Effect of dormancy on the emergence of Tabernaemontana heterophylla seedlings in different substrates
Romário de Mesquita Pinheiro,
Henrique Pereira de Carvalho,
Ricardo de Araújo Marques
et al.
Abstract:The composition and dynamics of plant communities are determined by the survival, dispersal and persistence of seeds in the soil, some of the fundamental aspects for understanding plant biology, among which seed dormancy is of particular importance. The aim of this work was to find out whether seed dormancy is affected by certain substrates in order to improve the production of Tabernaemontana heterophylla seedlings. Treatments were carried out with different substrates (T1. Sand, T2. Vegetable clay, T3. Veget… Show more
The analysis of Tabernaemontana heterophylla seeds entails morphological characterization and the study of genetic variability between batches. This knowledge is fundamental for evolutionary biology and agronomic and conservation practices. Crop productivity, species preservation, reforestation, and post-harvest processing can all benefit from understanding and considering seed size. This work aimed to determine the multidimensional characteristics and mass of the seeds using multivariate cluster analysis. We investigated multidimensional characteristics by measuring the dimensions and mass of the seeds and computing their physical attributes. Several statistical measures were used to assess the morphometric data, including the mean, amplitude, coefficient of variation, relative frequency, arithmetic mean, standard deviation, and confidence interval. In addition, grouping patterns and inter-variable dependencies were examined by multivariate cluster analysis using Ward’s method. The results revealed significant variability in seed dimensions, indicating morphological unevenness in the seeds of this species. Euclidean distance analysis identified the formation of subclusters, implying distinct groupings based on seed size and mass. The finding highlights the significance of segregating lots with similar physical characteristics and defining representative properties for management practices. These variations reflect the genetic diversity required for adaptability and ecological resilience, ensuring forest ecosystems’ survival and proper functioning. Alternatively, classifying and standardizing seed lots based on these physical traits can optimize post-harvest processing and increase agronomic productivity.
The analysis of Tabernaemontana heterophylla seeds entails morphological characterization and the study of genetic variability between batches. This knowledge is fundamental for evolutionary biology and agronomic and conservation practices. Crop productivity, species preservation, reforestation, and post-harvest processing can all benefit from understanding and considering seed size. This work aimed to determine the multidimensional characteristics and mass of the seeds using multivariate cluster analysis. We investigated multidimensional characteristics by measuring the dimensions and mass of the seeds and computing their physical attributes. Several statistical measures were used to assess the morphometric data, including the mean, amplitude, coefficient of variation, relative frequency, arithmetic mean, standard deviation, and confidence interval. In addition, grouping patterns and inter-variable dependencies were examined by multivariate cluster analysis using Ward’s method. The results revealed significant variability in seed dimensions, indicating morphological unevenness in the seeds of this species. Euclidean distance analysis identified the formation of subclusters, implying distinct groupings based on seed size and mass. The finding highlights the significance of segregating lots with similar physical characteristics and defining representative properties for management practices. These variations reflect the genetic diversity required for adaptability and ecological resilience, ensuring forest ecosystems’ survival and proper functioning. Alternatively, classifying and standardizing seed lots based on these physical traits can optimize post-harvest processing and increase agronomic productivity.
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