2017
DOI: 10.1590/s0102-053620170302
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Planning and implementing experiments and analyzing experimental data in vegetable crops: problems and solutions

Abstract: The statistical interpretation of experimental results is inherent to the research process. Therefore, every researcher is expected to have basic understanding on the subject. In vegetable crops, the planning, implementing and data gathering is more complex due to specific aspects related to this group of plants, such as intensive management and high labor requirement to carry out the experiments, uneven fruit maturation and heterogeneity of the experimental area. Since all these factors are sources of variabi… Show more

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Cited by 16 publications
(27 citation statements)
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“…These characteristics minimize the effects of the interactions involving the year factor (Yan, 2016). Therefore, the success of any breeding effort greatly depends on the high representativeness and potential for the selection of superior genotypes of each core location, as well as on the homogeneity of the experimental area and on an efficient crop management practice (Lucio & Sari, 2017).…”
Section: Resultsmentioning
confidence: 99%
“…These characteristics minimize the effects of the interactions involving the year factor (Yan, 2016). Therefore, the success of any breeding effort greatly depends on the high representativeness and potential for the selection of superior genotypes of each core location, as well as on the homogeneity of the experimental area and on an efficient crop management practice (Lucio & Sari, 2017).…”
Section: Resultsmentioning
confidence: 99%
“…Experimental planning for the proper choice of plot size is an indispensable procedure for performing tests with experimental precision of acceptable magnitude (SCHWERTNER et al, 2015). When the experimental area is not a limiting factor, it is better to increase the number of repetitions than the plot size (LÚCIO and SARI, 2017). Saving human and financial resources, without losing experimental precision, is considered an important factor in the design of experiments (MICHELS et al, 2015;LÚCIO and SARI, 2017).…”
Section: Introductionmentioning
confidence: 99%
“…The selection of a minimum number of experiments is an essential factor for the good progress of the research [19]. Statistical interpretation of the experimental results is inherent in the research process and the control of the experimental variables can reduce the experimental error.…”
Section: Introductionmentioning
confidence: 99%
“…Statistical interpretation of the experimental results is inherent in the research process and the control of the experimental variables can reduce the experimental error. The knowledge of statistical tests and assumptions are equally critical to make the research statistically valid [19].…”
Section: Introductionmentioning
confidence: 99%