Functional growth analysis of diploid potato cultivars (Solanum phureja Juz. et Buk.)


  • Tatiana María Saldaña-Villota Universidad Nacional de Colombia, sede Medellín, Facultad de Ciencias Agrarias, Medellin
  • José Miguel Cotes-Torres Universidad Nacional de Colombia, sede Medellín, Facultad de Ciencias Agrarias, Medellin



Net assimilation rate, Relative growth rate, Dry matter accumulation, Leaf area


Plant growth analysis has been widely used to study factors that influence plant growth. This analysis uses a set of quantitative methods that describe and analyze the growth of plants and their organs. It uses data from direct measurements (weight, area, volume) and quantifies and analyzes growth using indexes based on models defined by mathematical functions. This study conducted a functional growth analysis of diploid potato cultivars in Colombia. The functional growth analysis of diploid potato cultivars was carried out over three consecutive growing seasons in Medellín, Colombia. A randomized block design was used with two levels of fertilization and five repetitions. The first factor corresponded to the three potato cultivars, and the second factor was two fertilization levels: 260 and 778 kg of fertilizer per hectare. Samples were taken weekly, and each sample was an entire plant per experiment unit. The dry weight of each organ and the leaf area were measured. These measurements were used to calculate the relative growth rate, leaf area ratio, net assimilation rate, and specific leaf area. The development time was evaluated in accumulated degree-days with threshold temperatures of 2 and 29°C. The three cultivars recorded their highest net assimilation rate at 1,252 accumulated degree days (ADD), with values of 0.0002565, 0.0002021, and 0.0001778 g cm-2 ADD-1 in the ‘Latina’, ‘Guaneña’, and ‘Colombia’ cultivars, respectively. The Latina cultivar stood out in several physiological characteristics, including the fastest developing cultivar. ‘Latina’ also had the highest total dry mass accumulated in the cycle (271.05 g) and accumulated dry matter in tubers (237 g).


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Aguilar, M.G., J. Carrillo, A. Rivera, and V. González. 2006. Growth analysis and sink-source relationships in two potato (Solanum tuberosum L.) varieties. Rev. Fitot. Mex. 29(2), 145-156.

Borrego, F., M. Murillo, J. Fernández, A. López, V. Parga, and A. Carvajal. 2000. Nota Técnica. Anáisis de crecimiento en siete variedades de papa (Solanum tuberosum L.). Agron. Mesoam. 11(1), 145-149. Doi: 10.15517/am.v11i1.17364

Cabezas, M. and G. Corchuelo. 2005. Estimación de la interceptación de la radiación solar en papa criolla (Solanum phureja Juz. et Buk.) en tres localidades colombianas. Agron. Colomb. 23(1), 62-73.

Condori, B., P. Mamani, R. Botello, F. Patiño, A. Devaux, and J.F. Ledent. 2008. Agrophysiological characterisation and parametrisation of Andean tubers: Potato (Solanum sp.), oca (Oxalis tuberosa), isaño (Tropaeolum tuberosum) and papalisa (Ullucus tuberosus). Eur. J. Agron. 28(4), 526-540. Doi: 10.1016/j.eja.2007.12.002

De Oliveira, A., J. Domingos, and S. Zambelo. 2000. Análise de crescimento na cultura da Batata submetida a diferentes lâminas de irrigação. Pesq. Agropec. Bras. 35(1986), 901-907. Doi: 10.1590/S0100-204X2000000500006

Fourcaud, T., X. Zhang, A. Stokes, H. Lambers, and C. Körner. 2008. Plant growth modelling and applications: the increasing importance of plant architecture in growth models. Ann. Bot. 101(8), 1053-1063. Doi: 10.1093/aob/mcn050

Gaitán, Á., M. Gonzales, C. Ñústez, T.M. Saldaña-Villota, and J.M. Cotes-Torres. 2013. Growth and development functional analysis in four potato varieties (Solanum tuberosum subsp. andigena. Rev. Fac. Cienc. Básicas 9(2), 172-185. Doi: 10.18359/rfcb.344

Gardner, F., R. Pearce, and R. Mitchell. 1985. Physiology of crop plants. Iowa State University Press, Ames, IA.

Gelman, A. and J. Hill. 2007. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, New York, NY. Doi: 10.1017/CBO9780511790942

Grime, J. and R. Hunt. 1975. Relative growth-rate: Its range and adaptive significance in a local flora. J. Ecol. 63(2), 393-422. Doi: 10.2307/2258728

Gutierrez, A.P.A.P. 1996. Applied population ecology: a supply-demand approach. John Wiley & Sons, New York, NY.

Hadfield, J.D. 2010. MCMC Methods for multi-response generalized linear mixed models: The MCMCglmm R Package. J. Stat. Softw. 33(2), 1-22. Doi: 10.18637/jss.v033.i02

Hendrik, P. 1989. Plant growth analysis: towards a synthesis of the classical and the functional approach. Physiol. Plant. 75, 237-244.

Holdridge, L. 1967. Life zone ecology. Tropical Life Science, San Jose.

Huamán, Z. 1986. Systematic, botany and morphology of the potato. International Potato Center (CIP), Lima.

Hunt, R. 1982. Plant growth curves: The functional approach to plant growth analysis: Cambridge University Press, New York, NY.

Hunt, R. 2002. A modern tool for classical plant growth analysis. Ann. Bot. 90(4), 485-488. Doi: 10.1093/aob/mcf214

Hunt, R. 2003. Growth analysis, individual plants. Elsevier, Sheffield, UK.

Kutschera, U. 2019. Cell expansion in plant development. Braz. J. Plant Physiol. 12(1), 65-95.

Lambers, H., F.S. Chapin, and T. Pons. 1998. Plant physiological ecology. 2nd ed. Springer. Doi: 10.1007/978-1-4757-2855-2

Larcher, W. 2003. Physiological plant ecology. Ecophysiology and stress physiology of the functional groups. Springer-Verlag Berlin, Heidelberg, New York.

Lynch, D.R. and R.G. Rowberry. 1977. Population density studies with Russet Burbank II. The effect of fertilization and plant density on growth, development and yield. Am. Potato J. 54, 57-71. Doi: 10.1007/BF02851874

Machida-Hirano, R. 2015. Diversity of potato genetic resources. Breed. Sci. 65(1), 26-40. Doi: 10.1270/jsbbs.65.26

Manetsch, T.J. 1976. Time-Varying distributed delays and their use in aggregative models of large systems. IEEE Trans. Syst. Man Cybern. Syst. 6(8), 547-553. Doi: 10.1109/TSMC.1976.4309549

Marenco, R.A. and N. Fernandes Lopes. 2009. Fisiologia vegetal. UFV, Viçosa, Brazil.

Montoya, F., D. Camargo, J.F. Ortega, J.I. Córcoles, and A. Domínguez. 2016. Evaluation of Aquacrop model for a potato crop under different irrigation conditions. Agric. Water Manage. 164, 267-280. Doi: 10.1016/j.agwat.2015.10.019

Ñústez, C., M. Santos, and M. Segura. 2009. Dry matter allocation and partitioning of four potato varieties (Solanum tuberosum L.) in Zipaquirá, Cundinamarca (Colombia). Rev. Fac. Nac. Agron. Medellin 62(1), 4823-4834.

Oliveira, J.S., H.E. Brown, A. Gash, and D.J. Moot. 2016. An explanation of yield differences in three potato cultivars. Agron. J. 108(4), 1434-1446. Doi: 10.2134/agronj2015.0486

Ovchinnikova, A., E. Krylova, T. Gavrilenko, T. Smekalova, M. Zhuk, S. Knapp, and D.M. Spooner. 2011. Taxonomy of cultivated potatoes (Solanum section Petota: Solanaceae). Bot. J. Linn. Soc. 165(2), 107-155. Doi: 10.1111/j.1095-8339.2010.01107.x

Plummer, M., N. Best, K. Cowles, and K. Vines. 2006. CODA: Convergence diagnosis and output analysis for MCMC. R News 6(1), 7-11.

R Core Team, 2020. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Cary, NC.

Rodríguez, D., J.M. Cotes, and J.R. Cure. 2012. Comparison of eight degree-days estimation methods in four agroecological regions in Colombia. Bragantia 71(2), 299-307. Doi: 10.1590/S0006-87052012005000011

Rodríguez, D., J.R. Cure, J.M. Cotes, A.P. Gutierrez, and F. Cantor. 2011. A coffee agroecosystem model: I. Growth and development of the coffee plant. Ecol. Model. 222(19), 3626-3639. Doi: 10.1016/j.ecolmodel.2011.08.003

Santos, M. 2010. Evaluación del crecimiento, desarrollo y componentes de rendimiento de cuatro cultivares de papa criolla en dos localidades del departamento de Cundinamarca. Universidad Nacional de Colombia, Bogotá.

Searle, S., G. Casella, and C.E. McCulloch. 1992. Variance components. Jhon Wiley & Sons, New York, USA. Doi: 10.1002/9780470316856

Segura, M., M. Santos, and C. Ñústez. 2006. Desarrollo fenológico de cuatro variedades de papa (Solanum tuberosum L.) en el Municipio de Zipaquirá (Cundinamarca). Fitot. Colomb. 6(2), 33-43.

Sorensen, D. and D. Gianola. 2002. Likelihood, bayesian, and MCMC methods in quantitative genetics. Springer, Statistics for Biology and Health. Doi: 10.1007/b98952

Struik, P.C. 2007. Responses of the potato plant to temperature. pp. 367-393. In: Vreugdenhil, D. (ed.), Potato biology and biotechnology. Elsevier, Wageningen, The Netherlands. Doi: 10.1016/B978-0-444-51018-1.X5040-4

Taiz, L., E. Zeiger, I. Moller, and A. Murphy. 2014. Plant physiology and development. 6th ed. Sinauer Associates, Los Ángeles, CA.

Tekalign, T. and P.S. Hammes. 2005. Growth and productivity of potato as influenced by cultivar and reproductive growth. I. Stomatal cnductance, rate of transpiration, net photosynthesis, and dry matter production and allocation. Sci. Hortic. 105(1), 13-27. Doi: 10.1016/j.scienta.2005.01.029

Vansickle, J. 1977. Attrition in distributed delay models. IEEE Trans. Syst. Man Cybern. Syst. 7(9), 635-638. Doi: 10.1109/TSMC.1977.4309800

Wood, P. 1967. Algebraic model of the lactation curve in cattle. Nature 216, 164-165. Doi: 10.1038/216164a0
View of the experimental field at 60 days after planting. Photo: T.M. Saldaña-Villota




How to Cite

Saldaña-Villota, T. M., & Cotes-Torres, J. M. (2020). Functional growth analysis of diploid potato cultivars (Solanum phureja Juz. et Buk.). Revista Colombiana De Ciencias Hortícolas, 14(3), 402–415.



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