Journal of Agrometeorology (May 2023)

Assessment of AquaCrop model for simulating Baby corn (Zea mays L.) growth and productivity under different sowing windows and crop geometries

  • SANKAR T.,
  • SP. RAMANATHAN,
  • S. KOKILAVANI,
  • K. CHANDRAKUMAR,
  • M.K. KALARANI

DOI
https://doi.org/10.54386/jam.v25i2.2119
Journal volume & issue
Vol. 25, no. 2

Abstract

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The experiments were conducted at Agro Climate Research Centre, TNAU, Coimbatore. Calibration and validation of AquaCrop model was done using Winter and Kharif, 2022 data. Calibration showed that AquaCrop accurately simulated the canopy cover by low RMSE≤13.1%, good E≤0.76, high d≤0.94 and high R2 values ≥0.98 and biomass development by low RMSE≤13.2%, high E≤0.92, good d≤0.68 and high R2 values ≥0.95. During calibration, model well-simulated the CC under second sowing (D2) and biomass under third sowing (D3). Validation showed almost good fit of CC by low RMSE≤22.0%, good E≤0.68, high d≤0.84 and high R2 values ≥0.97 and biomass development with low RMSE≤7.1%, good E≤0.66, good d≤0.60 and high R2 values ≥0.98. During Validation, model well-simulated the CC and biomass under third sowing (D3). Model showed good fit of yield during first sowing window (D1) with a less deviation for both calibration and validation (15.6% and 5.8% respectively). From the result it could be concluded that sowing windows influence on baby corn production was accurately simulated using AquaCrop during calibration (R2=0.94) and validation (R2=0.98). Hence, AquaCrop proved to be a feasible tool for maximizing the Baby corn yield under different sowing windows.

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