Sample size for principal component analysis in corn

Filho, Alberto Cargnelutti; Toebe, Marcos

doi:10.1590/s1678-3921.pab2021.v56.02510

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…In this regard, Ref. [70] observed that the traits of the cob that are associated most with the grain yield were GYP, NGC, CW, CL, NRC and dry weight of roots, with the exception of total dry matter [71]. In this context, based on the PCA (PC1 and PC2), Figure 4 shows that the crosses of L × L mesocotyls in F 1 and F 2 were those that were mostly associated with PC1, which is characteristic of its greatest relevance in the explanation of the variation observed between mesocotyl crosses.…”

Section: Discussionmentioning

confidence: 99%

Genetic Parameters in Mesocotyl Elongation and Principal Components for Corn in High Valleys, Mexico

Villalobos-González,

Benítez-Riquelme,

Castillo-González

et al. 2024

Seeds

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Corn germplasm with different mesocotyl elongation was characterized for High Valleys in Mexico by estimating the general combinatory aptitude (GCA), specific combinatory aptitude (SCA), heterosis (H), inbreeding depression (ID) and principal component aptitude (PCA), with the purpose of directing the improvement for deep sowing. The hypothesis was that the parents and crosses of mesocotyl present variability in seedling and adult plant traits based on deep sowing. The 36 F1 and F2 crosses—derived from nine parents, three with short mesocotyl (S), three medium (M) and three long (L), obtained through Griffing diallel II—plus the parents were planted in sand beds and polyethylene bags in a greenhouse during the spring–summer cycles of 2021 and 2022. The following traits were measured: length of mesocotyl (LM), length of coleoptile, total seedling dry matter and 10 cob traits in addition to total dry matter. In 11 of the 14 traits, there was a positive and significant correlation (p ≤ 0.05) between the GCA of the parents and their LM. The highest SCA, H and ID (p ≤ 0.05) were for crosses L × L for all the traits measured. When comparing the GCA/SCA proportions, this relation varied from 0.76 to 0.97, which points to practically equal additive effects with those of dominance; however, in parents and L × L crosses, this relation was on average 0.94, 1.07 in M × M, 0.22 in S × S and 0.36 in L × S. In both F1 and F2, the variation was explained by two principal components: 89.5% for GCA and 73.4% for SCA. In both generations, the parents with higher GCA were H-48, HS-2 and Promesa, the three with long mesocotyl, while those with the highest GCA were crosses between these three hybrids.

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Section: Discussionmentioning

confidence: 99%

Genetic Parameters in Mesocotyl Elongation and Principal Components for Corn in High Valleys, Mexico

Villalobos-González,

Benítez-Riquelme,

Castillo-González

et al. 2024

Seeds

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Sample size and genetic divergence: a principal component analysis for soybean traits

Souza

Filho

Toebe

et al. 2023

European Journal of Agronomy

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Sample size affects the precision of the analysis of variance in experiments with cauliflower seedlings

et al. 2023

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This study verified whether sample size would affect the precision of the analysis of variance in experiments with cauliflower seedlings. An experiment was carried out where the number of leaves and shoot, root and total length were measured. For each variable, resamplings with repositions were performed in sample scenarios of 1, 2, …, 100 seedlings per experimental unit, and the sample size was defined for the variance components through Schumacher models and maximum curvature points. The mean squares of the analysis of variance suffer direct interference from the number of sampled seedlings. The sampling of 16 seedlings per experimental unit is enough to estimate the analysis of variance reliably, promoting satisfactory precision gains compared to the sampling of only one seedling per experimental unit.

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Sample size for principal component analysis in corn

Cited by 4 publications

References 17 publications

Genetic Parameters in Mesocotyl Elongation and Principal Components for Corn in High Valleys, Mexico

Genetic Parameters in Mesocotyl Elongation and Principal Components for Corn in High Valleys, Mexico

Sample size and genetic divergence: a principal component analysis for soybean traits

Sample size affects the precision of the analysis of variance in experiments with cauliflower seedlings

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