(TECHNICAL SHORT REPORT), COKRIGING IN PREDICTING WHEAT YIELD USING PRINCIPLE COMPONENT ANALYSIS

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SEYED JALALI S.A.R.; SARMADIAN F.; SHORAFA M.; ESMAIEL Z. MOHAMMAD

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Journal: Crop Production Year:2016 | Volume:9 | Issue:2 Page(s): 213-224

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Title

(TECHNICAL SHORT REPORT), COKRIGING IN PREDICTING WHEAT YIELD USING PRINCIPLE COMPONENT ANALYSIS

Author(s)

SEYED JALALI S.A.R. | SARMADIAN F. | SHORAFA M. | ESMAIEL Z. MOHAMMAD | Issue Writer Certificate

Keywords

GEOSTATISTICQ3

LAND CHARACTERISTICQ2

WHEATQ2

Abstract

Background and objectives: Increasing demand for food in the world and limiting available resource for production make the necessity of using new tools for prediction of crop production. Knowing factors that limit regional production and promote management methods is essential. The measurement of WHEAT crop yield in large areas is time consuming and requires high expenses. One way to save time and cost, using GEOSTATISTICal methods for mapping crop yield. The aim of this research is interpolation of irrigated WHEAT yield with two methods of ordinary kriging and cokriging in order to use the optimum method.Materials and methods: In this research principle component analysis were used for identifying variables that have correlation with each other, and Kriging and Cokriging were used to map crop yield prediction. Forty six samples were used for prediction as training, and 21 samples for test. For selection of covariate, principle component analysis was performed. So that predicted yield by square root method in PC2 was selected as covariate in Cokriging.Results: Predicted irrigated WHEAT yield is from 3002 to 4593 Kg ha-1 with kriging method and 2112 to 5215 Kg ha-1 with cokriging. For measured yield is 2000 to 5300 Kg ha-1. Based on result of cross validation for predicted dataset, RMSE, MAE and MBE for Cokriging was 496, 417 and -91 Kg ha-1, and for Kriging was 896, 754 and -124 Kg ha-1. These result showed higher accuracy of yield estimation in Cokriging than Kriging and indicated higher accuracy of yield estimation in Cokriging than Kriging.Conclusion: Using auxiliary variable for predicting soil and crop yield is significant. In this research observed WHEAT yield was used as main variable and predicted yield with square root method was as auxiliary variable. For validation of kriging and cokriging methods cross validation was used with criteria of RMSE, MAE and MBE that shows amount of error and accuracy of methods. Lower rate of these criteria shows less error and higher accuracy. With lower values of these criteria in cokriging to kriging, the prepared map with cokriging showed higher accuracy. In this research showed that interpolation method with auxiliary variable such as cokriging is better than normal interpolation method like ordinary kriging.

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APA: Copy

SEYED JALALI, S.A.R., SARMADIAN, F., SHORAFA, M., & ESMAIEL, Z. MOHAMMAD. (2016). (TECHNICAL SHORT REPORT), COKRIGING IN PREDICTING WHEAT YIELD USING PRINCIPLE COMPONENT ANALYSIS. ELECTRONIC JOURNAL OF CROP PRODUCTION, 9(2), 213-224. SID. https://sid.ir/paper/135178/en

Vancouver: Copy

SEYED JALALI S.A.R., SARMADIAN F., SHORAFA M., ESMAIEL Z. MOHAMMAD. (TECHNICAL SHORT REPORT), COKRIGING IN PREDICTING WHEAT YIELD USING PRINCIPLE COMPONENT ANALYSIS. ELECTRONIC JOURNAL OF CROP PRODUCTION[Internet]. 2016;9(2):213-224. Available from: https://sid.ir/paper/135178/en

IEEE: Copy

S.A.R. SEYED JALALI, F. SARMADIAN, M. SHORAFA, and Z. MOHAMMAD ESMAIEL, “(TECHNICAL SHORT REPORT), COKRIGING IN PREDICTING WHEAT YIELD USING PRINCIPLE COMPONENT ANALYSIS,” ELECTRONIC JOURNAL OF CROP PRODUCTION, vol. 9, no. 2, pp. 213–224, 2016, [Online]. Available: https://sid.ir/paper/135178/en

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