Hostname: page-component-7c8c6479df-hgkh8 Total loading time: 0 Render date: 2024-03-19T09:22:03.727Z Has data issue: false hasContentIssue false

Using double logistic equation to describe the growth of winter rapeseed

Published online by Cambridge University Press:  18 January 2018

A. Shabani*
Affiliation:
Irrigation Department, Fasa University, Fasa, Iran
A. R. Sepaskhah
Affiliation:
Irrigation Department, Shiraz University, Shiraz, Iran Drought Research Center, Shiraz University, Shiraz, Iran
A. A. Kamgar-Haghighi
Affiliation:
Irrigation Department, Shiraz University, Shiraz, Iran Drought Research Center, Shiraz University, Shiraz, Iran
T. Honar
Affiliation:
Irrigation Department, Shiraz University, Shiraz, Iran Drought Research Center, Shiraz University, Shiraz, Iran
*
Author for correspondence: A. Shabani, E-mail: shabani8ali@gmail.com

Abstract

There are many parameters in agriculture that change over time in a sigmoid pattern. In the current study, the double logistic function was used to describe and simulate dry matter (DM) variation of winter rapeseed plant and to explain the growth rate under water stress. Irrigation treatments were full irrigation at all growth stages, water stress during the vegetative stage in early spring, water stress at flowering and podding stages, water stress at grain filling stage and rain-fed treatment with supplemental irrigation at time of planting. A high value for the goodness of fit (0.996) and low value for normalized root mean square error (0.085) showed that the double logistic function can describe and simulate DM variation of rapeseed accurately. DM predicted by the double logistic equation based on growing degree day was slightly closer to the measured DM compared with the DM predicted by the double logistic equation based on days after planting. Results showed that growth rate before the winter cold period was lower than that after this period. There were two maximum growth rates for winter rapeseed: the first occurred before cold period and another after.

Type
Crops and Soils Research Paper
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Archontoulis, SV and Miguez, FE (2015) Nonlinear regression models and applications in agricultural research. Agronomy Journal 107, 786798.Google Scholar
Auzanneau, J, Huyghe, C, Escobar-Gutiérrez, AJ, Julier, B, Gastal, F and Barre, P (2011) Association study between the gibberellic acid insensitive gene and leaf length in a Lolium perenne L. synthetic variety. BMC Plant Biology 11, 183196.Google Scholar
BBCH (Biologische Bundesanstallt für Land-und Forstwirtschaft) (1997) Growth Stages of Mono-and Dicotyledonous Plants: BBCH Monograph. Berlin: Blackwell Wissenschafts-Verlag.Google Scholar
Bouchereau, A, Clossais-Besnard, N, Bensaoud, A, Leport, L and Renard, M (1996) Water stress effects on rapeseed quality. European Journal of Agronomy 5, 1930.Google Scholar
Feller, C, Favre, P, Janka, A, Zeeman, SC, Gabriel, J-P and Reinhardt, D (2015) Mathematical modeling of the dynamics of shoot-root interactions and resource partitioning in plant growth. PLoS ONE 10, e0127905. doi: 10.1371/journal.pone.0127905.Google Scholar
Gabriel y Galán, JM, Prada, C, Martínez-Calvo, C and Lahoz-Beltrá, R (2015) A Gompertz regression model for fern spores germination. Anales del Jardín Botánico de Madrid 72, e015, 10.3989/ajbm.2405.Google Scholar
Gajanayake, B, Raja Reddy, K and Shankle, MW (2015) Quantifying growth and developmental responses of sweet potato to mid- and late-season temperature. Agronomy Journal 107, 18541862.Google Scholar
Gan, Y, Angadi, SV, Cutforth, H, Potts, D, Angadi, VV and McDonald, CL (2004) Canola and mustard response to short periods of temperature and water stress at different developmental stages. Canadian Journal of Plant Science 84, 697704.Google Scholar
Génard, M and Huguet, JG (1996) Modeling the response of peach fruit growth to water stress. Tree Physiology 16, 407415.Google Scholar
Greer, DH and Weston, C (2010) Heat stress affects flowering, berry growth, sugar accumulation and photosynthesis of Vitis vinifera cv. Semillon grapevines grown in a controlled environment. Functional Plant Biology 37, 206214.Google Scholar
Gur, A, Osorio, S, Fridman, E, Fernie, AR and Zamir, D (2010) hi2-1, A QTL which improves harvest index, earliness and alters metabolite accumulation of processing tomatoes. Theoretical and Applied Genetics 121, 15871599.Google Scholar
Hau, B, Amorim, L and Bergamin Filho, A (1993) Mathematical functions to describe disease progress curves of double sigmoid pattern. Phytopathology 83, 928932.Google Scholar
Honar, T, Sabet Sarvestani, A, Shams, S, Sepaskhah, AR and Kamgar Haghighi, AA (2013) Effect of drought stress in different growth stages on grain yield and yield components of rapeseed (cv. Talayeh). Iranian Journal of Crop Science 14, 320332 (In Persian with English abstract).Google Scholar
Jamieson, PD, Porter, JR and Wilson, DR (1991) A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field Crops Research 27, 337350.Google Scholar
Lancashire, PD, Bleiholder, H, Van Den Boom, T, Langelüddecke, P, Stauss, R, Weber, E and Witzenberger, A (1991) A uniform decimal code for growth stages of crops and weeds. Annals of Applied Biology 119, 561601.CrossRefGoogle Scholar
Lim, CAA, Awan, TH, Sta. Cruz, PC and Chauhan, BS (2015) Influence of environmental factors, cultural practices, and herbicide application on seed germination and emergence ecology of Ischaemum rugosum Salisb. PLoS ONE 10, e0137256, 10.1371/journal.pone.0137256.Google Scholar
Lipovetsky, S (2010) Double logistic curve in regression modeling. Journal of Applied Statistics 37, 17851793.Google Scholar
Montanaro, G, Dichio, B, Xiloyannis, C and Celano, G (2006) Light influences transpiration and calcium accumulation in fruit of kiwifruit plants (actinidia deliciosa var. deliciosa). Plant Science 170, 520527.Google Scholar
Morrison, MJ, McVetty, PBE and Shaykewich, CF (1989) The determination and verification of a baseline temperature for the growth of westar summer rape. Canadian Journal of Plant Science 69, 455464.Google Scholar
Moustakas, ΝΚ, Akoumianakis, KA and Passam, HC (2011) Patterns of dry biomass accumulation and nutrient uptake by okra (Abelmoschus esculentus (L.) Moench.) under different rates of nitrogen application. Australian Journal of Crop Science 5, 9931000.Google Scholar
Sepaskhah, AR, Fahandezh-Saadi, S and Zand-Parsa, S (2011) Logistic model application for prediction of maize yield under water and nitrogen management. Agricultural Water Management 99, 5157.Google Scholar
Shabani, A, Kamkar Haghighi, AA, Sepaskhah, AR, Emam, Y and Honar, T (2009) Effect of water stress on physiological parameters of oil seed rape (Brassica napus L.). Journal of Water and Soil Science 13, 3142, In Persian.Google Scholar
Shabani, A, Sepaskhah, AR and Kamgar-Haghighi, AA (2013) Estimation of yield and dry matter of rapeseed using logistic model under water salinity and deficit irrigation. Archives of Agronomy and Soil Science 60, 951969.Google Scholar
Soil Survey Staff (1993) Soil Survey Manual. U.S. Department of Agriculture, Handbook No. 18. Washington, DC, USA: USDA.Google Scholar
Soudani, K, le Maire, G, Dufrêne, E, François, C, Delpierre, N, Ulrich, E and Cecchini, S (2008) Evaluation of the onset of green-up in temperate deciduous broadleaf forests derived from moderate resolution imaging spectroradiometer (MODIS) data. Remote Sensing of Environment 112, 26432655.CrossRefGoogle Scholar
Tarara, JM, Blom, PE, Shafii, B, Price, WJ and Olmstead, MA (2009) Modeling seasonal dynamics of canopy and fruit growth in grapevine for application in trellis tension monitoring. HortScience 44, 334340.Google Scholar
Willmott, CJ, Rowe, CM and Mintz, Y (1985) Climatology of the terrestrial seasonal water cycle. International Journal of Climatology 5, 589606.Google Scholar
Xiangxiang, W, Quanjiu, W, Jun, F, Lijun, S and Xinlei, S (2014) Logistic model analysis of winter wheat growth on China's Loess Plateau. Canadian Journal of Plant Science 94, 14711479.Google Scholar