Optimizing Bartlett test: a grain yield analysis in soybean
ABSTRACT: This study analyzed the response of the Bartlett test as a function of sample size and to define the optimal sample size for the test with soybean grain yield data. Six experiments were conducted in a randomized block design with 20 or 30 cultivars and three repetitions. Grain yield was de...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universidade Federal de Santa Maria
2022-08-01
|
| Series: | Ciência Rural |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782023000600201&tlng=en |
| _version_ | 1818494860569608192 |
|---|---|
| author | Rafael Rodrigues de Souza Marcos Toebe Anderson Chuquel Mello Karina Chertok Bittencourt Iris Cristina Datsch Toebe |
| author_facet | Rafael Rodrigues de Souza Marcos Toebe Anderson Chuquel Mello Karina Chertok Bittencourt Iris Cristina Datsch Toebe |
| author_sort | Rafael Rodrigues de Souza |
| collection | DOAJ |
| description | ABSTRACT: This study analyzed the response of the Bartlett test as a function of sample size and to define the optimal sample size for the test with soybean grain yield data. Six experiments were conducted in a randomized block design with 20 or 30 cultivars and three repetitions. Grain yield was determined per plant, totaling 9,000 sampled plants. Next, sample scenarios of 1, 2, ..., 100 plants were simulated and the optimal sample size was defined via maximum curvature points. The increase in sampled plants per experimental unit favors Bartlett test’s precision. Also, the sampling of 17 to 20 plants per experimental unit is enough to maintain the accuracy of the test. |
| first_indexed | 2024-12-10T18:12:32Z |
| format | Article |
| id | doaj.art-e8c338c247e9499e9ffd4318189f97bf |
| institution | Directory Open Access Journal |
| issn | 1678-4596 |
| language | English |
| last_indexed | 2024-12-10T18:12:32Z |
| publishDate | 2022-08-01 |
| publisher | Universidade Federal de Santa Maria |
| record_format | Article |
| series | Ciência Rural |
| spelling | doaj.art-e8c338c247e9499e9ffd4318189f97bf2022-12-22T01:38:25ZengUniversidade Federal de Santa MariaCiência Rural1678-45962022-08-0153610.1590/0103-8478cr20220110Optimizing Bartlett test: a grain yield analysis in soybeanRafael Rodrigues de Souzahttps://orcid.org/0000-0002-7068-4079Marcos Toebehttps://orcid.org/0000-0003-2033-1467Anderson Chuquel Mellohttps://orcid.org/0000-0003-4509-957XKarina Chertok Bittencourthttps://orcid.org/0000-0002-4127-0715Iris Cristina Datsch Toebehttps://orcid.org/0000-0001-6831-6624ABSTRACT: This study analyzed the response of the Bartlett test as a function of sample size and to define the optimal sample size for the test with soybean grain yield data. Six experiments were conducted in a randomized block design with 20 or 30 cultivars and three repetitions. Grain yield was determined per plant, totaling 9,000 sampled plants. Next, sample scenarios of 1, 2, ..., 100 plants were simulated and the optimal sample size was defined via maximum curvature points. The increase in sampled plants per experimental unit favors Bartlett test’s precision. Also, the sampling of 17 to 20 plants per experimental unit is enough to maintain the accuracy of the test.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782023000600201&tlng=enanalysis of varianceexperimental planningGlycine maxmathematical assumptions. |
| spellingShingle | Rafael Rodrigues de Souza Marcos Toebe Anderson Chuquel Mello Karina Chertok Bittencourt Iris Cristina Datsch Toebe Optimizing Bartlett test: a grain yield analysis in soybean Ciência Rural analysis of variance experimental planning Glycine max mathematical assumptions. |
| title | Optimizing Bartlett test: a grain yield analysis in soybean |
| title_full | Optimizing Bartlett test: a grain yield analysis in soybean |
| title_fullStr | Optimizing Bartlett test: a grain yield analysis in soybean |
| title_full_unstemmed | Optimizing Bartlett test: a grain yield analysis in soybean |
| title_short | Optimizing Bartlett test: a grain yield analysis in soybean |
| title_sort | optimizing bartlett test a grain yield analysis in soybean |
| topic | analysis of variance experimental planning Glycine max mathematical assumptions. |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782023000600201&tlng=en |
| work_keys_str_mv | AT rafaelrodriguesdesouza optimizingbartletttestagrainyieldanalysisinsoybean AT marcostoebe optimizingbartletttestagrainyieldanalysisinsoybean AT andersonchuquelmello optimizingbartletttestagrainyieldanalysisinsoybean AT karinachertokbittencourt optimizingbartletttestagrainyieldanalysisinsoybean AT iriscristinadatschtoebe optimizingbartletttestagrainyieldanalysisinsoybean |