产量(工程)
过程(计算)
增长模型
农学
生物
园艺
植物
数学
计算机科学
物理
热力学
操作系统
数理经济学
作者
Álvaro López‐Bernal,Alejandro Morales,Omar García-Tejera,Luca Testi,F. Orgaz,José Paulo De Melo-Abreu,Francisco J. Villalobos
标识
DOI:10.3389/fpls.2018.00632
摘要
Several simulation models of the olive crop have been formulated so far, but none of them is capable of analyzing the impact of environmental conditions and management practices on water relations, growth and productivity under both well-irrigated and water-limiting irrigation strategies. This paper presents and tests OliveCan, a process-oriented model conceived for those purposes. In short, OliveCan is composed of three main model components simulating the principal elements of the water and carbon balances of olive orchards and the impacts of some management operations. To assess its predictive power, OliveCan was tested against independent data collected in two 3-year field experiments conducted in Córdoba, Spain, each of them applying different irrigation treatments. An acceptable level of agreement was found between measured and simulated values of seasonal evapotranspiration (ET, range 393 to 1016 mm year-1; RMSE of 89 mm year-1), daily transpiration (Ep, range 0.14-3.63 mm d-1; RMSE of 0.32 mm d-1) and oil yield (Yoil, range 13-357 g m-2; RMSE of 63 g m-2). Finally, knowledge gaps identified during the formulation of the model and further testing needs are discussed, highlighting that there is additional room for improving its robustness. It is concluded that OliveCan has a strong potential as a simulation platform for a variety of research applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI