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Pear Tree Growth Simulation and Soil Moisture Assessment Considering Pruning

Author

Listed:
  • Chengkun Wang

    (School of Information Engineering, Tarim University, Alaer 843300, China)

  • Nannan Zhang

    (School of Information Engineering, Tarim University, Alaer 843300, China
    Southern Xinjiang Research Center for Information Technology in Agriculture, Tarim University, Alaer 843300, China)

  • Mingzhe Li

    (School of Information Engineering, Tarim University, Alaer 843300, China)

  • Li Li

    (School of Information Engineering, Tarim University, Alaer 843300, China)

  • Tiecheng Bai

    (School of Information Engineering, Tarim University, Alaer 843300, China
    Southern Xinjiang Research Center for Information Technology in Agriculture, Tarim University, Alaer 843300, China)

Abstract

Few studies deal with the application of crop growth models to fruit trees. This research focuses on simulating the growth process, yield and soil moisture assessment of pear trees, considering pruning with a modified WOrld FOod Studies (WOFOST) model. Field trials (eight pruning treatments) were conducted in pear orchards in Alaer and Awat in Xinjiang, China and data were measured to calibrate and evaluate the modified model. In two pear orchards, the simulated total dry weight of storage organs (TWSO) and leaf area index (LAI) were in good agreement with the field measurements of each pruning intensity treatment, indicating that the R 2 values of TWSO ranged from 0.899 to 0.976, and the R 2 values of LAI ranged from 0.849 to 0.924. The modified model also showed high accuracy, with a normalized root mean square error (NRMSE) ranging from 12.19% to 26.11% for TWSO, and the NRMSE values for LAI were less than 10%. The modified model also had a good simulation performance for the soil moisture (SM) under all eight pruning intensity treatments, showing good agreement (0.703 ≤ R 2 ≤ 0.878) and low error (NRMSE ≤ 7.47%). The measured and simulated results of different pruning intensities showed that the highest yield of pear trees was achieved when the pruning intensity was about 20%, and the yield increased and then decreased with the increase in pruning intensity. In conclusion, the modified WOFOST model can better describe the effects of summer pruning on pear tree growth, yield and soil moisture than the unmodified model, providing a promising quantitative analysis method for the numerical simulation and soil moisture assessment of fruit tree growth.

Suggested Citation

  • Chengkun Wang & Nannan Zhang & Mingzhe Li & Li Li & Tiecheng Bai, 2022. "Pear Tree Growth Simulation and Soil Moisture Assessment Considering Pruning," Agriculture, MDPI, vol. 12(10), pages 1-26, October.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:10:p:1653-:d:937265
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    References listed on IDEAS

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    1. Wang, Linlin & Wu, Wenyong & Xiao, Juan & Huang, Qiannan & Hu, Yaqi, 2021. "Effects of different drip irrigation modes on water use efficiency of pear trees in Northern China," Agricultural Water Management, Elsevier, vol. 245(C).
    2. Desheng Wang & Chengkun Wang & Lichao Xu & Tiecheng Bai & Guozheng Yang, 2022. "Simulating Growth and Evaluating the Regional Adaptability of Cotton Fields with Non-Film Mulching in Xinjiang," Agriculture, MDPI, vol. 12(7), pages 1-20, June.
    3. Siad, Si Mokrane & Iacobellis, Vito & Zdruli, Pandi & Gioia, Andrea & Stavi, Ilan & Hoogenboom, Gerrit, 2019. "A review of coupled hydrologic and crop growth models," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    4. Cui, Ningbo & Du, Taisheng & Li, Fusheng & Tong, Ling & Kang, Shaozhong & Wang, Mixia & Liu, Xiaozhi & Li, Zhijun, 2009. "Response of vegetative growth and fruit development to regulated deficit irrigation at different growth stages of pear-jujube tree," Agricultural Water Management, Elsevier, vol. 96(8), pages 1237-1246, August.
    5. Sandhu, Rupinder & Irmak, Suat, 2019. "Performance of AquaCrop model in simulating maize growth, yield, and evapotranspiration under rainfed, limited and full irrigation," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    6. Cui, Ningbo & Du, Taisheng & Kang, Shaozhong & Li, Fusheng & Zhang, Jianhua & Wang, Mixia & Li, Zhijun, 2008. "Regulated deficit irrigation improved fruit quality and water use efficiency of pear-jujube trees," Agricultural Water Management, Elsevier, vol. 95(4), pages 489-497, April.
    7. Qiu, Rangjian & Li, Longan & Liu, Chunwei & Wang, Zhenchang & Zhang, Baozhong & Liu, Zhandong, 2022. "Evapotranspiration estimation using a modified crop coefficient model in a rotated rice-winter wheat system," Agricultural Water Management, Elsevier, vol. 264(C).
    8. Molina, A.J. & Aranda, X. & Llorens, P. & Galindo, A. & Biel, C., 2019. "Sap flow of a wild cherry tree plantation growing under Mediterranean conditions: Assessing the role of environmental conditions on canopy conductance and the effect of branch pruning on water product," Agricultural Water Management, Elsevier, vol. 218(C), pages 222-233.
    9. Xu, Junzeng & Bai, Wenhuan & Li, Yawei & Wang, Haiyu & Yang, Shihong & Wei, Zheng, 2019. "Modeling rice development and field water balance using AquaCrop model under drying-wetting cycle condition in eastern China," Agricultural Water Management, Elsevier, vol. 213(C), pages 289-297.
    10. Ceglar, A. & van der Wijngaart, R. & de Wit, A. & Lecerf, R. & Boogaard, H. & Seguini, L. & van den Berg, M. & Toreti, A. & Zampieri, M. & Fumagalli, D. & Baruth, B., 2019. "Improving WOFOST model to simulate winter wheat phenology in Europe: Evaluation and effects on yield," Agricultural Systems, Elsevier, vol. 168(C), pages 168-180.
    11. Bai, Tiecheng & Zhang, Nannan & Wang, Tao & Wang, Desheng & Yu, Caili & Meng, Wenbo & Fei, Hao & Chen, Rengu & Li, Yanhui & Zhou, Baoping, 2021. "Simulating on the effects of irrigation on jujube tree growth, evapotranspiration and water use based on crop growth model," Agricultural Water Management, Elsevier, vol. 243(C).
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