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Predicting the seedling emergence time of sugar beet (Beta vulgaris) using beta models

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Abstract

Soil temperature, texture, water content and sowing depth are effective factors on the estimation of emergence time. This research aimed to test the Beta model for its adequacy in predicting the time of emergence for sugar beet. The Beta growth model as a phenological model have been used for evaluating the time of seedling emergences under both controlled environments in laboratory and field conditions. An experiment was conducted both in the laboratory with five soil textures, three sowing depths, five soil water contents and ten constant soil temperatures, under field conditions on five sowing dates (20 February, 28 March, 19 April, 10 May, and 31 May) and three sowing depths. The results demonstrated that the Beta model can predict the time of emergence. Based on the root mean square error (RMSE), the time of emergence estimated by the Beta model was in high agreement with the time of emergence measured in the laboratory. Estimation accuracy was reduced slightly by the Beta model under field conditions. The accuracy of the Beta model was influenced by the sowing date under field conditions. So, on the first and second sowing dates (with low air temperature), the estimation of time of emergence by the model was lower and on the fourth and the fifth sowing date (with warmer air temperature), was more than the duration measured. Estimation accuracy was increased by the Beta model under field conditions using soil temperature. In conclusion, the Beta model can predict the time to emergence of sugar beet seedlings in different levels of soil texture and soil water content under field conditions, and with that, the proper planting date for sugar beet seeds to overcome weeds in different soil water content can be predicted.

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References

  • Abbasi S, Motevali A, Minaei S, Ghaderi A (2010) Selection of a mathematical model for drying kinetics of sour cherry (Prunus cerasus L.) in a microwave-vacuum dryer. Iranian J Nutr Sci Food Technol 6(2):55–64

    Google Scholar 

  • Alex Sandro TF, Alexandre GG, Joao Eduardo B, Renata F (2016) Beet seedling emergence in function of sowing depth and system. Scientia Agraria Paranaensis. 15(2):215–221

    Google Scholar 

  • Alipor S, Taghvaei M, Jalilian A, Kazemeini A, Razi H (2019) Hydro-thermal priming enhances seed germination capacity and seedling growth in sugar beet. Cell Mol Biol (Noisy-le-grand) 65(4):90–96

    Google Scholar 

  • Asgarpour R, Ghorbani R, Khajeh-Hosseini M, Mohammadvand E, Chauhan BS (2015) Germination of spotted spurge (Chamaesyce maculata) seeds in response to different environmental factors. Weed Sci 63(2):502–510

    Google Scholar 

  • Aubertot JN, Dürr C, Richard G, Souty N, Duval Y (2002) Are penetrometer measurements useful in predicting seedling emergence of sugar beet (Beta vulgaris L.) seedlings through a crust? Plant Soil 241:177–186

    CAS  Google Scholar 

  • Bewley JD, Black M (1994) Seeds: physiology of development and germination. Plenum Press, London

    Google Scholar 

  • Blunt SJ, Asher MJC, Gilligan CA (1992) The effect of sowing date on infection of sugar beet by Polymyxa Betae. Plant Pathol 41(2):148–153

    Google Scholar 

  • Bradford KJ (2002) Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Sci 50:248–260

    CAS  Google Scholar 

  • Chaofu LU, Matthew JH (2002) Arabidopsis mutants deficient in Triacylglycerol Acyltransferase display increased sensitivity to abscisic acid, sugars, and osmotic stress during germination and seedling development. Plant Physiol 129:1352–1358

    Google Scholar 

  • Chatelin MH, Aubry C, Poussin JC, Meynard JM, Masse J, Verjux N, Ph GN, Le Bris X, ciBle D (2005) A software package for wheat crop management simulation. Agric Syst 83:77–99

    Google Scholar 

  • Cornea-Cipcigan M, Pamfil D, Sisea CR, Mărgăoan R (2020) Gibberellic acid can Improve seed germination and ornamental quality of selected Cyclamen species grown under short and long days. Agronomy 10(4):516

    CAS  Google Scholar 

  • Daws MI, Burslem DFRP, Crabtree LM, Kirkman P, Mullins CE, Dalling JW (2002) Differences in seed germination responses may promote coexistence of four sympatric Piper species. Funct Ecol 16:258–267

    Google Scholar 

  • Deka RL, Hussain R, Singh KK, Rao VU, Balasubramanian R, Baxla AK (2016) Rice phenology and growth simulation using CERES-Rice model under the agro-climate of upper Brahmaputra valley of Assam. MAUSAM 67(3):591–598

    Google Scholar 

  • Edalat M, Kazemeini SA (2014) Estimation of cardinal temperatures for seedling. Aust J Crop Sci 8(7):1072–1078

    Google Scholar 

  • FAO (2011) Faostat online database, available at link http://faostat.fao.org/. Accessed on December 2011

  • Finch-Savage W, Bassel G (2015) Seed vigour and crop establishment: extending performance beyond adaptation. J Exp Bot 67:567–591

    PubMed  Google Scholar 

  • Gerhards R, Bezhin K, Santel HJ (2017) Sugar beet yield loss predicted by relative weed cover, weed biomass and weed density. Plant Protect Sci 53:118–125

    CAS  Google Scholar 

  • Ghafari E (2011) The effect of temperature, moisture and soil texture on the germination of corn and wheat in laboratory and field condition. M.Sc. thesis. Shiraz University (in Persian)

  • Hyatt J, Wendroth O, Egli DB, Tekrony DM (2007) Soil compaction and soybean seedling emergence. Crop Sci 47:2495–2503

    Google Scholar 

  • Iveta T, Dusan I, Jaroslav A (2007) Soil water movement modelling in Hapllicc luvisols and Albihapllic luvisols under slovak climatic conditions. J Environ Eng Landscape Manag 95(2):69–75

    Google Scholar 

  • Jalilian A, Mazaheri D, Tavakol Afshari R, Abdolahi M, Gohari J (2005) Estimation of base temperature and the investigation of germination and field emergence trend of monogerm sugar beet under various temperatures. J Sugar Beet 20(2):97–112

    Google Scholar 

  • Jame YW, Cutforth HW (2004) Simulating the effects of temperature and seeding depth on germination and emergence of spring wheat. Agric Forest Meteorol 124:207–218

    Google Scholar 

  • Jeremi K, Jacek P (2015) Effect of environmental factors on germination and emergence of invasive Rumex confertus in Central Europe. Sci World J 5:170176

    Google Scholar 

  • Kamkar B, Ahmadi M, Soltani A, Zeinali E (2008) Evaluating non-linear regression models to describe response of wheat emergence rate to temperature. Seed Sci Biotechnol 2:53–57

    Google Scholar 

  • Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves H, Meinke JNG, Hochman Z, McLean G, Verbug K, Snow V, Dimes JP, Silburn M, Wang E, Brown S, Bristow KL, Asseng S, Chapman S, McCown RL, Freebairn DM, Smith JC (2003) An overview of APSIM, a model designed for farming system simulation. Agric Syst 18(34):267–288

    Google Scholar 

  • Kenter C, Hoffman CM, Mariander B (2006) Effects of weather variables on sugar beet (Beta vulgaris L.) yield. Eur J Agron 24:62–69

    Google Scholar 

  • Liu QQ, Huang ZJ, Guo S, Wang DY, Wang CH, Wang ZN, Ma XQ, Liu B (2019) Responses of seed germination and seedling growth of Cunninghamia lanceolata and Schima superba to different light intensities. J Appl Ecol 30(9):2955–2963

    Google Scholar 

  • Mahbod M, Zand-Parsa S, Sepaskhah AR (2015) Modification of maize simulation model for predicting growth and yield of winter wheat under different applied water and nitrogen. Agric Water Manag 150:18–34

    Google Scholar 

  • Majidi M, Heidari G, Emam Y (2017) Qualitative characteristics of sugar beet as affected by different broadleaf herbicides combinations. Iran Agric Res 36(2):1–6

    Google Scholar 

  • May M (2001) Crop protection in sugar beet. Pestic Outlook 12:188–191

    Google Scholar 

  • Mohan A, Schillinger WF, Gill KS (2013) Wheat seedling emergence from deep planting depths and its relationship with coleoptile length. PLoS ONE 8(9):115

    Google Scholar 

  • Muttoni M, Maus A, Cleber B, Alex C, Osmari UL, de Lima T, Vanderley S, Nereu A (2017) Cardinal temperatures for planting-emergence phase in gladiolus. Ciência Rural Santa Maria 47(10):1–7

    Google Scholar 

  • Petkeviciene B (2009) The effects of climate factors on sugar beet early sowing timing. Agron Res 7:436–443

    Google Scholar 

  • Phartyal SS, Thapliyal RC, Nayal JS, Rawat MMS, Joshi G (2003) The Influences of temperatures on seed germination rate in Himalayan elm (Ulmus wallichiana). Seed Sci Technol 31:83–93

    Google Scholar 

  • Rajic M, Čacic N, Sklenar P, Den S (2002) Seed yield of sugar beet as affected by stand density and harvesting and harvesting date. Acta Agron Hung 50(4):417–423

    Google Scholar 

  • Romaneckas K, Romaneckien R, Sarauskis E, Pilipaviius V (2009) The effect of conservation primary and zero tillage on soil bulk density, water content, sugar beet growth and weed infestation. Agron Res 7:73–86

    Google Scholar 

  • Shahgholi G, Gundoshmian TM, Molaie F, Eskandari O (2018) Energy use pattern in production of sugar beet in western Azerbaijan province of Iran. Agric Eng Int 20(1):118–127

    Google Scholar 

  • Soltani A, Robertson MJ, Torabi B, Yousefi-Daz M, Sarparast R (2006) Modelling seedling emergence in chickpea as influenced by temperature and sowing depth. Agric For Meteorol 138:156–167

    Google Scholar 

  • Taghvaei M, Ghaedi M (2010) The impact of cardinal temperature variation on the germination of Haloxylon aphyllum L. seeds. J Ecol Field Biol 33(3):187–193

    Google Scholar 

  • Taghvaei M, Sadeghi H, Khaef N (2015) Cardinal temperatures for germination of a medicinal and desert plant, Calotropis procera Aiton). Planta Daninha 33:671–678

    Google Scholar 

  • Tribouillois H, Dürr C, Demilly D, WagnerM-H JE (2016) Determination of germination response to temperature and water potential for a wide range of cover crop species and related functional groups. PLoS ONE 11(8):e0161185

    PubMed  PubMed Central  Google Scholar 

  • Wang, R (2005). Modelling seed germination and seedling emergence in winterfat (Krascheninnikovia lanata (Pursh). Ph.D. thesis. University of Saskatchewan, Canada, p 190

  • Wang H, Cutforth H, McCaig T, McLeod G, Brandt K, Lemke R, Goddard T, Sprout C (2009) Predicting the time to 50% seedling emergence in wheat using a Beta model. NJAS-Wagen J Life Sci 57:65–71

    Google Scholar 

  • Wang H, Cutforth H, McCaig T, McLeod Brandt K, Lemke R, Goddard T, Sprout C (2010) Modeling time of seedling emergence of spring Wheat. Crop Model Decis Supp 5:1–11

    Google Scholar 

  • Willmott CJ (1982) Some comments on the evaluation of model performance. Bull Am Meteor Soc 63:1309–1313

    Google Scholar 

  • Yan W, Hunt LA (1999) An equation for modelling the temperature-response of plants using only the cardinal temperatures. Ann Bot 84:607–614

    Google Scholar 

  • Zhou G, Wang Q (2018) A new nonlinear method for calculating growing degree days. Sci Rep 8:10149

    PubMed  PubMed Central  Google Scholar 

Download references

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HRR and MT performed the measurements, HRR, SZ-P, MT and AAK-H were involved in the planning and supervised the work. HRR and MT collected data and performed the analysis. Article has been written by MT.

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Correspondence to Mansour Taghvaei.

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Rimaz, H.R., Zand-Parsa, S., Taghvaei, M. et al. Predicting the seedling emergence time of sugar beet (Beta vulgaris) using beta models. Physiol Mol Biol Plants 26, 2329–2338 (2020). https://doi.org/10.1007/s12298-020-00884-1

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