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Vol. 79 No. 1 (2024)

Articles

The effect of different row spacing and sowing amount on the development and yielding of soybean (Glycine max (L.) Merrill). Part I. Development and morphological features of soybean

DOI: https://doi.org/10.24326/as.2024.5259
Submitted: August 22, 2023
Published: 2024-08-07

Abstract

In 2015–2017, in the proving grounds of the Institute of Agroecology and Plant Production of Wrocław University of Environmental and Life Sciences, field studies were carried out on the different row spacing and sowing amount on the development and yielding of soybean. The test included the assessment of the impact of the varied spacing of rows (15 cm, 30 cm) and the number of sown seeds (50, 75, 90) per unit area. In both of test, the “split-plot” method was used, four repetitions, with two variable factors. The length of the growing seasons of soybean was influenced by the variable thermal and humidity conditions in individual years of the research. In the studies, the factor of differentiated row spacing (15 cm, 30 cm) significantly determined: the number of pods, the number and mass of seeds per plant, the mass of 1000 seeds. The increasing number of sown soybean seeds from 50 to 90 pieces per 1 m2 resulted in a significant increase in the height of the first pod placement, while causing a gradual decrease in the number of 1st order branches, the number of pods per plant, the number and weight of seeds per plant and the weight of 1000 seeds.

References

  1. Abdelghany A.M., Zhang S., Azam M., Shaibu A.S., Feng Y., 2020. Profiling of seed fatty acid composition in 1025 Chinese soybean accessions from diverse ecoregions. Crop J. 8(4), 635–644. https://doi.org/10.1016/j.cj.2019.11.002 DOI: https://doi.org/10.1016/j.cj.2019.11.002
  2. Ball R.A., Purcell L.C., Vories E.D., 2000. Optimizing soybean plant population for a short-season production system in the southern USA. Crop Sci. 40(3), 757–764. https://doi.org/10.2135/cropsci2000.403757x DOI: https://doi.org/10.2135/cropsci2000.403757x
  3. Bartkowiak A., 1978. Analiza wariancji dla układów ortogonalnych. Program AWA. W: Opis mery-toryczny programów statystycznych opracowanych w Instytucie Informatyki Uniwersytetu Wrocławskiego. Wydawnictwo Uniwersytetu Wrocławskiego, 43–60.
  4. Bongaarts J., 2009. Human population growth and the demographic transition. Philos. Trans. – R. Soc., Biol. Sci. 364(1532), 2985–2990. https://doi.org/10.1098/rstb.2009.0137 DOI: https://doi.org/10.1098/rstb.2009.0137
  5. Beiküfner M., Hüsing B., Trautz D., Kühling I., 2019. Comparative harvest efficiency of soybeans between cropping systems affected by first pod height and plant length. Org. farming 5(1), 3–13. https://doi.org/10.12924/of2019.05010003 DOI: https://doi.org/10.12924/of2019.05010003
  6. Bellaloui N., Bruns H.A., Abbas H.K., Mengistu A., Fisher D.K., Reddy K.N., 2015. Effects of row-type, row-spacing, seeding rate, soil-type, and cultivar differences on soybean seed nutrition under US Mississippi Delta conditions. PLoS ONE 10(6), e0129913. https://doi.org/10.1371/journal.pone.0129913 DOI: https://doi.org/10.1371/journal.pone.0129913
  7. Clemente T.E., Cahoon E.B., 2009. Soybean oil: genetic approaches for modification of functionality and total content. Plant Physiol. 151(3), 1030–1040. https://doi.org/10.1104/pp.109.146282 DOI: https://doi.org/10.1104/pp.109.146282
  8. De Bruin J.L., Pedersen P., 2008. Effect of row spacing and seeding rate on soybean yield. Agron. J. 100(3), 704–710. https://doi.org/10.2134/agronj2007.0106 DOI: https://doi.org/10.2134/agronj2007.0106
  9. Elandt R., 1964. Statystyka matematyczna w zastosowaniu do doświadczalnictwa rolniczego. Warszawa, PWN.
  10. Gan Y.I., Van-Keulen S.H., Kuiper P.J.C., 2002. Physiological response of soybean genotypes to plant density. Field Crops Res. 74, 231–241. DOI: https://doi.org/10.1016/S0378-4290(01)00212-X
  11. Hou G., Ablett G.R., Pauls K.P., Rajcan I., 2006. Environmental effects on fatty acid levels in soy-bean seed oil. J. Am. Oil Chem. Soc. 83(9), 759–763. https://doi.org/10.1007/s11746-006-5011-4 DOI: https://doi.org/10.1007/s11746-006-5011-4
  12. Kang B.K., Kim H.T., Choi M.S., Koo S.C., Seo J.H., Kim H.S., Shin S.O., Yun H.T., Oh I.S., Kulkarni K.P., 2017. Genetic and environmental variation of first pod height in soybean [Gly-cine max (L.) Merr.]. Plant Breed. Biotechnol. 5(1), 36–44. https://doi.org/10.9787/PBB.2017.5.1.036 DOI: https://doi.org/10.9787/PBB.2017.5.1.36
  13. Koźmiński C., Michalska B., 2001. Atlas klimatycznego ryzyka uprawy roślin w Polsce. Akademia Rolnicza, Szczecin.
  14. Lee S.J., Yan W., Kuk A., Chung M., 2003. Effects of year, site, genotype and their interactions on various soybean isoflavones. Field Crops Res. 81(2–3), 181–192. https://doi.org/10.1016/S0378-4290(02)00220-4 DOI: https://doi.org/10.1016/S0378-4290(02)00220-4
  15. Lorenc-Kozik A., Pisulewska E., 2003. Wpływ zróżnicowanego nawożenia azotem i mikroelemen-tami na plonowanie wybranych odmian soi. Rośl. Oleiste 24, 131–142.
  16. Malek M.A., Shafiquzzaman M., Rahman M.S., Ismail M.R., Mondal M.M.A., 2012. Standardiza-tion of soybean row spacing based on morpho-physiological characters. Legume Res. 35, 138‒143.
  17. Medic J., Atkinson C., Hurburgh C.R., 2014. Current knowledge in soybean composition. J. Am. Oil Chem. Soc. 91(3), 363–384. https://doi.org/10.1007/s11746-013-2407-9 DOI: https://doi.org/10.1007/s11746-013-2407-9
  18. Miętus M., Owczarek M., Filipiak J., 2002. Warunki termiczne na obszarze Wybrzeża i Pomorza
  19. w świetle wybranych klasyfikacji, Materiały Badawcze IMGW, Seria Meteorologia, 36, ss. 56.
  20. Molga M., 1980. Meteorologia rolnicza. PWRiL, Warszawa.
  21. Molga M., 1986. Podstawy klimatologii rolniczej. PWRiL, Warszawa.
  22. Natarajan S., 2014. Analysis of soybean seed proteins using proteomics. J. Data Min. Genom. Pro-teom. 05(01), 10–12. https://doi.org/10.4172/2153-0602.1000e113 DOI: https://doi.org/10.4172/2153-0602.1000e113
  23. Oz M., Karasu A., Goksoy A.T., Turan Z.M., 2009. Interrelationships of agronomical characteristics in soybean (Glycine max) grown in different environments. Int. J. Agric. Biol. 11(1), 85–88.
  24. PN-R-04031:1997. Analiza chemiczno-rolnicza gleby – Pobieranie próbek.
  25. Popovic V., Malesevic M., Miladinovic J., Maric V., Zivanovic L., 2012. Effect of agroecological factors on variations in yield, protein and oil contents in soybean grain. Rom. Agric. Res. (30), 241–247.
  26. Pyzik J., 1982. Wpływ warunków przyrodniczych i czynników agrotechnicznych na plon i skład chemiczny nasion oraz niektóre cechy morfologiczne nowych form soi. Zeszyty Naukowe Akademii Rolniczej w Krakowie. Rozprawa habilitacyjna 87, 1–33, Kraków.
  27. Radomski C., 1987. Agrometeorologia. PWN, Warszawa.
  28. Ribeiro A., Marchetti B, Bruzi A.T., Zuffo A.M., Zambiazzi E.V., Soares I.O., Dias Vilela N.J., de Andrade J., Pereira R., Moreira S.G., 2017. Productive performance of soybean cultivars grown in different plant densities. Crop Prod., Cienc. Rural 47(7), https://doi.org/10.1590/0103-8478cr20160928 DOI: https://doi.org/10.1590/0103-8478cr20160928
  29. Sichilima I., Mataa M., Mweetwa A.M., 2018. Morpho-physiological and yield responses associated with plant density variation in soybean (Glycine max L. (Merrill)). Int. J. Environ. Agric. Bio-technol. 3(1), 274–285. https://doi.org/10.22161/ijeab/3.1.35 DOI: https://doi.org/10.22161/ijeab/3.1.35
  30. Sobko O., Hartung J., Zikeli S., Claupein W., Gruber S., 2019. Effect of sowing density on grain yield, protein and oil content and plant morphology of soybean (Glycine max L. Merrill). Plant Soil Environ. 65(12), 594–601. https://doi.org/10.17221/346/2019-PSE DOI: https://doi.org/10.17221/346/2019-PSE
  31. Sultan S.M., Dikshit N., Vaidya U.J., 2015. Oil content and fatty acid composition of soybean (Gly-cine max L.) genotypes evaluated under rainfed conditions of Kashmir Himalayas in India. J. Appl. Nat. Sci. 7(2), 910–915. https://doi.org/10.31018/jans.v7i2.706 DOI: https://doi.org/10.31018/jans.v7i2.706
  32. Suzuki E., 2021. World’s population will continue to grow and will reach nearly 10 billion by 2050, https://blogs.worldbank.org/opendata/worlds-population-will-continue-grow-and-will-reach-nearly-10-billion-2050 [dostęp: 3.08.2023].
  33. Taheripour F., Hertel T.W., Ramankutty N., 2019. Market-mediated responses confound policies to limit deforestation from oil palm expansion in Malaysia and Indonesia. Proc. Natl Acad. Sci. U.S.A. 116(38), 19193–19199. https://doi.org/10.1073/PNAS.1903476116 DOI: https://doi.org/10.1073/pnas.1903476116
  34. Toleikiene M., Slepetys J., Sarunaite L., Lazauskas S., Deveikyte I., Kadziuliene Z., 2021. Soybean development and productivity in response to organic management above the northern boundary of soybean distribution in Europe. Agronomy 11(2), 214. https://doi.org/10.3390/agronomy11020214 DOI: https://doi.org/10.3390/agronomy11020214
  35. Tomczyk A., Szyga-Pluta K., 2016. Okres wegetacyjny w Polsce w latach 1971–2010. Prz. Geogr. 88(1), 75–86. https://doi.org/10.7163/PrzG.2016.1.4 DOI: https://doi.org/10.7163/PrzG.2016.1.4
  36. Walker E.R., Mengistu A., Bellaloui N., Koger C.H., Roberts R.K., Larson J.A., 2010. Plant popula-tion and row-spacing effects on maturity group III soybean. Agron. J. 102, 821–826. DOI: https://doi.org/10.2134/agronj2009.0219
  37. Witzenberger A, Van Den Boom T., Hack H., 1989. Erläuterungen zum BBCH-Dezimal-Code für die Entwicklungsstadien des Getreides-mit Abbildungen. Gesunde Pflanzen 41(11), 384–388.
  38. Worku M., Astatkie T., 2015. Effects of row spacing on productivity and nodulation of two soybean varieties under hot submoist tropical conditions in south-western Ethiopia. J. Agric. Rural De-velop. Tropics Subtropics 116(2), 99–106.
  39. Young V., Pellett P., 1994. Plant proteins in relation to human protein and amino acid nutrition, Am. J. Clinical Nutr. 59(5), 1203–1212. DOI: https://doi.org/10.1093/ajcn/59.5.1203S

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