Correlation between the Spectrometric Parameters of Coniferous Seeds and the Molecular Indicators of Seedlings: Is It Possible to Apply It in Practice? †
Abstract
:1. Introduction
2. First Application
3. Second Application
- there is a universal criterion for selecting viable seeds with certain improved genetic characteristics;
- availability of an optimal method for conducting such testing; and
- availability of technical means for such testing that meet the requirements of energy conservation and environmental safety.
4. Third Application
- released as a result of felling (including burning felling), which makes it inefficient for the operational technology of ground-based seeding or planting;
- released as a result of forest fires that are not effective for the operational technology of ground-based seeding or planting;
- inaccessible to ground-based mechanization facilities for climatic and geomorphological reasons; and
- inaccessible to people due to the complication of the radiation background and after man-made disasters.
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Mansuy, N.; Burton, P.J.; Stanturf, J.; Beatty, C.; Mooney, C.; Besseau, P.; Degenhardt, D.; MacAfee, K.; Lapointe, R. Scaling up forest landscape restoration in Canada in an era of cumulative effects and climate change. For. Policy Econ. 2020, 116, 102177. [Google Scholar] [CrossRef]
- Stanturf, J.A.; Palik, B.J.; Dumroese, R.K. Contemporary forest restoration: A review emphasizing function. For. Ecol. Manag. 2014, 331, 292–323. [Google Scholar] [CrossRef]
- Elliott, S.; Chairuangsri, S.; Kuaraksa, C.; Sangkum, S.; Sinhaseni, K.; Shannon, D.; Nippanon, P.; Manohan, B. Collaboration and Conflict—Developing Forest Restoration Techniques for Northern Thailand’s Upper Watersheds Whilst Meeting the Needs of Science and Communities. Forests 2019, 10, 732. [Google Scholar] [CrossRef]
- Sabogal, C.; Besacier, C.; McGuire, D. Forest and landscape restoration: Concepts, approaches and challenges for implementation. Unasylva 2015, 66, 3. [Google Scholar]
- Novikov, A.I.; Sokolov, S.; Drapalyuk, M.; Zelikov, V.; Ivetić, V. Performance of Scots pine seedlings from seeds graded by colour. Forests 2019, 10, 1064. [Google Scholar] [CrossRef]
- Mattheus, R.E.F. Plant Virology; Academic Press Inc.: New Work, NY, USA, 1970; 685p. [Google Scholar]
- González-Martínez, S.C.; Krutovsky, K.V.; Neale, D.B. Forest-tree population genomics and adaptive evolution. New Phytol. 2006, 170, 227–238. [Google Scholar] [CrossRef]
- Ivetić, V.; Novikov, A.I. The role of forest reproductive material quality in forest restoration. For. Eng. J. 2019, 9, 56–65. [Google Scholar]
- Hampton, J.G. What is seed quality? Seed Sci. Technol. 2002, 30, 1–10. [Google Scholar]
- Basu, R.N. Seed viability. In Seed quality: Basic mechanisms and agricultural implications; Basra, A.S., Ed.; CRC Press, Taylor & Francis: New York, NY, USA, 1995; Volume 1, pp. 1–44. [Google Scholar]
- Alekseychuk, G.N.; Laman, N.A. Physiological Quality of Seeds of Agricultural Crops and Methods of Its Assessment; Law and Economics: Minsk, Belarus, 2005. [Google Scholar]
- Owens, J.N.; Morris, S.J.; Catalano, G.L. How the pollination mechanism and prezygotic and postzygotic events affect seed production in Larix occidentalis. Can. J. For. Res. 1994, 24, 917–927. [Google Scholar] [CrossRef]
- Tigabu, M.; Daneshvar, A.; Wu, P.; Ma, X.; Christer Odén, P. Rapid and non-destructive evaluation of seed quality of Chinese fir by near infrared spectroscopy and multivariate discriminant analysis. New For. 2020, 51, 395–408. [Google Scholar] [CrossRef]
- Tigabu, M.; Odén, P.C. Simultaneous detection of filled, empty and insect-infested seeds of three Larix species with single seed near-infrared transmittance spectroscopy. New For. 2004, 27, 39–53. [Google Scholar] [CrossRef]
- Tigabu, M.; Odén, P.C.; Shen, T.Y. Application of near-infrared spectroscopy for the detection of internal insect infestation in Picea abies seed lots. Can. J. For. Res. 2004, 34, 76–84. [Google Scholar] [CrossRef]
- Tigabu, M.; Odén, P.C. Rapid and non-destructive analysis of vigour of Pinus patula seeds using single seed near infrared transmittance spectra and multivariate analysis. Seed Sci. Technol. 2004, 32, 593–606. [Google Scholar] [CrossRef]
- Gutterman, Y. Maternal effects on seeds during development. In Seeds: The Ecology of Regeneration in Plant Communities, 2nd ed.; Fenner, M., Ed.; CABI Publishing: New York, NY, USA, 2000; pp. 59–84. [Google Scholar]
- Mamo, N.; Mihretu, M.; Fekadu, M.; Tigabu, M.; Teketay, D. Variation in seed and germination characteristics among Juniperus procera populations in Ethiopia. For. Ecol. Manag. 2006, 225, 320–327. [Google Scholar] [CrossRef]
- Koralewski, T.E.; Brooks, J.E.; Krutovsky, K.V. Molecular evolution of drought tolerance and wood strength related candidate genes in loblolly pine (Pinus taeda L.). Silvae Genet. 2014, 63, 59–66. [Google Scholar]
- Lázaro-Lobo, A.; Herrera, M.; Campos, J.A.; Caño, L.; Goñi, E.; Ervin, G.N. Influence of local adaptations, transgenerational effects and changes in offspring’s saline environment on Baccharis halimifolia L. under different salinity and light levels. Environ. Exp. Bot. 2020, 177, 104134. [Google Scholar] [CrossRef]
- Knyazeva, S.G.; Hantemirova, E. V Comparative analysis of genetic and morpho-anatomical variability of common juniper (Juniperus communis L.). Russ. J. Genet. 2020, 56, 48–58. [Google Scholar] [CrossRef]
- Ellegren, H. Genome sequencing and population genomics in non-model organisms. Trends Ecol. Evol. 2014, 29, 51–63. [Google Scholar] [CrossRef]
- Millar, C.I.; Stephenson, N.L. Temperate forest health in an era of emerging megadisturbance. Science 2015, 349, 823–826. [Google Scholar] [CrossRef]
- Soltis, P.S.; Marchant, D.B.; Van de Peer, Y.; Soltis, D.E. Polyploidy and genome evolution in plants. Curr. Opin. Genet. Dev. 2015, 35, 119–125. [Google Scholar] [CrossRef]
- Novikov, A.I.; Ivetić, V.; Novikova, T.P.; Petrishchev, E.P. Scots pine seedlings growth dynamics data reveals properties for the future proof of seed coat color grading conjecture. Data 2019, 4, 106. [Google Scholar] [CrossRef]
- Albekov, A.U.; Drapalyuk, M.V.; Morkovina, S.S.; Vovchenko, N.G.; Novikov, A.I.; Sokolov, S.V.; Novikova, T.P. Express Analyzer of Seed Quality. RU Patent 2,675,056, 14 December 2018. [Google Scholar]
- Jahnke, S.; Roussel, J.; Hombach, T.; Kochs, J.; Fischbach, A.; Huber, G.; Scharr, H. phenoSeeder—A robot system for automated handling and phenotyping of individual seeds. Plant Physiol. 2016, 172, 1358–1370. [Google Scholar] [CrossRef] [PubMed]
- Kovalev, S.M.; Sokolov, S.V.; Kucherenko, P.A. Intelligent processing of temporal data based on hybrid fuzzy-stochastic models. Autom. Control Comput. Sci. 2015, 49, 1–10. [Google Scholar] [CrossRef]
- Sokolov, S.V.; Kovalev, S.M.; Kucherenko, P.A.; Smirnov, Y.A. Methods for Identifying Fuzzy and Stochastic Systems; Fizmatlit: Moscow, Russia, 2018; 432p. [Google Scholar]
- Ivetić, V.; Devetaković, J.; Nonić, M.; Stanković, D.; Šijačić-Nikolić, M. Genetic diversity and forest reproductive material—from seed source selection to planting. iForest Biogeosci. For. 2016, 9, 801–812. [Google Scholar] [CrossRef]
- Novikov, A.I. Forest seeds rapid analysis: The choice of the effective quality indicator. In Proceedings of the Proceeding in Ecological and Biological Bases of Increasing Productivity and Sustainability of Natural and Artificially Renewed Forest Ecosystems, Voronezh, Russia, 4–6 October 2018; Voronezh State University of Forestry and Technologies Named after G.F. Morozov: Voronezh, Russia, 2018; pp. 559–567. [Google Scholar]
- Ivetić, V.; Grossnickle, S.; Škorić, M. Forecasting the field performance of Austrian pine seedlings using morphological attributes. iForest Biogeosci. For. 2016, 10, 99–107. [Google Scholar] [CrossRef]
- Pravdin, L.F. The main regularities of the geographical variability of Scots pine (Pinus sylvestris L.). In Fundamentals of Forest Science and Forestry; Forestry Publ.: Moscow, Russia, 1960; pp. 245–250. [Google Scholar]
- Tikhonova, I.V.; Tarakanov, V.V.; Tikhonova, N.A.; Barchenkov, A.P.; Ekart, A.K. Population variability of cones and seeds of scots pine by phenes of color and traits-indices in the south of Siberia. Contemp. Probl. Ecol. 2014, 7, 60–66. [Google Scholar] [CrossRef]
- Rogozin, M.V. Cryptic effect of tree characters on the growth of the progeny. In Proceedings of the Lesnaya Genetika, Selektsiya i Fiziologiya Drevesnykh Rasteniĭ; VFEI Publ.: Voronezh, Russia, 1989; pp. 177–179. (In Russian) [Google Scholar]
- Vidyakin, A.I. Phenes of woody plants: Identification, scaling, and use in population studies (An Example of Pinus sylvestris L.). Russ. J. Ecol. 2001, 32, 179–184. [Google Scholar] [CrossRef]
- Müller-Olsen, C.; Simak, M.; Gustafsson, Å. Germination analyses by the X-ray method. Rep. For. Res. Inst. Swed. 1956, 46, 1–12. [Google Scholar]
- Simak, M. The X-ray contrast method for seed testing Scots Pine—Pinus silvestris. Medd. från Statens skogsforskningsinstitut 1957, 47, 1–22. [Google Scholar]
- Linskens, H.F.; Jackson, J.F. Seed Analysis; Linskens, H.F., Jackson, J.F., Eds.; Modern Methods of Plant Analysis; Springer: Berlin/Heidelberg, Germany, 1992; 380p. [Google Scholar]
- Tillman-Sutela, E.; Kauppi, A. The morphological background to imbibition in seeds of Pinus sylvestris L. of different provenances. Trees 1995, 9, 123–133. [Google Scholar] [CrossRef]
- Lestander, T.A.; Odén, P.C. Separation of viable and non-viable filled Scots pine seeds by differentiating between drying rates using single seed near infrared transmittance spectroscopy. Seed Sci. Technol. 2002, 30, 383–392. [Google Scholar]
- Repo, T.; Paine, D.H.; Taylor, A.G. Electrical impedance spectroscopy in relation to seed viability and moisture content in snap bean (Phaseolus vulgaris L.). Seed Sci. Res. 2002, 12, 17–29. [Google Scholar]
- Tigabu, M.; Oden, P.C.; Lindgren, D. Identification of seed sources and parents of Pinus sylvestris L. using visible–near infrared reflectance spectra and multivariate analysis. Trees 2005, 19, 468–476. [Google Scholar]
- Farhadi, M.; Tigabu, M.; Odén, P. Near infrared spectroscopy as non-destructive method for sorting viable, petrified and empty seeds of Larix sibirica. Silva Fenn. 2015, 49, 1340. [Google Scholar] [CrossRef]
- Olesen, M.H.; Nikneshan, P.; Shrestha, S.; Tadayyon, A.; Deleuran, L.C.; Boelt, B.; Gislum, R. Viability Prediction of Ricinus cummunis L. Seeds Using Multispectral Imaging. Sensors 2015, 15, 4592–4604. [Google Scholar] [CrossRef]
- Timchenko, S.P. Spectral-Optical Criteria for Determining Seed Germination. Ph.D. Thesis, Moscow Timiryazev Agricultural Academy, Moscow, Russia, 1993. [Google Scholar]
- Grossnickle, S.C.; Ivetić, V. Direct Seeding in Reforestation—A Field Performance Review. Reforesta 2017, 4, 94–142. [Google Scholar] [CrossRef]
- Novikov, A.I.; Ersson, B.T. Aerial seeding of forests in Russia: A selected literature analysis. IOP Conf. Ser. Earth Environ. Sci. 2019, 226, 012051. [Google Scholar] [CrossRef]
- Albekov, A.U.; Drapalyuk, M.V.; Morkovina, S.S.; Novikov, A.I.; Vovchenko, N.G.; Sokolov, S.V.; Novikova, T.P. Seed Sorting Device. RU Patent 2,687,509, 14 May 2019. [Google Scholar]
- Drapalyuk, M.V.; Morkovina, S.S.; Novikov, A.I.; Vovchenko, N.G.; Sokolov, S.V.; Novikova, T.P. Seed Sorting Device. RU Patent 2,700,759, 14 September 2019. [Google Scholar]
- Albekov, A.U.; Drapalyuk, M.V.; Morkovina, S.S.; Vovchenko, N.G.; Novikov, A.I.; Sokolov, S.V.; Novikova, T.P. Device for Seeds Sorting. RU Patent 2,682,854, 21 March 2019. [Google Scholar]
- Novikov, A.I. Forest Restoration Method. RU Patent 2,714,705, 20 May 2019. [Google Scholar]
- Löf, M.; Ersson, B.T.; Hjältén, J.; Nordfjell, T.; Oliet, J.; Willoughby, I. Site Preparation Techniques for Forest Restoration. In Restoration of Boreal and Temperate Forests, 2nd ed.; Stanturf, J.A., Ed.; CRC Press: Boca Raton, FL, USA, 2016; pp. 85–102. [Google Scholar]
- Guignabert, A.; Augusto, L.; Delerue, F.; Maugard, F.; Gire, C.; Magnin, C.; Niollet, S.; Gonzalez, M. Combining partial cutting and direct seeding to overcome regeneration failures in dune forests. For. Ecol. Manag. 2020, 476, 118466. [Google Scholar] [CrossRef]
- Sudrajat, D.J.; Rustam, E. Reforestation by direct seeding of Gmelina arborea using seed briquettes: Composition, size and site preparation, and sowing date. IOP Conf. Ser. Earth Environ. Sci. 2020, 533, 012014. [Google Scholar] [CrossRef]
- Ramantswana, M.; Guerra, S.P.S.; Ersson, B.T. Advances in the Mechanization of Regenerating Plantation Forests: A Review. Curr. For. Rep. 2020, 6, 143–158. [Google Scholar] [CrossRef]
- Ersson, B.; Laine, T.; Saksa, T. Mechanized Tree Planting in Sweden and Finland: Current State and Key Factors for Future Growth. Forests 2018, 9, 370. [Google Scholar] [CrossRef]
- Zhao, D.; Pang, Y.; Liu, L.; Li, Z. Individual Tree Classification Using Airborne LiDAR and Hyperspectral Data in a Natural Mixed Forest of Northeast China. Forests 2020, 11, 303. [Google Scholar] [CrossRef]
- Kampen, M.; Vienna, L.S.; Immitzer, M.; Vienna, L.S. UAV-Based Multispectral Data for Tree Species Classification and Tree Vitality Analysis. In Proceedings of the Dreilandertagung der DGPF, der OVG und der SGPF; Publ. der DGPF: Vienna, Austria; 2019; pp. 623–639. [Google Scholar]
- Albekov, A.U.; Drapalyuk, M.V.; Morkovina, S.S.; Vovchenko, N.G.; Novikov, A.I.; Sokolov, S.V.; Novikova, T.P. Seed Encapsulation Method for Aerial Seeding. RU Patent 2,710,721, 20 January 2020. [Google Scholar]
- Sokolov, S.V.; Novikov, A.I. Adaptive estimation of UVs navigation parameters by irregular inertial-satellite measurements. Int. J. Intell. Unmanned Syst. (in press).
- Sokolov, S.V.; Novikov, A.I. Suboptimal stochastic estimation of the initial orientation parameters of a strapdown inertial navigation system on an unmanned vehicle perturbed base. Int. J. Intell. Unmanned Syst. (under review).
- Sokolov, S.V.; Kamenskij, V.V.; Novikov, A.I.; Ivetić, V. How to increase the analog-to-digital converter speed in optoelectronic systems of the seed quality rapid analyzer. Inventions 2019, 4, 61. [Google Scholar] [CrossRef]
- Sokolov, S.; Novikov, A.; Ivetić, V. Determining the initial orientation for navigation and measurement systems of mobile apparatus in reforestation. Inventions 2019, 4, 56. [Google Scholar] [CrossRef]
- Morkovina, S.S.; Vovchenko, N.G.; Novikov, A.I.; Sokolov, S.V.; Dornyak, O.R. Seed Aerial Sowing Device. RU Patent 2,712,516, 21 May 2019. [Google Scholar]
- Jansen, S.; Konrad, H.; Geburek, T. Crossing borders—European forest reproductive material moving in trade. J. Environ. Manag. 2019, 233, 308–320. [Google Scholar] [CrossRef]
- McLain, R.; Lawry, S.; Guariguata, M.R.; Reed, J. Toward a tenure-responsive approach to forest landscape restoration: A proposed tenure diagnostic for assessing restoration opportunities. Land Use Policy 2018, in press. [Google Scholar]
- Dumroese, R.K.; Balloffet, N.; Crockett, J.W.; Stanturf, J.A.; Nave, L.E. A national approach to leverage the benefits of tree planting on public lands. New For. 2019, 50, 1–9. [Google Scholar] [CrossRef]
- Stanturf, J.A.; Kleine, M.; Mansourian, S.; Parrotta, J.; Madsen, P.; Kant, P.; Burns, J.; Bolte, A. Implementing forest landscape restoration under the Bonn Challenge: A systematic approach. Ann. For. Sci. 2019, 76, 50. [Google Scholar] [CrossRef]
- Verdone, M.; Seidl, A. Time, space, place, and the Bonn Challenge global forest restoration target. Restor. Ecol. 2017, 25, 903–911. [Google Scholar] [CrossRef]
- DellaSala, D.A.; Martin, A.; Spivak, R.; Schulke, T.; Bird, B.; Criley, M.; Van Daalen, C.; Kreilick, J.; Brown, R.; Aplet, G. A citizen’s call for ecological forest restoration: Forest restoration principles and criteria. Ecol. Restor. 2003, 21, 14–23. [Google Scholar] [CrossRef]
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Ivetić, V.; Novikov, A.; Daneshvar, A.; Ahmadi-Afzadi, M. Correlation between the Spectrometric Parameters of Coniferous Seeds and the Molecular Indicators of Seedlings: Is It Possible to Apply It in Practice? Environ. Sci. Proc. 2021, 3, 18. https://doi.org/10.3390/IECF2020-08084
Ivetić V, Novikov A, Daneshvar A, Ahmadi-Afzadi M. Correlation between the Spectrometric Parameters of Coniferous Seeds and the Molecular Indicators of Seedlings: Is It Possible to Apply It in Practice? Environmental Sciences Proceedings. 2021; 3(1):18. https://doi.org/10.3390/IECF2020-08084
Chicago/Turabian StyleIvetić, Vladan, Arthur Novikov, Abolfazl Daneshvar, and Masoud Ahmadi-Afzadi. 2021. "Correlation between the Spectrometric Parameters of Coniferous Seeds and the Molecular Indicators of Seedlings: Is It Possible to Apply It in Practice?" Environmental Sciences Proceedings 3, no. 1: 18. https://doi.org/10.3390/IECF2020-08084
APA StyleIvetić, V., Novikov, A., Daneshvar, A., & Ahmadi-Afzadi, M. (2021). Correlation between the Spectrometric Parameters of Coniferous Seeds and the Molecular Indicators of Seedlings: Is It Possible to Apply It in Practice? Environmental Sciences Proceedings, 3(1), 18. https://doi.org/10.3390/IECF2020-08084