PreprintData DescriptorVersion 1Preserved in Portico This version is not peer-reviewed
The VIS-Spectrometric Data of Scots Pine Individual Seed Reveal Forecasting Potential for Container-Grown Germination and Seedling’s Dickson Quality Index
Version 1
: Received: 7 December 2023 / Approved: 8 December 2023 / Online: 8 December 2023 (05:47:28 CET)
How to cite:
Novikova, T.P.; Petrishchev, E.P.; Novikov, A.I. The VIS-Spectrometric Data of Scots Pine Individual Seed Reveal Forecasting Potential for Container-Grown Germination and Seedling’s Dickson Quality Index. Preprints2023, 2023120561. https://doi.org/10.20944/preprints202312.0561.v1
Novikova, T.P.; Petrishchev, E.P.; Novikov, A.I. The VIS-Spectrometric Data of Scots Pine Individual Seed Reveal Forecasting Potential for Container-Grown Germination and Seedling’s Dickson Quality Index. Preprints 2023, 2023120561. https://doi.org/10.20944/preprints202312.0561.v1
Novikova, T.P.; Petrishchev, E.P.; Novikov, A.I. The VIS-Spectrometric Data of Scots Pine Individual Seed Reveal Forecasting Potential for Container-Grown Germination and Seedling’s Dickson Quality Index. Preprints2023, 2023120561. https://doi.org/10.20944/preprints202312.0561.v1
APA Style
Novikova, T.P., Petrishchev, E.P., & Novikov, A.I. (2023). The VIS-Spectrometric Data of Scots Pine Individual Seed Reveal Forecasting Potential for Container-Grown Germination and Seedling’s Dickson Quality Index. Preprints. https://doi.org/10.20944/preprints202312.0561.v1
Chicago/Turabian Style
Novikova, T.P., Evgeniy P. Petrishchev and Arthur I. Novikov. 2023 "The VIS-Spectrometric Data of Scots Pine Individual Seed Reveal Forecasting Potential for Container-Grown Germination and Seedling’s Dickson Quality Index" Preprints. https://doi.org/10.20944/preprints202312.0561.v1
Abstract
To follow the growth and development of each tree (N = 1200) Pinus sylvestris L., var. Negorelskaya starting from the seed and continuing at the juvenile (or even generative) stage is the goal of an ambitious project to create a plant passport if possible. Five datasets of replenished empirical (tab-ular and file) and systematic data reflect the early results of a unique ongoing experiment conducted with families moved along a climatic gradient from the collection area (1731 degree days, 722 mm) to the experimental area (2326 degree days; 786 mm). Datasets of morphometric, VIS-spectrometric, and germination seed data, combined with the first results of biometric data (including the Dickson quality index) of seedlings produced from these seeds, will allow scientists in the future to conduct correlation and other statistical analysis, or train a neural network to determine the presence of connections between a seed and a plant. These data contribute to the early non-destructive diag-nosis and grading of seeds according to VIS-spectrometric properties. This dataset structure can complement the FLR-Library. In the future, by tracing seedlings in their early growth (for example, over three growing seasons at the site being restored), it will be possible to determine the degree of intensification of FRM production depending on the initial properties of the seed.
Keywords
Pinus sylvestris L.;Scots pine; seed spectrometric feature; individual seed; container-growm germination; RGB color space; L*a*b* color space; seed size; individual seed mass; Dickson quality index (DQI); forest landscape restoration (FLR)
Subject
Biology and Life Sciences, Forestry
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
