The feasibility of using vegetation indices and soil texture to predict rice yield

• Autorzy: Yaghouti H. , Pazira E. , Amiri E. , Masihabadi M.H.
• Języki publikacji: EN

Abstrakty

EN

Identifying plant-environment interactions along with remote sensing provides grounds for designing management methods as well as predicting rice yield in different conditions; accordingly, it is very helpful to use vegetation indices for identifying the vegetation and greenness of farms. The regression between the local and high-yield varieties of rice in 2012 and the NDVI, SAVI, LAI, DVI, and RVI indices derived from Landsat 7 in northern Iran indicate the superiority of the NDVI index in the flowering stage of rice. Results show that the coefficient of determination of the fitted model for local and high-yielding varieties is 0.71 and 0.70, respectively, which indicates the good consistency of the results with the regional data. We evaluated the models for the local and high-yielding varieties in crop year 2013 with RMSE of 406 and 272 kg ha-1 and NRMSE of 12% and 6%, respectively. Moreover, the simulation results show that the yield of the models is well fitted with the observed values; besides, there is high correlation (R>0.80) between the real and predicted yield values. As shown by the investigation of the region’s soil texture, the fine-texture paddy fields have better yield.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2019
• Tom: 28
• Numer: 4
• Opis fizyczny: p.2473-2481,fig.,ref.

Twórcy

autor

Yaghouti H.

• Science and Research Branch, Department of Soil Science, Faculty of Agriculture and Natural Resources, Islamic Azad University, Tehran, Iran

autor

Pazira E.

• Science and Research Branch, Department of Soil Science, Faculty of Agriculture and Natural Resources, Islamic Azad University, Tehran, Iran

autor

Amiri E.

• Lahijan Branch, Department of Water Engineering, Islamic Azad University, Lahijan, Iran

autor

Masihabadi M.H.

• Soil and Water Research Institute, Tehran, Iran

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Identyfikatory

DOI

10.15244/pjoes/81088