggesting that the results are similar and even coincident, especially when a priori information are not provided in the Bayesian analysis. Differences in the photosynthetic rate were observed only with the Bayesian method, adjusting linear models according to the irrigation depths, in both the irrigation times.

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“…The Bayesian approach is another method for more accurate estimates, especially few observations are available and designs are unbalanced (Silva et al, 2013;Silva et al, 2018;Silva et al, 2020). This approach allows to use of a priori distributions incorporated into the model, which can be an advantage.…”

Section: Introductionmentioning

confidence: 99%

Row–Col and Bayesian approach seeking to improve the predictive capacity and selection of passion fruit

Souza

Viana

Silva

et al. 2022

Sci. agric. (Piracicaba, Braz.)

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Methods for genetic improvement of semi-perennial species, such as passion fruit, often involve large areas, unbalanced data, and lack of observations. Some strategies can be applied to solve these problems. In this work, different models and approaches were tested to improve the precision of estimates of genetic evaluation models for several characteristics of the passion fruit. A randomized block design (RBD) model was compared to a posteriori correction, adding two factors to the model (post-hoc blocking Row-Col). These models were also combined with the frequentist and Bayesian approaches to identify which combination yields the most accurate results. These approaches are part of a strategic plan in a perennial plant breeding program to select promising genitors of passion to compose the next selection cycle.For Bayesian, we tested two priors, defining different values for the distribution parameters of effect variances of the model. We also performed a cross-validation test to choose a priori values and compare the frequentist and Bayesian approaches using the root mean square error (RMSE) and the correlation between the predicted and observed values, called Predictive capacity of the model (PC). The model with the post-hoc blocking Row-Col design captured the spatial variability for productivity and number of fruits, directly affecting the experimental precision. Both approaches applied to the models showed a similar performance, with predictive capacity and selective efficiency leading to the selection of the same individuals.

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Bayesian approach, traditional method, and mixed models for multienvironment trials of soybean

Cited by 3 publications

References 13 publications

Row-col method associated with frequentist and Bayesian statistics in a passion fruit population

Row-col method associated with frequentist and Bayesian statistics in a passion fruit population

Frequentist and Bayesian inference for gas exchanges of drip-irrigated bell pepper1

Row–Col and Bayesian approach seeking to improve the predictive capacity and selection of passion fruit

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