PREDICT THE GROWTH AND YIELD OF CORN IN HAMEDAN

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

DADRASI AMIR; TORABI BENJAMIN

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Iranian Journal of Field Crop Science Year:2017 | Volume:47 | Issue:4 Page(s): 595-610

Download Full-Text

Persian Verion

View:

659

Download:

Cites:

Information Journal Paper

Title

PREDICT THE GROWTH AND YIELD OF CORN IN HAMEDAN

Author(s)

DADRASI AMIR | TORABI BENJAMIN | Issue Writer Certificate

Keywords

CORNQ1

GRAIN YIELDQ2

MODELINGQ2

PHENOLOGYQ1

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.

Cites

No record.

References

No record.

Cite

APA: Copy

DADRASI, AMIR, & TORABI, BENJAMIN. (2017). PREDICT THE GROWTH AND YIELD OF CORN IN HAMEDAN. IRANIAN JOURNAL OF FIELD CROP SCIENCE (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES), 47(4), 595-610. SID. https://sid.ir/paper/153342/en

Vancouver: Copy

DADRASI AMIR, TORABI BENJAMIN. PREDICT THE GROWTH AND YIELD OF CORN IN HAMEDAN. IRANIAN JOURNAL OF FIELD CROP SCIENCE (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES)[Internet]. 2017;47(4):595-610. Available from: https://sid.ir/paper/153342/en

IEEE: Copy

AMIR DADRASI, and BENJAMIN TORABI, “PREDICT THE GROWTH AND YIELD OF CORN IN HAMEDAN,” IRANIAN JOURNAL OF FIELD CROP SCIENCE (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES), vol. 47, no. 4, pp. 595–610, 2017, [Online]. Available: https://sid.ir/paper/153342/en

Related Journal Papers