The development of a new crop growth model SwitchFor for yield mapping of switchgrass

Yanmei Liu* (Corresponding Author), Astley Hastings, Shaolin Chen, Andre Faaij

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Switchgrass is a promising energy crop has the potential to mitigate global warming and energy security, improve local ecology and generate profit. Its quantitative traits, such as biomass productivity and environmental adaptability, are determined by genotype-by-environment interaction (GEI) or response of genotypes grown across different target environments. To simulate the yield of switchgrass outside its original habitat, a genotype-specific growth model, SwitchFor that captures GEI was developed by parameterising the MiscanFor model. Input parameters were used to describe genotype-specific characteristics under different soil and climate conditions, which enables the model to predict the yield in a wide range of environmental and climate conditions. The model was validated using global field trail data and applied to estimate the switchgrass yield potentials on the marginal land of the Loess Plateau in China. The results suggest that upland and lowland switchgrass have significant differences in the spatial distribution of the adaptation zone and site-specific biomass yield. The area of the adaption zone of upland switchgrass was 4.5 times of the lowland ecotype's. The yield difference between upland and lowland ecotypes ranges from 0 to 34 Mg ha−1. The weighted average yield of the lowland ecotype (20 Mg ha−1) is significantly higher than the upland type (5 Mg ha−1). The optimal yield map, generated by comparing the yield of upland and lowland ecotypes based on 1 km2 grid locations, illustrates that the total yield potential of the optimal switchgrass is 61.6–106.4 Tg on the marginal land of the Loess Plateau, which is approximately twice that of the individual ecotypes. Compared with the existing models, the accuracy of the yield prediction of switchgrass is significantly improved by using the SwitchFor model. This spatially explicit and cultivar-specific model provides valuable information on land management and crop breeding and a robust and extendable framework for yield mapping of other cultivars.
Original languageEnglish
Pages (from-to)1281-1302
Number of pages22
JournalGlobal Change Biology. Bioenergy
Issue number12
Early online date3 Oct 2022
Publication statusPublished - 1 Dec 2022

Bibliographical note

This study was supported by the Chinese Scholarship Council (CSC) and partially supported by the National Key Project of Intergovernmental Cooperation in International Scientific and Technological Innovation (2018YFE0112400 to S.C.). A.H. was funded by was funded by the ADVENT project funded by the UK Natural Environment Research Council (NE/M019691/1) and ADVANCES funded by the UK Natural Environment Research Council (NE/M019691/1), EPSRC funded UKERC-4 and the BBSRC funded PCB4GGR project (BB/V011553/1). We would like to Bingchen Xu, from Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, China, for providing field trail data of the switchgrass on the Loess Plateau. We also acknowledge the data support from the Loess Plateau Data Center, National Earth System Science Data Sharing Infrastructure, and National Science and Technology Infrastructure of China (

Data Availability Statement

Data Availability
The climate data of China was obtained from the National Scientific Meteorological Centre ( The climate data of the US, Canada, and European was obtained from public database. The daily temperature and precipitation data was obtained from national centers for environmental information (NOAA), the evapotranspiration data were collected from the National Aeronautics and Space Administration (NASA), and the solar radiation data were collected from Application for Extracting and Exploring Analysis Ready Samples (APPEEARS). The key output of Switch For model in this study are the spatial distribution biomass yield maps of switchgrass (upland switchgrass, lowland switchgrass, and optimal switchgrass) on the marginal land of the Loess Plateau in the land use scenario1 and scenario2. The data supporting the findings of this study are openly available in the file name of “Spatial distribution of the yield biomass of switchgrass on the marginal land o fthe Loess Plateau” at are.21047 224.v1. The data are raster maps in Tiffformation with resolution of1 × 1 km2.

Supporting Information
Additional supporting information can be found online in the Supporting Information section at the end of this article


  • bio-energy
  • biomass production
  • genotype-by-environment interaction
  • genotype-specific plant growth model
  • marginal land
  • SwitchFor model


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