IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i11p1166-d682797.html
   My bibliography  Save this article

Crop Models: Important Tools in Decision Support System to Manage Wheat Production under Vulnerable Environments

Author

Listed:
  • Aftab Wajid

    (Agro-Climatology Laboratory, Department of Agronomy, University of Agriculture, Faisalabad 38040, Pakistan)

  • Khalid Hussain

    (Agro-Climatology Laboratory, Department of Agronomy, University of Agriculture, Faisalabad 38040, Pakistan)

  • Ayesha Ilyas

    (Agro-Climatology Laboratory, Department of Agronomy, University of Agriculture, Faisalabad 38040, Pakistan)

  • Muhammad Habib-ur-Rahman

    (Department of Agronomy, MNS University of Agriculture, Multan 60000, Pakistan)

  • Qamar Shakil

    (Fooder Research Sub-Station, AARI, Faisalabad 38850, Pakistan)

  • Gerrit Hoogenboom

    (Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32611, USA)

Abstract

Decision support systems are key for yield improvement in modern agriculture. Crop models are decision support tools for crop management to increase crop yield and reduce production risks. Decision Support System for Agrotechnology Transfer (DSSAT) and an Agricultural System simulator (APSIM), intercomparisons were done to evaluate their performance for wheat simulation. Two-year field experimental data were used for model parameterization. The first year was used for calibration and the second-year data were used for model evaluation and intercomparison. Calibrated models were then evaluated with 155 farmers’ fields surveyed for data in rice-wheat cropping systems. Both models simulated crop phenology, leaf area index (LAI), total dry matter and yield with high goodness of fit to the measured data during both years of evaluation. DSSAT better predicted yield compared to APSIM with a goodness of fit of 64% and 37% during evaluation of 155 farmers’ data. Comparison of individual farmer’s yields showed that the model simulated wheat yield with percent differences (PDs) of −25% to 17% and −26% to 40%, Root Mean Square Errors ( RMSE s) of 436 and 592 kg ha −1 with reasonable d-statistics of 0.87 and 0.72 for DSSAT and APSIM, respectively. Both models were used successfully as decision support system tools for crop improvement under vulnerable environments.

Suggested Citation

  • Aftab Wajid & Khalid Hussain & Ayesha Ilyas & Muhammad Habib-ur-Rahman & Qamar Shakil & Gerrit Hoogenboom, 2021. "Crop Models: Important Tools in Decision Support System to Manage Wheat Production under Vulnerable Environments," Agriculture, MDPI, vol. 11(11), pages 1-22, November.
  • Handle: RePEc:gam:jagris:v:11:y:2021:i:11:p:1166-:d:682797
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/11/1166/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/11/11/1166/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Singh, Anil Kumar & Tripathy, Rojalin & Chopra, Usha Kiran, 2008. "Evaluation of CERES-Wheat and CropSyst models for water-nitrogen interactions in wheat crop," Agricultural Water Management, Elsevier, vol. 95(7), pages 776-786, July.
    2. Kalra, Naveen & Chakraborty, Debashis & Ramesh Kumar, P. & Jolly, Monica & Sharma, P.K., 2007. "An approach to bridging yield gaps, combining response to water and other resource inputs for wheat in northern India, using research trials and farmers' fields data," Agricultural Water Management, Elsevier, vol. 93(1-2), pages 54-64, October.
    3. Arora, V.K. & Singh, Harbakhshinder & Singh, Bijay, 2007. "Analyzing wheat productivity responses to climatic, irrigation and fertilizer-nitrogen regimes in a semi-arid sub-tropical environment using the CERES-Wheat model," Agricultural Water Management, Elsevier, vol. 94(1-3), pages 22-30, December.
    4. Zhao, Gang & Bryan, Brett A. & Song, Xiaodong, 2014. "Sensitivity and uncertainty analysis of the APSIM-wheat model: Interactions between cultivar, environmental, and management parameters," Ecological Modelling, Elsevier, vol. 279(C), pages 1-11.
    5. Timsina, J. & Humphreys, E., 2006. "Performance of CERES-Rice and CERES-Wheat models in rice-wheat systems: A review," Agricultural Systems, Elsevier, vol. 90(1-3), pages 5-31, October.
    6. K.J. Boote & J.W. Jones & G. Hoogenboom & J.W. White, 2010. "The Role of Crop Systems Simulation in Agriculture and Environment," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 1(1), pages 41-54, January.
    7. Carberry, P. S. & Hochman, Z. & McCown, R. L. & Dalgliesh, N. P. & Foale, M. A. & Poulton, P. L. & Hargreaves, J. N. G. & Hargreaves, D. M. G. & Cawthray, S. & Hillcoat, N. & Robertson, M. J., 2002. "The FARMSCAPE approach to decision support: farmers', advisers', researchers' monitoring, simulation, communication and performance evaluation," Agricultural Systems, Elsevier, vol. 74(1), pages 141-177, October.
    8. Saseendran, S.A. & Trout, T.J. & Ahuja, L.R. & Ma, L. & McMaster, G.S. & Nielsen, D.C. & Andales, A.A. & Chávez, J.L. & Ham, J., 2015. "Quantifying crop water stress factors from soil water measurements in a limited irrigation experiment," Agricultural Systems, Elsevier, vol. 137(C), pages 191-205.
    9. Chen, Chao & Wang, Enli & Yu, Qiang, 2010. "Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain," Agricultural Water Management, Elsevier, vol. 97(8), pages 1175-1184, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vieira Junior, Nilson & Carcedo, Ana Julia Paula & Min, Doohong & Diatta, Andre Amakobo & Araya, Alemie & Prasad, P.V. Vara & Diallo, Amadiane & Ciampitti, Ignacio, 2023. "Management adaptations for water-limited pearl millet systems in Senegal," Agricultural Water Management, Elsevier, vol. 278(C).
    2. Elzbieta Czembor & Zygmunt Kaczmarek & Wiesław Pilarczyk & Dariusz Mańkowski & Jerzy H. Czembor, 2022. "Simulating Spring Barley Yield under Moderate Input Management System in Poland," Agriculture, MDPI, vol. 12(8), pages 1-20, July.
    3. Md Rafique Ahasan Chawdhery & Murtuza Al-Mueed & Md Abdul Wazed & Shah-Al Emran & Md Abeed Hossain Chowdhury & Sk Ghulam Hussain, 2022. "Climate Change Impacts Assessment Using Crop Simulation Model Intercomparison Approach in Northern Indo-Gangetic Basin of Bangladesh," IJERPH, MDPI, vol. 19(23), pages 1-20, November.
    4. Yingnan Wei & Han Ru & Xiaolan Leng & Zhijian He & Olusola O. Ayantobo & Tehseen Javed & Ning Yao, 2022. "Better Performance of the Modified CERES-Wheat Model in Simulating Evapotranspiration and Wheat Growth under Water Stress Conditions," Agriculture, MDPI, vol. 12(11), pages 1-15, November.
    5. Irina Pilvere & Aleksejs Nipers & Agnese Krievina & Ilze Upite & Daniels Kotovs, 2022. "LASAM Model: An Important Tool in the Decision Support System for Policymakers and Farmers," Agriculture, MDPI, vol. 12(5), pages 1-26, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(C).
    2. Anshuman Gunawat & Devesh Sharma & Aditya Sharma & Swatantra Kumar Dubey, 2022. "Assessment of climate change impact and potential adaptation measures on wheat yield using the DSSAT model in the semi-arid environment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 2077-2096, March.
    3. Malik, Wafa & Dechmi, Farida, 2019. "DSSAT modelling for best irrigation management practices assessment under Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 216(C), pages 27-43.
    4. Phelan, David C. & Harrison, Matthew T. & McLean, Greg & Cox, Howard & Pembleton, Kieth G. & Dean, Geoff J. & Parsons, David & do Amaral Richter, Maria E. & Pengilley, Georgie & Hinton, Sue J. & Moham, 2018. "Advancing a farmer decision support tool for agronomic decisions on rainfed and irrigated wheat cropping in Tasmania," Agricultural Systems, Elsevier, vol. 167(C), pages 113-124.
    5. Ahmed M. S. Kheir & Hiba M. Alkharabsheh & Mahmoud F. Seleiman & Adel M. Al-Saif & Khalil A. Ammar & Ahmed Attia & Medhat G. Zoghdan & Mahmoud M. A. Shabana & Hesham Aboelsoud & Calogero Schillaci, 2021. "Calibration and Validation of AQUACROP and APSIM Models to Optimize Wheat Yield and Water Saving in Arid Regions," Land, MDPI, vol. 10(12), pages 1-16, December.
    6. Zhang, Yuxi & Walker, Jeffrey P. & Pauwels, Valentijn R.N., 2022. "Assimilation of wheat and soil states for improved yield prediction: The APSIM-EnKF framework," Agricultural Systems, Elsevier, vol. 201(C).
    7. Zeng, Ruiyun & Lin, Xiaomao & Welch, Stephen M. & Yang, Shanshan & Huang, Na & Sassenrath, Gretchen F. & Yao, Fengmei, 2023. "Impact of water deficit and irrigation management on winter wheat yield in China," Agricultural Water Management, Elsevier, vol. 287(C).
    8. Zeng, Ruiyun & Yao, Fengmei & Zhang, Sha & Yang, Shanshan & Bai, Yun & Zhang, Jiahua & Wang, Jingwen & Wang, Xin, 2021. "Assessing the effects of precipitation and irrigation on winter wheat yield and water productivity in North China Plain," Agricultural Water Management, Elsevier, vol. 256(C).
    9. Liu, H.L. & Yang, J.Y. & Tan, C.S. & Drury, C.F. & Reynolds, W.D. & Zhang, T.Q. & Bai, Y.L. & Jin, J. & He, P. & Hoogenboom, G., 2011. "Simulating water content, crop yield and nitrate-N loss under free and controlled tile drainage with subsurface irrigation using the DSSAT model," Agricultural Water Management, Elsevier, vol. 98(6), pages 1105-1111, April.
    10. Devkota, Mina & Devkota, Krishna Prasad & Paudel, Gokul Prasad & Krupnik, Timothy J. & McDonald, Andrew James, 2024. "Opportunities to close wheat yield gaps in Nepal's Terai: Insights from field surveys, on-farm experiments, and simulation modeling," Agricultural Systems, Elsevier, vol. 213(C).
    11. Si, Zhuanyun & Zain, Muhammad & Li, Shuang & Liu, Junming & Liang, Yueping & Gao, Yang & Duan, Aiwang, 2021. "Optimizing nitrogen application for drip-irrigated winter wheat using the DSSAT-CERES-Wheat model," Agricultural Water Management, Elsevier, vol. 244(C).
    12. Timsina, J. & Godwin, D. & Humphreys, E. & Yadvinder-Singh & Bijay-Singh & Kukal, S.S. & Smith, D., 2008. "Evaluation of options for increasing yield and water productivity of wheat in Punjab, India using the DSSAT-CSM-CERES-Wheat model," Agricultural Water Management, Elsevier, vol. 95(9), pages 1099-1110, September.
    13. Mahboobe Ghobadi & Mahdi Gheysari & Mohammad Shayannejad & Hamze Dokoohaki, 2023. "Analyzing the Effects of Planting Date on the Uncertainty of CERES-Maize and Its Potential to Reduce Yield Gap in Arid and Mediterranean Climates," Agriculture, MDPI, vol. 13(8), pages 1-17, July.
    14. Gupta, Rishabh & Mishra, Ashok, 2019. "Climate change induced impact and uncertainty of rice yield of agro-ecological zones of India," Agricultural Systems, Elsevier, vol. 173(C), pages 1-11.
    15. Haomiao Cheng & Qilin Yu & Mohmed A. M. Abdalhi & Fan Li & Zhiming Qi & Tengyi Zhu & Wei Cai & Xiaoping Chen & Shaoyuan Feng, 2022. "RZWQM2 Simulated Drip Fertigation Management to Improve Water and Nitrogen Use Efficiency of Maize in a Solar Greenhouse," Agriculture, MDPI, vol. 12(5), pages 1-14, May.
    16. Hisham Eldardiry & Emad Habib & David M. Borrok, 2020. "Accounting for Inter-Annual and Seasonal Variability in Assessment of Water Supply Stress: Perspectives from a humid region in the USA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(8), pages 2517-2534, June.
    17. Hao, Shirui & Ryu, Dongryeol & Western, Andrew W & Perry, Eileen & Bogena, Heye & Franssen, Harrie Jan Hendricks, 2024. "Global sensitivity analysis of APSIM-wheat yield predictions to model parameters and inputs," Ecological Modelling, Elsevier, vol. 487(C).
    18. Paresh B. Shirsath & Vinay Kumar Sehgal & Pramod K. Aggarwal, 2020. "Downscaling Regional Crop Yields to Local Scale Using Remote Sensing," Agriculture, MDPI, vol. 10(3), pages 1-14, March.
    19. Shahadha, Saadi Sattar & Wendroth, Ole & Zhu, Junfeng & Walton, Jason, 2019. "Can measured soil hydraulic properties simulate field water dynamics and crop production?," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    20. Yan Shan & Mingbin Huang & Paul Harris & Lianhai Wu, 2021. "A Sensitivity Analysis of the SPACSYS Model," Agriculture, MDPI, vol. 11(7), pages 1-30, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:11:y:2021:i:11:p:1166-:d:682797. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.