Studying the spectrometric features of forest seeds to improve sowing qualities: a retrospective cluster analysis of the scientific landscape trends

Author:

Novikova Tatyana1,Novikov Arthur1,Petrishchev E.1

Affiliation:

1. Voronezh State University of Forestry and Technologies named after G.F. Morozov

Abstract

Forest seeds spectral data in the visible and infrared regions of electromagnetic radiation lengths quite effectively differentiate the origin, viability, types of seeds, their infestation with pests and diseases, the ability to absorb and lose water. The search for a method of seed testing that is both experimentally simple, fast and effective for predicting germination is necessary to increase the energy efficiency of forest nurseries in the production of planting material. The retrospective references systematization (N = 55, 1998-2023, terms [Scholar Query = seeds* AND (spectr* OR optic*) (properties OR features) AND analysis]) into clusters was carried out on the basis of eight performance criteria represented by rank variables. The level of similarity and difference between clusters is determined by the method of the most distant neighbors with the grouping of data by the square of the Euclidean distance. The most distant criterion from other criteria is the level of invasiveness of testing (the square of the Euclidean distance is 25, p < 0.05). Correlation analysis of nonparametric criteria indicates a direct strong interaction between the level of financial and organizational costs (Spearman coefficient ρ = 0.77; p = 0.0008), time costs and low machine learning capability (ρ = 0.725; p = 0.0008). In the future, it is planned to periodically supplement the set of systematic data to obtain an objective assessment of seed testing methods, as well as using a seed passport to evaluate the relationship of RGB spectral data of more than 1 000 individual seeds with early growth of seedlings in a post-pyrogenic experimental site of the forest landscape of the Voronezh region by example (Pinus sylvestris L. var. Negorelskaya).

Publisher

Voronezh State University of Forestry and Technologies named after G.F. Morozov

Reference64 articles.

1. McDonald, M.B. Computer Imaging to Improve Seed Quality Determinations / M.B. McDonald, K. Fujimura, Y. Sako et al. // Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology. – 2015. – P. 15-28. – Mode of access: http://doi.wiley.com/10.2134/asaspecpub66.c2., McDonald, M.B. Computer Imaging to Improve Seed Quality Determinations / M.B. McDonald, K. Fujimura, Y. Sako et al. // Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology. – 2015. – P. 15-28. – Mode of access: http://doi.wiley.com/10.2134/asaspecpub66.c2.

2. Novikov, A.I. The effect of sorting Scots pine seeds by color and size on their soil germination in containers // Coniferous boreal zones. – 2019. – Vol. 37. – № 5. – P. 313-319. – URL: https://www.elibrary.ru/item.asp?id=42337219., Novikov, A.I. The effect of sorting Scots pine seeds by color and size on their soil germination in containers // Coniferous boreal zones. – 2019. – Vol. 37. – № 5. – P. 313-319. – URL: https://www.elibrary.ru/item.asp?id=42337219.

3. New optoelectronic systems for express analysis of seeds in forestry production / S.V. Sokolov et al. // Forestry Engineering Journal. – 2019. – Vol. 9, № 2(34). – P. 5-13. – DOI 10.34220/issn.2222-7962/2019.2/1. – https://elibrary.ru/CNXAWZ., New optoelectronic systems for express analysis of seeds in forestry production / S.V. Sokolov et al. // Forestry Engineering Journal. – 2019. – Vol. 9, № 2(34). – P. 5-13. – DOI 10.34220/issn.2222-7962/2019.2/1. – https://elibrary.ru/CNXAWZ.

4. Novikov, A.I. Express analysis of forest seeds by biophysical methods – Voronezh : Voronezh State University of Forestry and Tecnologies named after G.F. Morozov, 2018. – 128 p. – URL: https://elibrary.ru/yzuzgx., Novikov, A.I. Express analysis of forest seeds by biophysical methods – Voronezh : Voronezh State University of Forestry and Tecnologies named after G.F. Morozov, 2018. – 128 p. – URL: https://elibrary.ru/yzuzgx.

5. The effect of the individual seed mass of Negorelskaya variety Scots pine (Pinus sylvestris L.) on 30-day germination in 40-cell SideSlit growing containers / S. Rabko et al. // Forestry Engineering Journal. – 2023. – Vol. 13. – № 2. – P. 59-86. – DOI: https://doi.org/10.34220/issn.2222-7962/2023.2/4., The effect of the individual seed mass of Negorelskaya variety Scots pine (Pinus sylvestris L.) on 30-day germination in 40-cell SideSlit growing containers / S. Rabko et al. // Forestry Engineering Journal. – 2023. – Vol. 13. – № 2. – P. 59-86. – DOI: https://doi.org/10.34220/issn.2222-7962/2023.2/4.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3