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About The Authors

Aditya Nugraha Putra
Faculty of Agriculture, Brawijaya University
Indonesia

Lecturer

S Sudarto
Faculty of Agriculture, Brawijaya University
Indonesia

Lecturer

Ananda Ginanthian Alpheratz Ridwan
Faculty of Agriculture, Brawijaya University
Indonesia

Assistant

Aftomi Firman Aditama
Faculty of Agriculture, Brawijaya University
Indonesia

Assistant

Sifa’ul Janahtin
Faculty of Agriculture, Brawijaya University
Indonesia

Assistant

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Comparison of soil physical properties and soil-vegetation indices to predict rice productivity in Malang Regency of East Java

Aditya Nugraha Putra, S Sudarto, Ananda Ginanthian Alpheratz Ridwan, Aftomi Firman Aditama, Sifa’ul Janahtin
  J. Degrade. Min. Land Manage. , pp. 2891-2901  
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Abstract


Rice has become the leading food commodity in Indonesia, with total production reached +54.60 million tons in 2019. However, the production tended to decrease by around 8% from 2018 to 2019, while the rice consumption increased by +1.53 tons. This study aims to develop a rice production estimation model using the soil-vegetation index transformation (MSAVI and SAVI) and soil physical properties, which has the advantage of being faster, cheaper, and more accurate than conventional methods. The soil physical properties were taken based on soil mapping units and analyzed with soil physical parameters. The results showed strong relationships between rice productivity - soil physical characteristics and rice productivity – MSAVI and EVI with r values of 0.97, 0.83, and 0.74, respectively. The soil physical properties have a better coefficient of determination and accuracy than soil-vegetation index. The prediction model of rice production by soil physical properties is formulated inward γ = -8.96+0.01 (Top Soil Sand) + 0.01 (Top Soil Silt) + 6.28 (Bulk Density) - 14.07 (Penetration) - 0.13 (Sub Soil Permeability). There is no difference in the productivity value between model and laboratory analysis result. These results indicate that the rice yield prediction model can be used for estimation purposes.


Keywords


remote sensing;. rice productivity; soil index; soil physical properties; vegetation index

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References


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