Package 'rhoneycomb'

Title: Analysis of Honeycomb Selection Designs
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>.
Authors: Anastasios Katsileros [aut], Nikos Antonetsis [aut, cre], Marietta Gkika [aut], Eleni Tani [aut], Ioannis Tokatlidis [aut], Penelope Bebeli [aut]
Maintainer: Nikos Antonetsis <[email protected]>
License: GPL (>= 2)
Version: 2.1.0
Built: 2025-02-02 05:41:15 UTC
Source: https://github.com/plantbreedingbiometryaua2/rhoneycomb

Help Index

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,
  ring = 6,
  blocks = FALSE,
  row_element = NULL,
  plant_element = NULL,
  CRS = 5
)

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.
ring

The number of plants per moving ring.
blocks

The moving circular block.
row_element

The position of the plant (number of row) in the centerof 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)

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)

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.

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 an 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 an 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)

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.