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| DOI | 10.1016/j.fcr.2024.109306 |
| Evaluating differences among crop models in simulating soybean in-season growth | |
| 发表日期 | 2024 |
| ISSN | 0378-4290 |
| EISSN | 1872-6852 |
| 起始页码 | 309 |
| 卷号 | 309 |
| 英文摘要 | Crop models are useful tools for simulating agricultural systems that require continued model development and testing to increase their robustness and improve how they describe our current understanding of processes. Coordinated and blind evaluation of multiple models using same protocols and experimental datasets provides unique opportunities to further improve models and enhance their reliability. For soybean [Glycine max (L.) Merr.], there has been limited coordinated multi-model evaluations for the simulation of in-season plant growth dynamics. We evaluated ten dynamic soybean crop models for their simulation of in-season plant growth using data from five experiments conducted in Argentina, Brazil, France, and USA. We evaluated models after a Blind (using only phenology data) and a Full calibration (with in-season and end-of-season variables). Calibration reduced model uncertainty by reducing standard bias for the simulation of in-season variables (biomass, leaf, pod, and stem weights, and leaf area index, LAI). However, we found that most models had difficulty in reproducing leaf growth dynamics, with normalized root mean squared error (nRMSE) of 56% for leaf weight and 43% for LAI (across locations and models after Full calibration). Models with different levels of complexity and experience were capable of simulating final seed yield at maturity with reasonable accuracy (nRMSE of 8-31% after Full calibration). However, the nRMSE for pod weight (of 17-64% after Full calibration) was two-fold larger than that of seed yield. Moreover, the models differed in how they simulated timing from sowing to beginning seed growth (47-93 days) and effective seed filling period (18-54 days), owing to model structural differences in defining the reproductive developmental stages. Overall, we identified the following processes that can benefit from further model improvement: leaf expansion and senescence, reproductive phenology, and partitioning to reproductive growth. Simulation of pod wall tissue and individual seed cohorts is another aspect that many models currently lack. Model improvement can benefit from high-temporal resolution experimental datasets that concurrently account for phenology, plant growth, and partitioning. Further, we recommend collecting reproductive phenology in the field consistent with actual dry matter allocation to organs in the models and collecting multiple observations of seed and pod weight to aid model improvement for simulation of seed growth and yield formation. |
| 英文关键词 | Agricultural Model Intercomparison and; Improvement Project (AgMIP); multi -model evaluation; pod growth; leaf area index; reproductive partitioning |
| 语种 | 英语 |
| WOS研究方向 | Agriculture |
| WOS类目 | Agronomy |
| WOS记录号 | WOS:001201828400001 |
| 来源期刊 | FIELD CROPS RESEARCH
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/305948 |
| 作者单位 | University of Kentucky; Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Roorkee; Universidade Federal de Goias; State University System of Florida; University of Florida; Iowa State University; Comision Nacional de Energia Atomica (CNEA); INRAE; Empresa Brasileira de Pesquisa Agropecuaria (EMBRAPA); Agriculture & Agri Food Canada; State University System of Florida; University of Florida; University of Pretoria; Universidade de Sao Paulo; Gorgan University of Agricultural Sciences & Natural Resources; Leibniz Zentrum fur Agrarlandschaftsforschung (ZALF); University of Potsdam; Czech Academy of Sciences; Global Change Research Centre of the Czech Academy of Sciences; University of Arkansas System; University of Arkansas Fayetteville; National Aeronautics & Space Administration (NASA); NASA Goddard Space Flight Center; Goddard Institute for Space Studies; University of Bonn |
| 推荐引用方式 GB/T 7714 | . Evaluating differences among crop models in simulating soybean in-season growth[J],2024,309. |
| APA | (2024).Evaluating differences among crop models in simulating soybean in-season growth.FIELD CROPS RESEARCH,309. |
| MLA | "Evaluating differences among crop models in simulating soybean in-season growth".FIELD CROPS RESEARCH 309(2024). |
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