Evaluating the simulate and prediction model of chitti bean (Phaseolus vulgaris L.) grain yield

Document Type : Research Paper

Authors

1 Instructor, Plant bank, Horticultural Sciences, Iranian Biological Resource Center (IBRC), Academic Center for Education, Culture and Research (ACECR), I.R. Iran

2 Assistant Professor, Department of Agronomy, Gorgan university of Agricultural Sciences and Natural Resources, Iran

3 Expert, Plant bank, Plant production, Iranian Biological Resource Center (IBRC), Academic Center for Education, Culture and Research (ACECR), I.R. Iran

Abstract

In this study, for simulation and prediction the yield of chitti bean, it is necessary to assess sub models include of phenology, production and dry matter distribution, leaf area changes and equilibrium of water-soil. The sub model parameters were estimated by using information of date plantings, different plant densities and different years at khomein Research Station and data results of Scientists around the world. Using this model, daily changes of sub models were calculated based on daily meteorological statistics (minimum temperature, maximum temperature, radiation and rain) and finally the yield was predicted. The resulting range of observed yield was 2518 to 3066 kg.h-1 with average of 2832 kg.h-1; whereas the resulting range of predicted yield was 2260 to 2870 kg.h-1 with average of 2643 kg.h-1. R2, CV and RMSD were %83, %1.6 and 205 kg.h-1, respectively. Therefore, it can be concluded that this model have appropriate accuracy for prediction of the growth and yield of common bean in khomein. Also it is possible to predict growth and yield responses of other crops if the data of sub models and regional data results of density and planting date of seed crops are available.

Keywords

References

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Iranian Journal of Field Crop Science
Volume 48, Issue 3 - Serial Number 3
December 2017
Pages 591-600

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History

  • Receive Date: 30 October 2014
  • Revise Date: 10 October 2015
  • Accept Date: 04 November 2015
  • Publish Date: 22 November 2017

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