scholarly journals Variability and Experimental Desing for Trials with Cucurbita pepo and Capsicum annuum

2017 ◽  
Vol 9 (11) ◽  
pp. 58
Author(s):  
Alessandro D. Lúcio ◽  
Daniel Santos ◽  
Tiago Olivoto
Keyword(s):  
Capsicum Annuum ◽  
Coefficient Of Variation ◽  
Cucurbita Pepo ◽  
Homogeneity Test ◽  
Plot Size ◽  
Homogeneity Of Variances ◽  
Randomized Design ◽  
Variance Homogeneity ◽  
Variability Data ◽  
Uniformity Trials

The variability within rows of cultivation may reduce the accuracy of vegetables trails; however, little is known about this variability in protected environments. This study aimed at to assess the variability in greenhouses cultivated with Cucurbita pepo and Capsicum annuum and to verify the effect of borders use and plot size in minimizing this variability. Data from two uniformity trials each crop were used. For statistical analysis, the total of productivity by plant was used, considering the plants arranged in parallel crop rows the lateral openings of the greenhouse and the same plants arranged in columns perpendicular to these openings. Different scenarios were designed by excluding rows and columns to generate the borders in different plot sizes. For each scenario, a variance homogeneity test was performed among the remaining rows and columns and the variance and coefficient of variation were calculated. There is variability among rows and columns in trials with C. pepo and C. annuum in greenhouses and the use of borders does not bring benefits in terms of reduction of the coefficient of variation or reduction of cases of variances heterogeneity among rows or columns. The use of a plot size greater than or equal to or two plants for trials with C. pepo and ten plants for trials with C. annuum provides homogeneity of variances among rows and columns enabling the use of the completely randomized design.

scholarly journals Variability of production and the planning of experiments in snapbeans

2018 ◽  
Vol 36 (3) ◽  
pp. 382-388
Author(s):  
Alessandro D Lúcio ◽  
Daniel Santos
Keyword(s):  
Coefficient Of Variation ◽  
Plot Size ◽  
Homogeneity Of Variances ◽  
Randomized Design ◽  
Heterogeneity Of Variance ◽  
Completely Randomized Design ◽  
Variability Data ◽  
Planning Of Experiments

ABSTRACT This work aimed at studying the variability of production of snapbeans grown in plastic greenhouses and the effectiveness of experimental borders and plot size in reducing such variability. Data from a uniformity experiment carried out in a plastic greenhouse were used. The analyzes were performed over spatial arrangements that considered the plants first arranged in planting rows parallel to the lateral openings of the greenhouse and then arranged in columns, perpendicular to these openings. Different scenarios were produced by excluding rows and columns. The homogeneity of variances between the remaining rows and columns was tested in each scenario, and the variance and the coefficient of variation were calculated as well. There was heterogeneity of variance between rows in the experiment. Borders were not effective in reducing the coefficient of variation or the frequency of cases of heterogeneity of variances between rows. Plots with two or more plants provided homogeneity of variances between rows and columns, creating room for the possibility of using the completely randomized design in experiments with snapbeans in plastic greenhouses.

scholarly journals Plot size and number of replications to assess the vegetable matter in oat

2018 ◽  
Vol 9 (2) ◽  
pp. 252-263
Author(s):  
André Lavezo ◽  
Alberto Cargnelutti Filho ◽  
Bruna Mendonça Alves ◽  
Denison Esequiel Schabarum ◽  
Daniela Lixinski Silveira ◽  
...  
Keyword(s):  
Dry Matter ◽  
Flowering Stage ◽  
Fresh Matter ◽  
Tukey Test ◽  
Plot Size ◽  
Randomized Design ◽  
Sowing Dates ◽  
Completely Randomized Design ◽  
Uniformity Trials

The determination of the optimum plot size in agricultural crops is important for obtaining accurate inferences in the treatments in question. This study aimed at determining the optimum plot size (Xo) and the number of replications to evaluate the fresh matter (FM) and the dry matter (DM) of oat and at verifying the variability of Xo among cultivars and sowing dates. Ninety-six uniformity trials of 3×3 m were performed and each assay was divided into 36 basic experimental units (BEU) of 0.5×0.5 m. The 96 uniformity trials were distributed in four cultivars and three sowing dates. At the flowering stage, FM and DM were determined in each BEU. Then, the Xo was determined in each uniformity assay, using the maximum curvature method of the coefficient of variation model. In oat, there is variability of Xo among cultivars and sowing dates to measure FM and DM. For the four cultivars on the three sowing dates, the Xo of 1.66 m2 and of 1.73 m2 are suitable to evaluate FM and DM, respectively. Four replications to evaluate the maximum of 50 treatments in completely randomized design and randomized blocks design are sufficient so that the differences among treatment means of 44.75% of the experiment mean may be significant, using the Tukey test at 5% probability to measure FM and DM in oat.

scholarly journals Plot Size and Number of Replications for Evaluation of the Yield of Grains in Cultivars and Dates of Sowing of Rye

2017 ◽  
Vol 10 (1) ◽  
pp. 122 ◽  
Author(s):  
Gabriela Görgen Chaves ◽  
Alberto Cargnelutti Filho ◽  
Cláudia Marques de Bem ◽  
Cirineu Tolfo Bandeira ◽  
Daniela Lixinski Silveira ◽  
...  
Keyword(s):  
Secale Cereale ◽  
Coefficient Of Variation ◽  
Tukey Test ◽  
Plot Size ◽  
Maximum Curvature ◽  
Sowing Dates ◽  
Secale Cereale L ◽  
The Mean ◽  
Uniformity Trials ◽  
Variation Model

The objectives of this study were to determine the optimum plot size (Xo) and the number of replications to evaluate the grains yield of rye (Secale cereale L.) and investigate the variability of Xo between two cultivars and three sowing dates. Eighteen uniformity trials were conducted with rye. The Xo was determined by the method of maximum curvature of the coefficient of variation model. The number of repetitions was determined in scenarios formed by combinations of i treatments (i = 3, 4, ... 50) and d minimum differences between means of treatments to be detected as significant at 0.05 of probability, by Tukey test, expressed in percentage of the average of the experiment (d = 10, 12, ... 30%). There is variability in optimum plot size to evaluate the grains yield among the cultivars BRS Progresso and Temprano and among sowing dates in the rye crop. The optimum plot size to evaluate the grains yield of rye is 6.08 m2. Seven replicates are sufficient to evaluate the grains yield of rye in experiments with up to 50 treatments, and identify, as significant at 5% probability by Tukey test, differences among averages of treatments of 29.65% of the mean of the experiment in designs completely randomized and randomized block.

scholarly journals Plot size and replications number for triticale experiments

2020 ◽  
Vol 50 (11) ◽  
Author(s):  
Marcos Toebe ◽  
Alberto Cargnelutti Filho ◽  
Anderson Chuquel Mello ◽  
Rafael Rodrigues de Souza ◽  
Franciéle dos Santos Soares ◽  
...  
Keyword(s):  
Experimental Design ◽  
Coefficient Of Variation ◽  
Fresh Weight ◽  
Human Food ◽  
Tukey Test ◽  
Plot Size ◽  
Maximum Curvature ◽  
Experimental Area ◽  
Uniformity Trials

ABSTRACT: The hybridization between wheat and rye crops resulted in the triticale crop, which presents rusticity, versatility in animal and human food and possibility of use as a cover plant. The objective of this research was to determine the optimal plot size and the replications number to evaluate the fresh weight of triticale in two evaluation moments. An experiment was carried out with the triticale cultivar IPR111. The experimental area was divided into 48 uniformity trials, each containing 36 basic experimental units of 0.51 m2. The fresh weight was evaluated in 24 uniformity trials at 99 days after sowing (DAS) and in 24 uniformity trials at 127 DAS. The optimal plot size was determined by the method of the maximum curvature of the coefficient of variation and the replications number was determined in scenarios of treatments number and differences between means to be detected as significant by Tukey test. To determine the fresh weight of triticale, the optimal plot size is 3.12 m2, with coefficient of variation of 13.69%. Six replications are sufficient to identify as significant, differences between treatment means of 25% for experiments with up to seven treatments and of 30% for experiments with up to 28 treatments, regardless of the experimental design.

scholarly journals Plot size and number of replications in Sudan grass

2020 ◽  
Vol 41 (3) ◽  
pp. 783
Author(s):  
Alberto Cargnelutti Filho ◽  
Cirineu Tolfo Bandeira ◽  
Gabriela Görgen Chaves ◽  
Jéssica Andiara Kleinpaul ◽  
Rafael Vieira Pezzini ◽  
...  
Keyword(s):  
Coefficient Of Variation ◽  
Iterative Process ◽  
Block Design ◽  
Mean Value ◽  
Fresh Weight ◽  
Sudan Grass ◽  
Plot Size ◽  
Maximum Curvature ◽  
The Mean ◽  
Uniformity Trials

The aim of this study was to determine the optimal plot size and the number of replications to evaluate fresh weight in Sudan grass [Sorghum sudanense (Piper) Stapf.]. Twenty-six uniformity trials were carried out in two cultivars (BRS Estribo and CG Farrapo), in four sowing seasons (20 Dec, 20 Jan, 7 Feb and 24 Feb) and two methods for evaluating fresh weight (cutting and at flowering). The fresh weight was evaluated in 936 basic experimental units (BEU) (26 trials × 36 BEU per trial). One BEU comprised three rows of plants, 1 m in length (1.2 m2). The optimal plot size was determined using the maximum curvature method of the model of the coefficient of variation. For experiments in a completely randomised or randomised block design, in combinations of number of treatments and levels of experimental precision, the number of replications was determined by an iterative process. The optimal plot size to evaluate fresh weight in Sudan grass is 7.95 m2. Eight replications, to evaluate up to 50 treatments in a completely randomised or randomised block design, are sufficient to identify as significant at 0.05% probability by Tukey’s test, differences between the mean value of each treatment of 30.2% of the mean value of the experiment.

scholarly journals Plot size and number of replicates in times of sowing and cuts of millet

2016 ◽  
Vol 20 (2) ◽  
pp. 119-127 ◽  
Author(s):  
Cláudia Burin ◽  
Alberto Cargnelutti Filho ◽  
Bruna M. Alves ◽  
Marcos Toebe ◽  
Jéssica A. Kleinpaul
Keyword(s):  
Coefficient Of Variation ◽  
Iterative Process ◽  
Block Design ◽  
Probability Level ◽  
Fresh Matter ◽  
Tukey Test ◽  
Plot Size ◽  
Randomized Block Design ◽  
The Mean ◽  
Uniformity Trials

ABSTRACT The objective of this study was to determine the optimum plot size (Xo) and number of replicates to evaluate millet shoot fresh matter in times of sowing and cuts. Uniformity trials of 6 × 4 m (24 m2) were carried out in three sowing times, in the agricultural year of 2013-2014. Each uniformity trial was divided into 24 basic experimental units (BEU) of 1 × 1 m (1 m2) and the shoot fresh matter of plants in each BEU was weighed. The Xo was determined by the method of maximum curvature of the coefficient of variation model. The number of replicates for experiments in completely randomized and randomized block design, in scenarios of combinations of i treatments (i = 3, 4, ..., 50) and d minimal differences between treatment means, to be detected as significant at 0.05 probability level by Tukey test, expressed in percentage of the experiment mean (d = 10, 12, ..., 30%), was determined by iterative process until convergence. The optimum plot size to evaluate millet shoot fresh matter is 4.97 m2, for the three times of sowing and cuts. For the evaluation of up to 50 treatments, in completely randomized and randomized block design, five replicates are sufficient to identify as significant, at 0.05 probability level by Tukey test, differences between treatment means of 28.66% of the mean of the experiment.

scholarly journals Productive variability, border use and plot size in trials with cherry tomato

2018 ◽  
Vol 48 (2) ◽  
Author(s):  
Daniel Santos ◽  
Alessandro Dal’Col Lúcio ◽  
Sidinei José Lopes ◽  
Alberto Cargnelutti Filho ◽  
Tiago Olivoto
Keyword(s):  
Experimental Design ◽  
Fruit Production ◽  
Cherry Tomato ◽  
Border Effect ◽  
Plot Size ◽  
Homogeneity Of Variances ◽  
Randomized Design ◽  
Uniformity Test ◽  
Completely Randomized Design ◽  
Cherry Tomatoes

ABSTRACT: Knowing the productive variability within protected environments is crucial for choosing the experimental design to be used in that conditions. Thus, the aim of the present study was to assess the variability of fruit production in protected environment cultivated with cherry tomatoes and to verify the border effect and plot size in reducing this variability. To this, data from an uniformity test carried out in a greenhouse with cherry tomato cv. ‘Lili’ were used. Total fresh mass of fruits per plant was considered being these plants arranged in cropping rows parallel to the lateral openings of the greenhouse and also the same plants arranged in columns perpendicular to these openings. To generate the borders, different scenarios were designed by excluding rows and columns and using different plot sizes. In each scenario, homogeneity of variances among the remaining rows and columns was tested. There is no variability of fruit production among rows or columns in trials with cherry tomatoes carried out in greenhouses and the use of border does not bring benefits in terms of reduction of coefficient of variation or reduction of cases of variance heterogeneity among rows or columns. Plots with a size equal to or greater than two plants make possible to use the completely randomized design in the cherry tomato trials in greenhouses.

scholarly journals Size of uniformity trials for estimating the optimum plot size for vegetables

2015 ◽  
Vol 33 (3) ◽  
pp. 388-393 ◽  
Author(s):  
Diogo V Schwertner ◽  
Alessandro D Lúcio ◽  
Alberto Cargnelutti Filho
Keyword(s):  
Confidence Interval ◽  
Coefficient Of Variation ◽  
Winter Season ◽  
Plot Size ◽  
Maximum Curvature ◽  
Snap Beans ◽  
Autumn And Winter ◽  
Fruit Mass ◽  
Uniformity Trials ◽  
Variation Model

The aim of this work was to determine the uniformity trial size for estimating the optimum plot size in order to evaluate the fruit mass of tomato, snap-beans and zucchini. The mass of fruits was evaluated in uniformity trials with tomato grown in plastic tunnel in spring-summer and autumn-winter seasons, with snap-beans in plastic greenhouse in autumn-winter season and, with zucchini in plastic greenhouse in summer-autumn and winter-spring seasons. These data were used for planning different sizes of uniformity trials and resampling with replacement was used to estimate the optimum plot size by the method of maximum curvature of the coefficient of variation model. The size of uniformity trials influences the estimation of the optimum plot size for evaluating the mass of fruits of tomato, snap-beans and zucchini. Uniformity trials with tomato with 12 basic experimental units (12 plants) and with snap-beans with 21 basic experimental units (42 plants) are enough for estimating the optimum plot size for evaluating the mass of fruits in plastic tunnel with a confidence interval of 95% minor or equal to two basic experimental units. Uniformity trials with snap-beans with 18 basic experimental units (36 plants) and with zucchini with ten basic experimental units (ten plants) in plastic greenhouse are enough for estimating the optimum plot size for evaluating the mass of fruits with a confidence interval of 95% minor or equal to three basic experimental units.

Size and Shape of Plots for Estimating Yield Losses from Cereal Foliage Diseases

1973 ◽  
Vol 9 (1) ◽  
pp. 63-71 ◽  
Author(s):  
W. C. James ◽  
C. S. Shih
Keyword(s):  
Powdery Mildew ◽  
Coefficient Of Variation ◽  
Yield Variability ◽  
Yield Losses ◽  
Leaf Blotch ◽  
Size And Shape ◽  
Plot Size ◽  
Uniformity Trials

SUMMARYData from uniformity trials on healthy and diseased wheat and oat crops showed that the coefficient of variation for yield decreased as plot size increased and became nearer to square in shape. Infection with Septoria leaf blotch of oats and powdery mildew of wheat did not appear to affect yield variability. Plots larger than rod row size (where 16 ft of the centre row of 3 rows is harvested) are recommended to detect differences of 10 per cent in yield between two treatments.

scholarly journals Automating Uniformity Trials to Optimize Precision of Agronomic Field Trials

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1254
Author(s):  
Marcus Jones ◽  
Marin Harbur ◽  
Ken J. Moore
Keyword(s):  
Web Application ◽  
Unit Area ◽  
Field Trials ◽  
State University ◽  
Iowa State University ◽  
Plot Size ◽  
Maize Field ◽  
Process Uniformity ◽  
Field Plots ◽  
Uniformity Trials

Plot size has an important impact on variation among plots in agronomic field trials, but is rarely considered during the design process. Uniformity trials can inform a researcher about underlying variance, but are seldom used due to their laborious nature. The objective of this research was to describe variation in maize field trials among field plots of varying size and develop a tool to optimize field-trial design using uniformity-trial statistics. Six uniformity trials were conducted in 2015–2016 in conjunction with Iowa State University and WinField United. All six uniformity trials exhibited a negative asymptotic relationship between variance and plot size. Variance per unit area was reduced over 50% with plots 41.8 m2 in size and over 75% when using a plot size >111.5 m2 compared to a 13.9 m2 plot. Plot shape within a fixed plot size did not influence variance. The data illustrated fewer replicates were needed as plot size increased, since larger plots reduced variability. Use of a Shiny web application is demonstrated that allows a researcher to upload a yield map and consider uniformity-trial statistics to inform plot size and replicate decisions.

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