IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i10p1653-d937265.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/10/1653/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/12/10/1653/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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).
    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).
    Full references (including those not matched with items on IDEAS)

    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. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    2. Zhu, Hongyan & Zheng, Bingyan & Nie, Weibo & Fei, Liangjun & Shan, Yuyang & Li, Ge & Liang, Fei, 2024. "Optimization of maize irrigation strategy in Xinjiang, China by AquaCrop based on a four-year study," Agricultural Water Management, Elsevier, vol. 297(C).
    3. Wang, Jiaxin & He, Xinlin & Gong, Ping & Heng, Tong & Zhao, Danqi & Wang, Chunxia & Chen, Quan & Wei, Jie & Lin, Ping & Yang, Guang, 2024. "Response of fragrant pear quality and water productivity to lateral depth and irrigation amount," Agricultural Water Management, Elsevier, vol. 292(C).
    4. Bai, Youshuai & Zhang, Hengjia & Jia, Shenghai & Huang, Caixia & Zhao, Xia & Wei, Huiqin & Yang, Shurui & Ma, Yan & Kou, Rui, 2022. "Plastic film mulching combined with sand tube irrigation improved yield, water use efficiency, and fruit quality of jujube in an arid desert area of Northwest China," Agricultural Water Management, Elsevier, vol. 271(C).
    5. Feng, Yu & Cui, Ningbo & Du, Taisheng & Gong, Daozhi & Hu, Xiaotao & Zhao, Lu, 2017. "Response of sap flux and evapotranspiration to deficit irrigation of greenhouse pear-jujube trees in semi-arid northwest China," Agricultural Water Management, Elsevier, vol. 194(C), pages 1-12.
    6. Zhong, Yun & Fei, Liangjun & Li, Yibo & Zeng, Jian & Dai, Zhiguang, 2019. "Response of fruit yield, fruit quality, and water use efficiency to water deficits for apple trees under surge-root irrigation in the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 222(C), pages 221-230.
    7. Galindo, A. & Collado-González, J. & Griñán, I. & Corell, M. & Centeno, A. & Martín-Palomo, M.J. & Girón, I.F. & Rodríguez, P. & Cruz, Z.N. & Memmi, H. & Carbonell-Barrachina, A.A. & Hernández, F. & T, 2018. "Deficit irrigation and emerging fruit crops as a strategy to save water in Mediterranean semiarid agrosystems," Agricultural Water Management, Elsevier, vol. 202(C), pages 311-324.
    8. Liao, Yang & Cao, Hong-Xia & Xue, Wen-Kai & Liu, Xing, 2021. "Effects of the combination of mulching and deficit irrigation on the soil water and heat, growth and productivity of apples," Agricultural Water Management, Elsevier, vol. 243(C).
    9. Janssens, Pieter & Deckers, Tom & Elsen, Frank & Elsen, Annemie & Schoofs, Hilde & Verjans, Wim & Vandendriessche, Hilde, 2011. "Sensitivity of root pruned ‘Conference’ pear to water deficit in a temperate climate," Agricultural Water Management, Elsevier, vol. 99(1), pages 58-66.
    10. Wen, Shenglin & Cui, Ningbo & Gong, Daozhi & Liu, Chunwei & Xing, Liwen & Wu, Zongjun & Wang, Zhihui & Wang, Jiaxin, 2023. "A global meta-analysis of yield and water productivity of woody, herbaceous and vine fruits under deficit irrigation," Agricultural Water Management, Elsevier, vol. 287(C).
    11. Xiaopeng Li & Yupeng Li & Zhong Zhang & Xingang Li, 2015. "Influences of Environmental Factors on Leaf Morphology of Chinese Jujubes," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-16, May.
    12. Zhaoyang Li & Rui Zong & Tianyu Wang & Zhenhua Wang & Jinzhu Zhang, 2021. "Adapting Root Distribution and Improving Water Use Efficiency via Drip Irrigation in a Jujube ( Zizyphus jujube Mill.) Orchard after Long-Term Flood Irrigation," Agriculture, MDPI, vol. 11(12), pages 1-16, November.
    13. Feng, Yu & Gong, Daozhi & Mei, Xurong & Hao, Weiping & Tang, Dahua & Cui, Ningbo, 2017. "Energy balance and partitioning in partial plastic mulched and non-mulched maize fields on the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 191(C), pages 193-206.
    14. Kelly, T.D. & Foster, T. & Schultz, David M., 2023. "Assessing the value of adapting irrigation strategies within the season," Agricultural Water Management, Elsevier, vol. 275(C).
    15. Kang, Shaozhong & Hao, Xinmei & Du, Taisheng & Tong, Ling & Su, Xiaoling & Lu, Hongna & Li, Xiaolin & Huo, Zailin & Li, Sien & Ding, Risheng, 2017. "Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice," Agricultural Water Management, Elsevier, vol. 179(C), pages 5-17.
    16. Lu, Yingjie & Li, Tao & Hu, Hui & Zeng, Xuemei, 2023. "Short-term prediction of reference crop evapotranspiration based on machine learning with different decomposition methods in arid areas of China," Agricultural Water Management, Elsevier, vol. 279(C).
    17. Marco Bascietto & Enrico Santangelo & Claudio Beni, 2021. "Spatial Variations of Vegetation Index from Remote Sensing Linked to Soil Colloidal Status," Land, MDPI, vol. 10(1), pages 1-15, January.
    18. Tsakmakis, I.D. & Gikas, G.D. & Sylaios, G.K., 2021. "Integration of Sentinel-derived NDVI to reduce uncertainties in the operational field monitoring of maize," Agricultural Water Management, Elsevier, vol. 255(C).
    19. Wen, Shenglin & Cui, Ningbo & Wang, Yaosheng & Gong, Daozhi & Xing, Liwen & Wu, Zongjun & Zhang, Yixuan & Zhao, Long & Fan, Junliang & Wang, Zhihui, 2024. "Optimizing deficit drip irrigation to improve yield,quality, and water productivity of apple in Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 296(C).
    20. Wang, Haidong & Wang, Naijiang & Quan, Hao & Zhang, Fucang & Fan, Junliang & Feng, Hao & Cheng, Minghui & Liao, Zhenqi & Wang, Xiukang & Xiang, Youzhen, 2022. "Yield and water productivity of crops, vegetables and fruits under subsurface drip irrigation: A global meta-analysis," Agricultural Water Management, Elsevier, vol. 269(C).

    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:12:y:2022:i:10:p:1653-:d:937265. 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.