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. 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. Fourty six samples were used for prediction as training, and 21 samples for test. For selection of covariate, principle component analysis were performed. So that predicted yield by square root method in PC2 was selected as covariat in Cokriging. Based on result of cross validation for predicted dataset, RMSE, MAE and MBE for Cokriging was 496, 417 and -91 kg/ha, and for Kriging was 896, 754 and -124 kg/ha. These result showed higher accuracy of yield estimation in Cokriging than Kriging., that also indicated higher accuracy of yield estimation in Cokriging than Kriging.
Seyed Jalali, ُ. A. , Seyed Jalali, ُ. A. and Shorafa, M. (2016). Application of Kriging and Cokriging in Predicting Wheat Yield using Principle Component Analysis. Journal of Crop Production, 9(2), 213-224. doi: 10.22069/ejcp.2016.3124
MLA
Seyed Jalali, ُ. A. , , Seyed Jalali, ُ. A. , and Shorafa, M. . "Application of Kriging and Cokriging in Predicting Wheat Yield using Principle Component Analysis", Journal of Crop Production, 9, 2, 2016, 213-224. doi: 10.22069/ejcp.2016.3124
HARVARD
Seyed Jalali, ُ. A., Seyed Jalali, ُ. A., Shorafa, M. (2016). 'Application of Kriging and Cokriging in Predicting Wheat Yield using Principle Component Analysis', Journal of Crop Production, 9(2), pp. 213-224. doi: 10.22069/ejcp.2016.3124
CHICAGO
ُ. A. Seyed Jalali , ُ. A. Seyed Jalali and M. Shorafa, "Application of Kriging and Cokriging in Predicting Wheat Yield using Principle Component Analysis," Journal of Crop Production, 9 2 (2016): 213-224, doi: 10.22069/ejcp.2016.3124
VANCOUVER
Seyed Jalali, ُ. A., Seyed Jalali, ُ. A., Shorafa, M. Application of Kriging and Cokriging in Predicting Wheat Yield using Principle Component Analysis. Journal of Crop Production, 2016; 9(2): 213-224. doi: 10.22069/ejcp.2016.3124
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