| Title: | Analysis of Honeycomb Selection Designs |
| Version: | 2.3.4 |
| Description: | A useful statistical tool for the construction and analysis of Honeycomb Selection Designs. More information about this type of designs: Fasoula V. (2013) <doi:10.1002/9781118497869.ch6> Fasoula V.A., and Tokatlidis I.S. (2012) <doi:10.1007/s13593-011-0034-0> Fasoulas A.C., and Fasoula V.A. (1995) <doi:10.1002/9780470650059.ch3> Tokatlidis I. (2016) <doi:10.1017/S0014479715000150> Tokatlidis I., and Vlachostergios D. (2016) <doi:10.3390/d8040029>. |
| Depends: | R (≥ 4.2) |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.3 |
| Suggests: | knitr, rmarkdown |
| VignetteBuilder: | knitr |
| LazyData: | true |
| Imports: | stats, utils, graphics |
| NeedsCompilation: | no |
| Packaged: | 2023-08-23 18:31:51 UTC; Windows |
| Author: | Anastasios Katsileros [aut], Nikos Antonetsis [aut, cre], Marietta Gkika [aut], Eleni Tani [aut], Ioannis Tokatlidis [aut], Penelope Bebeli [aut] |
| Maintainer: | Nikos Antonetsis <stud610027@aua.gr> |
| Repository: | CRAN |
| Date/Publication: | 2023-08-23 18:50:02 UTC |
Construction of the honeycomb selection design.
Description
This function creates a data frame of a honeycomb selection design.
Usage
HSD(E, K, rows, plpr, distance, poly = TRUE, control = FALSE)
Arguments
E |
The number of entries. |
K |
The k parameter. |
rows |
The number of rows. |
plpr |
The number of plants per row. |
distance |
The plant-to-plant distance in meters. |
poly |
If TRUE the polygon pattern is displayed. |
control |
Convert the design to controlled. |
Value
A dataframe.
References
Fasoula V. (2013). Prognostic Breeding: A New Paradigm for Crop Improvement. Plant Breeding Reviews 37: 297-347. 10.1002/9781118497869.ch6. doi:10.1002/9781118497869.ch6
Fasoula V.A., and Tokatlidis I.S. (2012). Development of crop cultivars by honeycomb breeding. Agronomy for Sustainable Development 32:161–180. 10.1007/s13593-011-0034-0 doi:10.1007/s13593-011-0034-0
Fasoulas A.C., and Fasoula V.A. (1995). Honeycomb selection designs. In J. Janick (ed.). Plant Breeding Reviews 13: 87-139. doi:10.1002/9780470650059.ch3
Tokatlidis I. (2016). Sampling the spatial heterogeneity of the honeycomb model in maize and wheat breeding trials: Analysis of secondary data compared to popular classical designs. Experimental Agriculture, 52(3), 371-390. doi:10.1017/S0014479715000150
Tokatlidis I., and Vlachostergios D. (2016). Sustainable Stewardship of the Landrace Diversity. Diversity 8(4):29. doi:10.3390/d8040029
Examples
HSD(7,2,10,10,1)
Construction of the honeycomb selection design without control.
Description
This function creates a data frame of a honeycomb selection design (one entry, without control).
Usage
HSD0(rows, plpr, distance, poly = TRUE)
Arguments
rows |
The number of rows. |
plpr |
The number of plants per row. |
distance |
The plant-to-plant distance in meters. |
poly |
If TRUE set polygon pattern is displayed. |
Value
A dataframe.
References
Fasoula V. (2013). Prognostic Breeding: A New Paradigm for Crop Improvement. Plant Breeding Reviews 37: 297-347. 10.1002/9781118497869.ch6. doi:10.1002/9781118497869.ch6
Fasoula V.A., and Tokatlidis I.S. (2012). Development of crop cultivars by honeycomb breeding. Agronomy for Sustainable Development 32:161–180. 10.1007/s13593-011-0034-0 doi:10.1007/s13593-011-0034-0
Fasoulas A.C., and Fasoula V.A. (1995). Honeycomb selection designs. In J. Janick (ed.). Plant Breeding Reviews 13: 87-139. doi:10.1002/9780470650059.ch3
Tokatlidis I. (2016). Sampling the spatial heterogeneity of the honeycomb model in maize and wheat breeding trials: Analysis of secondary data compared to popular classical designs. Experimental Agriculture, 52(3), 371-390. doi:10.1017/S0014479715000150
Tokatlidis I., and Vlachostergios D. (2016). Sustainable Stewardship of the Landrace Diversity. Diversity 8(4):29. doi:10.3390/d8040029
Examples
HSD0(10,10,1)
Construction of the honeycomb selection design with one control.
Description
This function creates a data frame of a honeycomb selection design (one entry, one control).
Usage
HSD01(K, rows, plpr, distance, poly = TRUE)
Arguments
K |
The K parameter. |
rows |
The number of rows. |
plpr |
The number of plants per row. |
distance |
Distance between plants in meters. |
poly |
If TRUE the polygon pattern is displayed. |
Value
A dataframe.
References
Fasoula V. (2013). Prognostic Breeding: A New Paradigm for Crop Improvement. Plant Breeding Reviews 37: 297-347. 10.1002/9781118497869.ch6. doi:10.1002/9781118497869.ch6
Fasoula V.A., and Tokatlidis I.S. (2012). Development of crop cultivars by honeycomb breeding. Agronomy for Sustainable Development 32:161–180. 10.1007/s13593-011-0034-0 doi:10.1007/s13593-011-0034-0
Fasoulas A.C., and Fasoula V.A. (1995). Honeycomb selection designs. In J. Janick (ed.). Plant Breeding Reviews 13: 87-139. doi:10.1002/9780470650059.ch3
Tokatlidis I. (2016). Sampling the spatial heterogeneity of the honeycomb model in maize and wheat breeding trials: Analysis of secondary data compared to popular classical designs. Experimental Agriculture, 52(3), 371-390. doi:10.1017/S0014479715000150
Tokatlidis I., and Vlachostergios D. (2016). Sustainable Stewardship of the Landrace Diversity. Diversity 8(4):29. doi:10.3390/d8040029
Examples
HSD01(1,10,10,1)
Construction of the honeycomb selection design with three controls.
Description
This function creates a data frame of a honeycomb selection design (one entry, three controls).
Usage
HSD03(K, rows, plpr, distance, poly = TRUE)
Arguments
K |
The k parameter. |
rows |
The number of rows. |
plpr |
The number of plants per row. |
distance |
Distance between plants in meters. |
poly |
If TRUE the polygon pattern is displayed. |
Value
A dataframe
References
Fasoula V. (2013). Prognostic Breeding: A New Paradigm for Crop Improvement. Plant Breeding Reviews 37: 297-347. 10.1002/9781118497869.ch6. doi:10.1002/9781118497869.ch6
Fasoula V.A., and Tokatlidis I.S. (2012). Development of crop cultivars by honeycomb breeding. Agronomy for Sustainable Development 32:161–180. 10.1007/s13593-011-0034-0 doi:10.1007/s13593-011-0034-0
Fasoulas A.C., and Fasoula V.A. (1995). Honeycomb selection designs. In J. Janick (ed.). Plant Breeding Reviews 13: 87-139. doi:10.1002/9780470650059.ch3
Tokatlidis I. (2016). Sampling the spatial heterogeneity of the honeycomb model in maize and wheat breeding trials: Analysis of secondary data compared to popular classical designs. Experimental Agriculture, 52(3), 371-390. doi:10.1017/S0014479715000150
Tokatlidis I., and Vlachostergios D. (2016). Sustainable Stewardship of the Landrace Diversity. Diversity 8(4):29. doi:10.3390/d8040029
Examples
HSD03(1,10,10,1)
Analysis of honeycomb selection design based on blocks of unique nearby entries.
Description
A Function to analyze blocks of entries. The "central" plant in each position is not calculated.
Usage
analize_blocks(
Main_Data_Frame = NULL,
observation = NULL,
row_element = NULL,
plant_element = NULL,
CRS,
rep_unrep
)
Arguments
observation |
A vector containing the observations. |
row_element |
The row of the element which the block it belongs to will be displayed. |
plant_element |
The position of the element in the row which the block it belongs to will be displayed. |
CRS |
Number of top plants used for the CRS index. |
rep_unrep |
Replicated of unreplicated design. |
Value
A dataframe.
Analysis of the honeycomb selection design.
Description
This function analyzes the response variable of the data frame.
Usage
analysis(
Main_Data_Frame = NULL,
Response_Vector = NULL,
circle = 6,
blocks = FALSE,
row_element = NULL,
plant_element = NULL,
CRS = NULL
)
Arguments
Main_Data_Frame |
A data frame generated by one of the functions HSD(), HSD0(), HSD01() and HSD03(). |
Response_Vector |
A vector containing the response variable data. |
circle |
The number of plants per moving ring. |
blocks |
The moving circular block. |
row_element |
The position of the plant (number of row) in the center of a moving ring/circular block. |
plant_element |
The position of the plant (number of plant) in the center of a moving ring/circular block. |
CRS |
The number of selected plants used for the CRS index. |
Value
A list.
References
Fasoula V. (2013). Prognostic Breeding: A New Paradigm for Crop Improvement. Plant Breeding Reviews 37: 297-347. 10.1002/9781118497869.ch6. doi:10.1002/9781118497869.ch6
Fasoula V.A., and Tokatlidis I.S. (2012). Development of crop cultivars by honeycomb breeding. Agronomy for Sustainable Development 32:161–180. 10.1007/s13593-011-0034-0 doi:10.1007/s13593-011-0034-0
Fasoulas A.C., and Fasoula V.A. (1995). Honeycomb selection designs. In J. Janick (ed.). Plant Breeding Reviews 13: 87-139. doi:10.1002/9780470650059.ch3
Tokatlidis I. (2016). Sampling the spatial heterogeneity of the honeycomb model in maize and wheat breeding trials: Analysis of secondary data compared to popular classical designs. Experimental Agriculture, 52(3), 371-390. doi:10.1017/S0014479715000150
Tokatlidis I., and Vlachostergios D. (2016). Sustainable Stewardship of the Landrace Diversity. Diversity 8(4):29. doi:10.3390/d8040029
Examples
main_data<-HSD(7,2,10,10,1)
main_data$Data<-wheat_data$total_yield
analysis(main_data,"Data",6)
Available honeycomb selection designs.
Description
This function is used to generate the available honeycomb selection designs including k parameters.
Usage
generate(E_gen = NULL)
Arguments
E_gen |
A single number or a vector of entries. |
Value
A dataframe.
References
Fasoula V. (2013). Prognostic Breeding: A New Paradigm for Crop Improvement. Plant Breeding Reviews 37: 297-347. 10.1002/9781118497869.ch6. doi:10.1002/9781118497869.ch6
Fasoula V.A., and Tokatlidis I.S. (2012). Development of crop cultivars by honeycomb breeding. Agronomy for Sustainable Development 32:161–180. 10.1007/s13593-011-0034-0 doi:10.1007/s13593-011-0034-0
Fasoulas A.C., and Fasoula V.A. (1995). Honeycomb selection designs. In J. Janick (ed.). Plant Breeding Reviews 13: 87-139. doi:10.1002/9780470650059.ch3
Tokatlidis I. (2016). Sampling the spatial heterogeneity of the honeycomb model in maize and wheat breeding trials: Analysis of secondary data compared to popular classical designs. Experimental Agriculture, 52(3), 371-390. doi:10.1017/S0014479715000150
Tokatlidis I., and Vlachostergios D. (2016). Sustainable Stewardship of the Landrace Diversity. Diversity 8(4):29. doi:10.3390/d8040029
Examples
generate(1:50)
This function returns a plot.
Description
It prints a graphic.
Usage
plot_convert(dataf, poly = TRUE, y_rev = TRUE, x_rev = FALSE, rep_unrep = NULL)
Arguments
dataf |
Data frame containing information about the experiment. |
poly |
If TRUE set the polygon pattern. |
y_rev |
Reverse the y axis. |
x_rev |
Reverse the x axis. |
rep_unrep |
Replicated or unreplicated selection design. |
Value
A dataframe.
This function returns only the grouped replicated selection designs.
Description
It calls the check for R function and keeps only the grouped selection designs.
Usage
return_grouped(R_gen)
Arguments
R_gen |
A single number or vector containing the replicated selection designs for testing. |
Value
A dataframe.
This function returns only the ungrouped replicated selection designs.
Description
It calls the check for R function and keeps only the Ungrouped selection designs.
Usage
return_ungrouped(R_gen)
Arguments
R_gen |
A single number or vector containing the replicated selection designs for testing. |
Value
A dataframe.
Tests if a selection design exists and returns its X and Y values.
Description
It is used to return the X and Y values of a replicated selection design if it exists.
Usage
test_for_R(R_gen)
Arguments
R_gen |
A single number or vector containing the replicated selection designs for testing. |
Value
A dataframe.
A dataset
Description
A dataset containing observations from an R7 honeycomb selection design.
Usage
wheat_data
Format
- wheat_data$main_spike_weight
The weight (g) of the main spike of a single plant.
- wheat_data$tillers_spike_weight
The weight (g) of tillers' spikes of a single plant.
- wheat_data$total_yield
The total yield (g) of a single plant.