Journal of Integrative Agriculture ›› 2020, Vol. 19 ›› Issue (3): 721-734.DOI: 10.1016/S2095-3119(19)62753-X

所属专题: 园艺-栽培生理/资源品质合辑Horticulture — Physiology · Biochemistry · Cultivation

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  • 收稿日期:2019-02-01 出版日期:2020-03-01 发布日期:2020-03-04

Growth simulation and yield prediction for perennial jujube fruit tree by integrating age into the WOFOST model

BAI Tie-cheng1, 2, WANG Tao2, ZHANG Nan-nan2, CHEN You-qi3, Benoit MERCATORIS1 
  

  1. 1 TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, Liège University, Gembloux 5030, Belgium
    2 Southern Xinjiang Research Center for Information Technology in Agriculture/College of Information Engineering, Tarim University, Alaer 843300, P.R.China
    3 Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
  • Received:2019-02-01 Online:2020-03-01 Published:2020-03-04
  • Contact: Correspondence CHEN You-qi, E-mail: chenyouqi@caas.cn; Benoit MERCATORIS, E-mail: benoit.mercatoris@uliege.be
  • About author:BAI Tie-cheng, E-mail: baitiecheng1983@163.com;
  • Supported by:
    This research was supported by the National Natural Science Foundation of China (41561088 and 61501314) and the Science & Technology Nova Program of Xinjiang Production and Construction Corps, China (2018CB020).

Abstract:

Mathematical models have been widely employed for the simulation of growth dynamics of annual crops, thereby performing yield prediction, but not for fruit tree species such as jujube tree (Zizyphus jujuba).  The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter.  The model was established using data collected from dedicated field experiments performed in 2016–2018.  Simulated growth dynamics of dry weights of leaves, stems, fruits, total biomass and leaf area index (LAI) agreed well with measured values, showing root mean square error (RMSE) values of 0.143, 0.333, 0.366, 0.624 t ha–1 and 0.19, and R2 values of 0.947, 0.976, 0.985, 0.986 and 0.95, respectively.  Simulated phenological development stages for emergence, anthesis and maturity were 2, 3 and 3 days earlier than the observed values, respectively.  In addition, in order to predict the yields of trees with different ages, the weight of new organs (initial buds and roots) in each growing season was introduced as the initial total dry weight (TDWI), which was calculated as averaged, fitted and optimized values of trees with the same age.  The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI.  The modelling performance was significantly improved when it considered TDWI integrated with tree age, showing good global (R2≥0.856, RMSE≤0.68 t ha–1) and local accuracies (mean R2≥0.43, RMSE≤0.70 t ha–1).  Furthermore, the optimized TDWI exhibited the highest precision, with globally validated R2 of 0.891 and RMSE of 0.591 t ha–1, and local mean R2 of 0.57 and RMSE of 0.66 t ha–1, respectively.  The proposed model was not only verified with the confidence to accurately predict yields of jujube, but it can also provide a fundamental strategy for simulating the growth of other fruit trees.
 

Key words: fruit tree ,  growth simulation ,  yield forecasting ,  crop model ,  tree age