Cover Image

Effect of deficit irrigation on the growth and yield of peanuts (Arachis hypogaea (L.) Merr.) compared to AquaCrop model simulation

https://doi.org/10.22146/ipas.77304

Febery Hery Suandana(1), Cahyoadi Bowo(2*), Sigit Soeparjono(3)

(1) University of Jember
(2) University of Jember
(3) University of Jember
(*) Corresponding Author

Abstract


The availability of irrigation water during the growing season reflects on the potential yield at the end of the peanuts’ growing season. Monitoring water availability is essential to optimize production. This study aimed to identify the effect of irrigation water on peanuts (Arachis hypogaea (L.) Merr.) under various irrigation conditions between actual and simulated AquaCrop. The research was conducted in the experimental field utilizing four irrigation treatments which were 60%, 80%, 100% of  field capacity (FC), and standard irrigation. The correlation results between the actual and simulated ones showed that the R2 value was 0.974–0.990 for the canopy cover parameter, 0.026–0.534 for ETc, and 0.542-0.554 for production. Comparison between actual and simulated AquaCrop showed Root Mean Square Error (RMSE) values of 5.08–­­9.74 for canopy cover parameters, 1.11–3.12 for ETc, and 0.82–1.09 for production. Welch test statistical analysis indicated values of 2.31–5.52 for plant biomass and 0.04–3.98 for dry pod yields. The AquaCrop simulation accurately predicted canopy cover at 80% irrigation treatment compared to 60%, 100%, and standard irrigation treatments. Parameter of ETc in AquaCrop simulations showed inaccurate predictions for biomass production and pod dry weight when compared with actual results on all irrigation treatments.

Keywords


AquaCrop;canopy cover;evapotranspiration;lysimeter

Full Text:

PDF


References

Adeboye, O. B., Schultz, B., Adeboye, A. P., Adekalu, K. O., and Osunbitan, J. A. (2020). Application of the AquaCrop model in decision support for optimization of nitrogen fertilizer and water productivity of soybeans. Information Processing in Agriculture, pp. 1–3.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. (2006). Crop evapotranspiration-guidelines for computing crop water requirements-FAO Irrigation and Drainage Paper 56. Roma : FAO (Food and Agriculture Organization), pp. 161–170.
Aziz, M., Rizvi, S. A., Sultan, M., Bazmi, M. S. A., Shamsiri, R. R., Ibrahim, S. M., and Imran, M. A. (2022). Simulating cotton growth and productivity using AquaCrop model under deficit irrigation in a semi-arid climate. Agriculture (Switzerland), 12(2), pp. 1–18.
Brown, B. C. and Knowles, D. A. (2021). Welch-weighted egger regression reduces false positives due to correlated pleiotropy in mendelian randomization. The American Journal of Human Genetics, 12(2), pp. 2319–2335.
Foster, T., Brozovic, N., Butler, A. P., Neale, C. M. U., Raes, D., Steduto, P., Fereres, E., and Hsiao, T. C. (2017). AquaCrop-OS : an open source version of FAO's crop water productivity model. Agricultural Water Management, 11(11), pp. 18–22.
Chibarabada, T. P., Modi, A. T., and Mabhaudhi, T. (2020). Calibration and evaluation of AquaCrop for groundnut (Arachis hypogaea) under water deficit conditions. Agricultural and Forest Meteorology, 11(17), pp. 1–2.
Er-Raki, S., Bouras, E., Rodriguez, J. C., Watts, C. J., Lizarraga-Celaya, C., and Chehbouni, A. (2020). Parameterization of the AquaCrop model for simulating table grapes growth and water productivity in an arid region of Mexico. Agricultural Water Management, 20(5), pp. 1–2.
Gebremedhin, M. A., Lubczynski, M. W., Maathuis, B. H. P., and Teka, D. (2022). Deriving potential evapotranspiration from satellite-based reference evapotranspiration, upper ekeze Basin, Northern Ethiopia. Journal of Hydrology: Regional Studies, 41(4), pp. 2–3.
Giménez, L., Paredes, P., and Pereira, L. S. (2017). Water use and yield of soybean under various irrigation regimes and severe water stress. Application of AquaCrop and SIMDualKc Models. Water, 9(393), pp. 1–18.
Han, C., Zhang, B., Chen, H., Liu, Y., and Wei, Z. (2020). Novel approach of upscaling the FAO Aquacrop model into regional scale by using distributed crop parameters derived from remote sensing data. Agricultural Water Management, 240(5), pp. 1–2.
Harahap, F. S., Purba, J. and Rauf, A. (2021). Hubungan curah hujan dengan pola ketersediaan air tanah terhadap produksi kelapa sawit (Elaeis guineensis Jacq) di dataran tinggi. Agrikultura, 32(1), pp. 37–38.
Iskandar, I., Suryaningtyas, D. T., Baskoro, D. P. T., Budi, S. W., Gozali, I., Suryanto, A., Kirmi, H., and Dultz, S. (2022). Revegetation as a driver of chemical and physical soil property changes in a post-mining landscape of East Kalimantan: a chronosequence study. Catena, 215(10), pp. 1–2.
Liu, Y., Jiang, Q., Wang, Q., Jin, Y., Yue, Q., Yu, J., Zheng, Y., Jiang, W., and Yao, X. (2022). The divergence between potential and actual evapotranspiration: an insight from climate, water, and vegetation change. Science of the Total Environment, 9(14), pp. 1–2.
Karagöz, D. (2016). Modified welch test statistic for ANOVA under weibull distribution. Journal of Mathematics and Statistics, 45(2), pp. 561–573.
Kelly, T. D. and Foster, T. (2021). AquaCrop-OSPy : bridging the gap between research and practice in crop-water modeling. Agricultural Water Management, 254(5), pp. 1–2.
Khov, S., Vote, C., Hornbuckle, J., Inthavong, I., Oeurng, C., Sengxua, P., Sihathep, V., Song, L., and Eberbach, P. (2017). Calibration and validation of aquacrop for irrigated peanut (Arachis hypogaea) in lowland rice systems of Southern Laos. Modelling and Simulation, 12(8), pp. 223-229.
Kuwagata, T., Murai, H. M., Matsunami, M., Terui, S., Nagano, A. J., Maruyama, A., and Ishida, S. (2022). Hydrometeorology for plant omics: potential evaporation as a key index for transcriptome in rice. Environmental and Experimental Botany, 196(11), pp. 1-2.
Serrano, S. M. V., Castro, F. D., Reig, F., Begueria, S., Burguera, M. T., Latore, B., Angulo, D. P., Noguera, I., Rabanaque, I., Luna, Y., Morata, A. and KenawyA. E. (2022). A Near Real-Time Drought Monitoring System for Spain using Automatic Weather Station Network. Atmospheric Research, 271(11), pp. 1–2.
Liu, Z. (2022). Estimating land evapotranspiration from potential evapotranspiration constrained by soil water at daily scale. Science of the Total Environment, 834(4), pp. 1–2.
Lyons, D. S., Dobrowski, S. Z., Holden, Z. A., Maneta, M. P., and Sala, A. (2021). Remote sensing of environment soil moisture variation drives canopy water content dynamics across the Western U. S. Remote Sensing of Environment, 253(11), pp. 1–2.
Man, A., Chaichana, C., and Wicharuck, S. (2019). Predicting sunlight availability for vertical shelves using simulation. Energy Technology for Environment Research Center, 20, pp. 4–5.
Mujiyo, Nugroho, D., Sutarno, Herawati, A., Herdiansyah, G., and Rahayu. (2022). Evaluasi kemampuan lahan sebagai dasar rekomendasi penggunaan lahan di Kecamatan Ngadirojo Kabupaten Wonogiri. Agrikultura, 33(1), pp. 56-57.
Nikolaou, G., Neocleous, D., Kitta, E., and Katsoulas, N. (2022). Assessment of the priestley-taylor coefficient and a modified potential evapotranspiration model. Pre-Profof, 5(27), pp. 10–11.
Nomura, K., Saito, M., Kitayama, M., Goto, Y., Nagao, K., Yamasaki, H., Iwao, T., Yamazaki, T., Tada, I., and Kitano, M. (2022). Leaf area index estimation of a row-planted eggplant canopy using wide-angle time-lapse photography divided according to view-zenith-angle contours. Agricultural and Forest Meteorology, 319(4), pp. 1–2.
Nsabagwa, M., Byamukama, M., Kondela, E., and Otim, J. S. (2019). Towards a robust and affordable automatic weather station. Development Engineering, 4(5), pp. 1–2.
Paredes, P., Wei, Z., Liu, Y., Xu, D., Xin, Y., Zhang, B., and Pereira, L. S. (2015). Performance assessment of the FAO Aquacrop Model for soil water, soil evaporation, biomass and yield of soybeans in North China Plain. Agricultural Water Management, 12(152), pp. 57–71.
Pirmoradian, N. and Davatgar, N. (2019). Simulating the effects of climatic fluctuations on rice irrigation water requirement using AquaCrop. Agricultural Water Management, 213(10), pp. 97–98.
Puértolas, J., Albacete, A., and Dodd, I. C. (2020). Irrigation frequency transiently alters whole plant gas exchange, water and hormone status, but irrigation volume determines cumulative growth in two herbaceous crops. Environmental and Experimental Botany, 176(2), pp. 1–2.
Rahmianna, A. A., Pratiwi, H., and Harnowo, D. (2012). Budidaya kacang tanah. Monograf Balitkabi, 40(13), pp. 133–169.
Silva, V. P. R., Silva, R. A., Maciel, G. F., Braga, C. C., Silva, J. J. L. C., Souza, E. P., Almeida, R. S. R., Silva, M. T., and Holanda, R. M. (2018). Calibration and validation of the Aquacrop Model for the soybean crop grown under different levels of irrigation in the Motopiba Region, Brazil. Ciência Rural, 48(01), pp. 1–8.
Souza, J. L. M., Rosa, S. L. K., Piekarski, K. R., and Tsukahara, R. Y. (2020). Influence of the Aquacrop soil module on the estimation of soybean and maize crop yield in the state of Parana, Brazil. Agronomía Colombiana, 38(2), pp. 234–241.
Victoria, K. Y. N. and Cribbie, R. A. (2018). The Gamma generalized linear model, log transformation, and the robust Yuen-Welch test for analyzing group means with skewed and heteroscedastic data. Communications in Statistics - Simulation and Computation, pp 1–18.
Walters, M. and Sinnett, D. (2021). Achieving tree canopy cover targets: a case study of ristol, UK. Urban Forestry & Urban Greening, 8(12), pp. 1–2.
Wasko, C., Visser, J. B., Nathan, R., Ho, M., and Sharma, A. (2022). Automating rainfall recording : ensuring homogeneity when Instruments change. Journal of Hydrology, 609(1), pp. 2–3.
Xing, H., Xu, X., Li, Z., Chen, Y., Feng, H., Yang, G. and Chen, Z. (2017). Global sensitivity analysis of the Aquacrop Model for winter wheat under different water treatments based on the extended fourier amplitude sensitivity test. Journal of Integrative Agriculture, 16(11), pp. 2444–2458.



DOI: https://doi.org/10.22146/ipas.77304

Article Metrics

Abstract views : 1335 | views : 1152

Refbacks

  • There are currently no refbacks.





Ilmu Pertanian (Agricultural Science) ISSN 0126-4214 (print), ISSN 2527-7162 (online) is published by Faculty of Agriculture Universitas Gadjah Mada collaboration with Perhimpunan Sarjana Pertanian Indonesia (PISPI) and licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

web
analytics View My Stats