Sample size to estimate the mean of traits in jack bean

Abstract

ABSTRACT:In experiments, it is important to evaluate sufficient number of plants, so that inferences have the desired precision. The objective of this research was to determine the sample size (i.e., number of plants) required to estimate the mean of jack bean traits (Canavalia ensiformis) with precision levels. In experimental area of 10 × 16 m (160 m 2 ), 194 plants were collected randomly at 202 days after sowing. The morphological (plant height, stem diameter, number of nodes, and number of leaves) and productive traits (number of pods, fresh matter of pods, fresh matter of aerial part without pods, fresh matter of aerial part, dry matter of pods, dry matter of aerial part without pods, and dry matter of aerial part) were measured in each plant. Measures of central tendency, variability, skewness, and kurtosis were calculated for each trait. The sample size was determined by resampling with replacement of 10,000 resamples. In order to estimate the mean of morphological and productive traits of jack bean with the amplitude of the confidence interval of 95% equal to 40% of the estimated mean, 114 plants are required.

Sample Size to Estimate the Mean and Median of Traits in Canola

“…In addition, differentiated sample size is expected between hybrids, i.e., larger sample size for Hyola 433, intermediate for Hyola 61, and smaller for Hyola 76. Larger coefficients of variation for productive traits in relation to morphological traits were also found in white lupine (Burin et al, 2014), forage turnip (Cargnelutti Filho et al, 2014), black oat (Cargnelutti Filho et al, 2015b), and flax (Cargnelutti Filho et al, 2018).…”

“…Sample size variability between traits for median estimation was also observed in agricultural crops, such as white lupine (Burin et al, 2014) and flax (Cargnelutti Filho et al, 2018). Among the traits for the three hybrids, larger sample sizes were found for productive traits (NS, FMS, FMWS, FM, DMS, DMWS, and DM) in relation to the morphological one (PH), as verified in white lupine (Burin et al, 2014) and flax (Cargnelutti Filho et al, 2018). Table 3.…”

“…At the other extreme, the sample size (number of plants) for mean estimation of these eight traits (PH, NS, FMS, FMWS, FM, DMS, DMWS, and DM) of canola hybrids with amplitude of confidence interval of 95% equals to 30% of the mean estimate (lower precision) ranged from 12 to 175 for Hyola 61, 5 to 125 for Hyola 76, and 10 to 208 for Hyola 433, respectively for the traits plant height and dry matter of siliques. Sample size variability between traits for mean estimation was also verified in agricultural crops, such as white lupine (Burin et al, 2014), forage turnip (Cargnelutti Filho et al, 2014), black oat Cargnelutti Filho et al, 2015b), millet (Kleinpaul et al, 2017), rye (Bandeira et al, 2018a, Bandeira et al, 2018b, and flax (Cargnelutti Filho et al, 2018). Among the traits for the three hybrids, larger sample sizes are required for the productive traits (NS, FMS, FMWS, FM, DMS, DMWS, and DM) in relation to the morphological one (PH), being explained by greater CV values by the productive traits in relation to the morphological one.…”

“…Among the traits for the three hybrids, larger sample sizes are required for the productive traits (NS, FMS, FMWS, FM, DMS, DMWS, and DM) in relation to the morphological one (PH), being explained by greater CV values by the productive traits in relation to the morphological one. Larger sample sizes of the productive traits in relation to the morphological traits were also obtained in white lupine (Burin et al, 2014), forage turnip (Cargnelutti Filho et al, 2014), black oat (Cargnelutti Filho et al, 2015b), and flax (Cargnelutti Filho et al, 2018). Table 2.…”

“…Resampling with reposition is an appropriate procedure for sample sizing and exhibits independence of the data probability distribution (Ferreira, 2009). This procedure was used to determine the sample size for the mean estimation in agricultural crops, such as millet (Kleinpaul et al, 2017) and rye (Bandeira et al, 2018a) and for the estimation of mean and median of white lupine (Burin, Cargnelutti Filho, Toebe, Alves, & Fick, 2014) and flax (Cargnelutti Filho et al, 2018). Meantime, a methodology based on Student's t distribution (Bussab & Morettin, 2017) has been used to determine the sample size for the mean estimation of forage turnip (Cargnelutti Filho et al, 2014), black oat (Cargnelutti Filho et al, 2015b), and rye (Bandeira et al, 2018b).…”