Predict the growth and yield of corn in Hamedan

Document Type : Research Paper

Authors

1 Ph.D. Student, Department of Agronomy, Agriculture College, Vali-e-Asr University of Rafsanjan, Iran

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

Abstract

In order to modeling of growth stages and yield of corn according to Hamedan province meteorological data (minimum and maximum temperature, radiation and rainfall) By using the sub models of phenology, production and distribution of dry matter  and leaf area changes in maize studies was conducted at the Faculty of Agriculture, University of Vali-e-Asr Rafsanjan in spring 2015. Daily changes of phenology, total dry matter and leaf area was calculated using the model and the yield was predicted. One of the criteria to evaluation of a model is Comparison between coefficients of linear regression of observed and predicted yield (b=0.29±2.11 and a=0.93±0.23) and coefficients of line 1:1 (1, 0). Accuracy of the model related to coefficient of variations of predicted and observed seed yield (CV=4.13) was very high so that in field experiments coefficient of variations limit is 20 to 25. R2 quantity of seed yield was 0.69; showing that the probability for coordination of predicted and observed data is 69 percent. The Root mean square error is the other statistics which is used to evaluation of model accuracy. The Root mean square error of seed yield was 0.36, which is evidence of accuracy of model for yield prediction. domain variation for observed and predicted data were 8.54-9.99 tones and 8.02-9.25 tons per hectare respectively and the means were 9.09 and 8.75 tones per hectare respectively.

Keywords

Main Subjects

References

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Iranian Journal of Field Crop Science
Volume 47, Issue 4 - Serial Number 4
February 2017
Pages 595-610

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History

  • Receive Date: 17 October 2015
  • Revise Date: 14 February 2016
  • Accept Date: 16 February 2016
  • Publish Date: 19 February 2017

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