Potato Production as Affected by Crop Parameters and Meteoro Logical Elements

  • André B Pereira
  • Nilson A Villa Nova
  • Antonio R Pereira
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 293)


Meteorological elements directly influence crop potential productivity, regulating its transpiration, photosynthesis, and respiration processes in such a way as to control the growth and development of the plants throughout their physiological mechanisms at a given site. The interaction of the meteorological factors with crop responses is complex and has been the target of attention of many researchers from all over the world. There is currently a great deal of interest in estimating crop productivity as a function of climate by means of different crop weather models in order to help growers choose planting locations and timing to produce high yields with good tuber quality under site-specific atmospheric conditions. In this manuscript an agrometeorological model based on maximum carbon dioxide assimilation rates for C3 plants, fraction of photosynthetically active radiation, air temperature, photoperiod duration, and crop parameters is assessed as to its performance under tropical conditions. Crop parameters include leaf areaand harvest indexes, dry matter content of potato tubers, and crop cycles to estimate potato potential yields. Productivity obtained with the cultivar Itararé, grown with adequate soil water supply conditions at four different sites in the State of São Paulo (Itararé, Piracicaba, TatuÍ, and São Manuel), Brazil, were used to test the model. The results showed thatthe agrometeorological model tested under the climatic conditions of the State of São Paulo in general underestimated irrigated potato yield by less than 10%.This justifies the recommendation to test the performance of the model in study in other climaticregions for different crops and genotypes under optimal irrigationconditions in further scientific investigations. We reached the conclusion that the agrometeorological model taking into account information on leaf area index, photoperiod duration, photosynthetically active radiation and air temperature is feasible to estimate potential tuber yield at a commercial scale. The performance test shows that it can then be used to forecast harvest time, and also as an effective tool to predict the suitability of potential regions to the cultivation of potato crop, cultivar Itararé, at the State of São Paulo, Brazil.


Photosynthetically Active Radiation Leaf Area Index Potential Yield Tuber Yield Harvest Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Assunção, H.F. 1994. Relações entre radiação fotossinteticamente ativa e radiação solar global em Piracicaba, SP. Piracicaba, Dissertation (MSc.), 58p. Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São Paulo.Google Scholar
  2. Bowen, W.T. Water productivity and potato cultivation. 2003. In: Kijne, J.W.; Barker, R.; Molden, D. (eds.) Water Productivity in Agriculture: Limits and Opportunities for Improvement. CAB International 2003. p.229–238. Available on-line at:
  3. Caldiz, D.O.; Struit, P.C. 1999. Survey of potato production and possible yield constraints in Argentina. Potato Research 42:51– 71.CrossRefGoogle Scholar
  4. Camargo, A.P.; Sentelhas, PC. 1995. Avaliação de modelos para estimativa da evapotranspiração potencial mensal em base diária para Campinas e Ribeirão Preto, SP. In: Congresso Brasileiro de Agrometeorologia, Vol. 7, Anais… Campina Grande, p. 415–417.Google Scholar
  5. Cervellini, A.; Salati, E., Godoy, H. 1966. Estimativa da distribuição da energia solar no Estado de São Paulo. Bragantia 25:31–40.CrossRefGoogle Scholar
  6. Coelho, D.T.; Dale, R.F. 1980. An energy-crop growth variable and temperature function for predicting corn growth and development. Planting to silking. Agronomy Journal 72: 503– 510.CrossRefGoogle Scholar
  7. Crommelynk, D.; Fichot, A. 1997. Solar constant temporal and frequency characteristics. Royal Meteorological Institute of Belgium, Bruxelas. Available on-line at:
  8. Doorenbos, J.; Kassam, A.H. 1979. Yield response to water. Rome: FAO, 193p. (Irrigation and Drainage Paper, 33).Google Scholar
  9. Haverkort, A.J. 1990. Ecology of potato cropping systems in relation to latitude and altitude. Agricultural Systems 32: 251–272.CrossRefGoogle Scholar
  10. Heemst, H.D.J. van. 1986. Physiological principles. In: Keulen, H. van; Wolf, J. Modelling of agricultural production: weather, soils and crops. Wageningen: Pudoc, p. 13–26.Google Scholar
  11. Kadaja, J.; Tooming, H. 2004. Potato production model based on principle of maximum plant productivity. Agricultural and Forest Meteorology 127:1–16.CrossRefGoogle Scholar
  12. Ku, S.B.; Edwards, G.E.; Tanner, C.B. 1977. Effects of light, carbon dioxide, and temperature on photosynthesis, oxygen inhibition of photosynthesis, and transpiration in Solanum tuberosum. Plant Physiology 59:868–872.CrossRefGoogle Scholar
  13. Manrique, L.A., D.P. Bartholomew. 1991. Growth and yield performance of potato grown at three elevations in Hawaii: II. Dry matter production and efficiency of partitioning. Crop Science 31:367–372.CrossRefGoogle Scholar
  14. Midmore, D.J.; Prange, R.K. 1992. Growth responses of two Solanum species to contrasting temperatures and irradiance levels: relations to photosynthesis, dark respiration and chlorophyll fluorescence. Annuals of Botany 69:13–20.Google Scholar
  15. Penning de Vries, F.W.T.; Jansen, D.M.; Jen Berge, H.F.M.; Bakema, A. 1989. Simulation of ecophysiological process of growth in several annual crops. Wageningen, PUDOC. 271p.Google Scholar
  16. Pereira, A.B.; Shock, C.C. 2006. Development of irrigation best management practices for potato from a research perspective in the United States. e-publish 1:1–20. Available on-line at:
  17. Pereira, A.B.; Villa Nova, N.A.; Galvani, E. 2003. Estimation of global solar radiation flux density in Brazil from a single measurement at solar noon. Biosystems Engineering 86:27–34. Available on-line at:
  18. Ramos, V.J. 1999. Produção e qualidade da batata (Solanum tuberosum spp. tuberosum), cv. Itararé (IAC-5986) em função do peso do tubérculo semente, densidade de plantas e adubação. Botucatu, Thesis (PhD), 127p. Faculdade de Ciências Agronômicas, Universidade Estadual Paulista.Google Scholar
  19. Robles, W.G.R. 2003. Dióxido de carbono via fertirrigação em batateira (Solanum tuberosum L.) sob condições de campo. Piracicaba, Thesis (PhD), 160 p. Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São Paulo.Google Scholar
  20. Robinson, J.M.; Hubbard, K.G. 1990. Soil water assessment model for several crops in high plains. Agronomy Journal 82:1141–1148.CrossRefGoogle Scholar
  21. Sarquis, J.I., Gonzalez, H.; Bernal-Lugo, I. 1996. Response of two potato clones (Solanum tuberosum L.) to contrasting temperature regimes in the field. American Potato Research 73:285–300.CrossRefGoogle Scholar
  22. Stark, J.C.; Love, S.L. Tuber Quality. 2003. In: Stark, J.C.; Love, S.L. (Co-editors) Potato Production Systems. University of Idaho Extension, Moscow, p. 329–343.Google Scholar
  23. Stuttle, G.W.; Yorio, N.C.; Wheeler, R.M. 1996. Interacting effects of photoperiod and photosynthetic photon flux on net carbon assimilation and starch accumulation in potato leaves. Journal of the American Society of Horticultural Science 121:264–268.Google Scholar
  24. Sun, D.; Dickinson, G.R. 1997. Early growth of six native Australian tree species in windbreaks and their effect on potato growth in tropical northern Australia. Forest Ecology Management 95:21–34.CrossRefGoogle Scholar
  25. Varillas, I.T. 1991. Determinação de unidades térmicas e avaliação dos efeitos de níveis térmicos elevados sobre o crescimento e a produção de cultura de batata (Solanum tuberosum L.). Piracicaba, Dissertation (MSc.), 62 p. Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São Paulo.Google Scholar
  26. Villa Nova, N.A.; Santiago, A.V.; Rezende, F.C. 2001. Energia Solar. Aspectos fisicos de captura pela biomassa. Departamento de Ciências Exatas: Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, 20p.Google Scholar
  27. Villa nova, N.A.; Pilau, F.G.; Dourado Neto, D.; Manfron, P.A. 2005. Estimativa da produtividade de cana-de-açúcar irrigada com base na fixação de CO2, radiação solar e temperatura do ar. Revista Brasileira de Agrometeorologia 13:405–411.Google Scholar
  28. Willmott, C.J.; Ackleson, S.G.; Davies, R.E.; Feddema, J.J.; Klink, K.M.; Legates, D.R.; O'Donnell, J.; Rowe, C.M. 1985. Statistics for the evaluation and comparison of models. Journal of Geophysical Research 90:8995–9005.CrossRefGoogle Scholar
  29. Uehara, G. 1985. The International Benchmark Sites Network for Agrotechnology Transfer (IBSNAT). Wheat Growth and Modelling. Proceedings of a NATO Advanced Research Workshop. 271–274.Google Scholar
  30. XIE Wenxia, YAN Lijiao, WANG Guanghuo. 2006. Simulation and Validation of Rice Potential rowth Process in Zhejiang by Utilizing WOFOST Model. Chinese Rice Sci. 20(3):319–32.Google Scholar
  31. Xuzhang Xue, Larry C Munn. 2003. Soil Survey Results in Xiaotangshan Station.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • André B Pereira
    • 1
  • Nilson A Villa Nova
    • 2
  • Antonio R Pereira
    • 2
  1. 1.Department of Soil Science and Agricultural Engineering, State University of Ponta Grossa4748 Carlos Cavalcanti AvenuePonta GrossaPR, Brazil
  2. 2.ESALQ/USP,and Brazilian Federal Funding Agency Researcher-CNPq.

Personalised recommendations