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A leaf reflectance-based crop yield modeling in Northwest Ethiopia

Author

Listed:
  • Gizachew Ayalew Tiruneh
  • Derege Tsegaye Meshesha
  • Enyew Adgo
  • Atsushi Tsunekawa
  • Nigussie Haregeweyn
  • Ayele Almaw Fenta
  • José Miguel Reichert

Abstract

Crop yield prediction provides information to policymakers in the agricultural production system. This study used leaf reflectance from a spectroradiometer to model grain yield (GY) and aboveground biomass yield (ABY) of maize (Zea mays L.) at Aba Gerima catchment, Ethiopia. A FieldSpec IV (350–2,500 nm wavelengths) spectroradiometer was used to estimate the spectral reflectance of crop leaves during the grain-filling phase. The spectral vegetation indices, such as enhanced vegetation index (EVI), normalized difference VI (NDVI), green NDVI (GNDVI), soil adjusted VI, red NDVI, and simple ratio were deduced from the spectral reflectance. We used regression analyses to identify and predict GY and ABY at the catchment level. The coefficient of determination (R2), the root mean square error (RMSE), and relative importance (RI) were used for evaluating model performance. The findings revealed that the best-fitting curve was obtained between GY and NDVI (R2 = 0.70; RMSE = 0.065; P

Suggested Citation

  • Gizachew Ayalew Tiruneh & Derege Tsegaye Meshesha & Enyew Adgo & Atsushi Tsunekawa & Nigussie Haregeweyn & Ayele Almaw Fenta & José Miguel Reichert, 2022. "A leaf reflectance-based crop yield modeling in Northwest Ethiopia," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-21, June.
    • Handle: RePEc:plo:pone00:0269791
    DOI: 10.1371/journal.pone.0269791
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    References listed on IDEAS

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    1. Dorosh, Paul A., ed. & Minten, Bart, ed., 2020. "Ethiopia's agrifood system: Past trends, present challenges, and future scenarios: Synopsis," IFPRI synopses 9780896296930, International Food Policy Research Institute (IFPRI).
    2. Héctor García-Martínez & Héctor Flores-Magdaleno & Roberto Ascencio-Hernández & Abdul Khalil-Gardezi & Leonardo Tijerina-Chávez & Oscar R. Mancilla-Villa & Mario A. Vázquez-Peña, 2020. "Corn Grain Yield Estimation from Vegetation Indices, Canopy Cover, Plant Density, and a Neural Network Using Multispectral and RGB Images Acquired with Unmanned Aerial Vehicles," Agriculture, MDPI, vol. 10(7), pages 1-24, July.
    3. Belay Kassie & Senthold Asseng & Reimund Rotter & Huib Hengsdijk & Alex Ruane & Martin Ittersum, 2015. "Exploring climate change impacts and adaptation options for maize production in the Central Rift Valley of Ethiopia using different climate change scenarios and crop models," Climatic Change, Springer, vol. 129(1), pages 145-158, March.
    4. Dorosh, Paul A. & Minten, Bart, 2020. "Ethiopia's agrifood system: Past trends, present challenges, and future scenarios," IFPRI books, International Food Policy Research Institute (IFPRI), number 9780896296916.
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