Performance of AquaCrop model for predicting yield and biomass of okra (Abelmoschus esculentus) crop
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Keywords:
AquaCrop model, Biomass, Crop yield, Drip system, Irrigation levelAbstract
The present study was carried out at Technology Park of College of Technology and Engineering, Udaipur, Rajasthan for two years (2019 and 2020) with 6 irrigation treatments and four replications in RBD. Among all the treatments, the treatment T2 (Irrigation at 85% field capacity of soil, based on soil moisture sensor based drip irrigation system) was found best in selected areas for growing okra [Abelmoschus esculentus (L.) Moench] crop under sensor based drip irrigation with maximum crop yield and biomass. In other water scarce regions of Rajasthan, the use of a simulation model can be a better option to predict the crop yield and biomass with respect to different irrigation levels. Therefore, calibration and validation of the AquaCrop model was done with the help of various data which were collected from field experiments during the study period (2019–20). The cut off temperature and base temperature
were set as 32.5–100C, respectively. The model was successfully calibrated and validated with minimum prediction error, mean absolute error (MAE: 0.34–0.56), root mean square error (RMSE: 0.38–0.60) and maximum model efficiency (E ranges 0.8–0.95) and coefficient of correlation (R2 > 0.9). The overall result indicate good performance of the model and can help in decision making as well as for irrigation water management for okra crop under the given conditions of Udaipur district of Rajasthan. It can be used to assess the influence of various environmental factors and management practices on okra crop growth.
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References
Abedinpour M, Sarangi A, Rajput T B S, Singh M, Pathak H and Ahmad T. 2012. Performance evaluation of AquaCrop model for maize crop in a semi-arid environment. Agricultural Water Management 110: 55–66. DOI: https://doi.org/10.1016/j.agwat.2012.04.001
Al-Gobari H M, Mohammad F S, Mohamed S A, Marazky E and Dewidar A Z. 2017. Automated irrigation systems for wheat and tomato crops in arid regions. Water Science and Agriculture 43(2): 354–64. DOI: https://doi.org/10.4314/wsa.v43i2.18
Changade N M, Sharma V and Kumar R. 2023. Performance of okra (Abelmoschus esculentus) to different irrigation levels and mulches under drip irrigation system. The Indian Journal of Agricultural Sciences 93(3): 318–20. DOI: https://doi.org/10.56093/ijas.v93i3.132320
Dhakar R, Sehgal V K, Chakraborty D, Mukherjee J and Kumar S N. 2021. Calibration and validation of InfoCrop model for phenology, LAI, dry matter and yield of wheat. The Indian Journal of Agricultural Sciences 91(5): 771–75. DOI: https://doi.org/10.56093/ijas.v91i5.113102
Hong V and Truong D. 2021. Potential benefits of altering the cassava farming practices in the water shortage regions of Vietnam. Journal of Agrometeorology 23: 396–401 DOI: https://doi.org/10.54386/jam.v23i4.143
Jain N K, Yadav R S and Jat R A. 2021. Drip fertigation influences yield, nutrient uptake and soil properties of peanuts (Arachis hypogaea). The Indian Journal of Agricultural Sciences 91(2): 258–62. DOI: https://doi.org/10.56093/ijas.v91i2.111652
Kumar P, Sarangi A, Singh D K and Parihar S S. 2014. Evaluation of AquaCrop model in predicting wheat yield and water productivity under irrigated saline regimes. Irrigation and Drainage 63(4): 474–87. DOI: https://doi.org/10.1002/ird.1841
Kumar A, Mishra A R, Denis D M, Jeet P and Uday S. 2020. Calibration and validation of FAO: Aqua crop model for wheat in Vindhyan region. Journal of Pharmacy and Photochemistry 9: 299–305.
Kumar J, Patel N, Singh R, Sahoo P K, Sudhishri S, Sehgal V K, Marwaha S and Singh A K. 2021. Development and evaluation of an automation system for irrigation scheduling in broccoli (Brassica oleracea). The Indian Journal of Agricultural Sciences 91(5): 796–98. DOI: https://doi.org/10.56093/ijas.v91i5.113108
Magalhaes I D, Lyra G B, Souza J L, Teodoro I, Carvalho A L and Ferra L D S. 2019. Performance of the AquaCrop model for bean (Phaseolus vulgaris L.) under irrigation condition. Australian Journal of Sciences 13: 1188–196. DOI: https://doi.org/10.21475/ajcs.19.13.07.p1790
Makinde A. 2022. Sensitivity of okra growth indices to various moisture conditions. American Journal of Agriculture and Bio Sciences 17: 51–57. DOI: https://doi.org/10.3844/ajabssp.2022.51.57
Vikas S. 2020. Impact of climate change on crop water requirement of different orchard crops for agro-climatic condition of Udaipur, Rajasthan. Indian Journal of Ecology 47(1): 12–16.
Sharma V and Yadav K K. 2021. Comparative study on crop water requirement using CROPWAT model for different vegetable crops grown under protected and open field cultivation. Indian Journal of Ecology 48(2): 588–91.
Wellen J, Raes D, Traore A, Denis A, Djaby B and Tychon B. 2013. Performance assessment of the FAO AquaCrop model for irrigated cabbage on farmer plots in a semi-arid environment. Agricultural Water Management 127: 40–47. DOI: https://doi.org/10.1016/j.agwat.2013.05.012
Woodward S J R, Van Oijen M, Griffiths W M, Beukes P C and Chapman D F. 2020. Identifying causes of low persistence of perennial ryegrass (Lolium perenne) dairy pasture using the Basic Grassland model (BASGRA). Grass Forage Sciences 75: 45–63. DOI: https://doi.org/10.1111/gfs.12464
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