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

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          Abstract

          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 km 2 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.

          Abstract

          A new cultivar‐specific switchgrass plant growth model, SwitchFor model, was developed and validated to give an accurate estimation of the switchgrass yield in a wide environment. The SwitchFor model was applied to the Loess Plateau region, which has about 12.8–20.8 Mha marginal land to estimate the yield potential. It was estimated that the Loess Plateau has a potential to produce up to 62–106 Tg switchgrass by considering the upland and lowland ecotype.

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          Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset

          CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5° latitude by 0.5° longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901–2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically.
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            Feedstocks for lignocellulosic biofuels.

            In 2008, the world produced approximately 87 gigaliters of liquid biofuels, which is roughly equal to the volume of liquid fuel consumed by Germany that year. Essentially, all of this biofuel was produced from crops developed for food production, raising concerns about the net energy and greenhouse gas effects and potential competition between use of land for production of fuels, food, animal feed, fiber, and ecosystem services. The pending implementation of improved technologies to more effectively convert the nonedible parts of plants (lignocellulose) to liquid fuels opens diverse options to use biofuel feedstocks that reach beyond current crops and the land currently used for food and feed. However, there has been relatively little discussion of what types of plants may be useful as bioenergy crops.
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              Meeting US biofuel goals with less land: the potential of Miscanthus

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                Author and article information

                Contributors
                yanmei.liu@rug.nl
                Journal
                Glob Change Biol Bioenergy
                Glob Change Biol Bioenergy
                10.1111/(ISSN)1757-1707
                GCBB
                Global Change Biology. Bioenergy
                John Wiley and Sons Inc. (Hoboken )
                1757-1693
                1757-1707
                03 October 2022
                December 2022
                : 14
                : 12 ( doiID: 10.1111/gcbb.v14.12 )
                : 1281-1302
                Affiliations
                [ 1 ] Integrated Research on Energy, Environment and Soc—Energy and Sustainability Research Institute Groningen University of Groningen Groningen The Netherlands
                [ 2 ] Institute of Biological and Environmental Science University of Aberdeen Aberdeen UK
                [ 3 ] Biomass Energy Center for Arid and Semi‐Arid Lands Northwest A&F University Yangling P.R. China
                [ 4 ] TNO, Energy Transition Utrecht The Netherlands
                [ 5 ] Copernicus Institute for Sustainable Development Utrecht University Utrecht The Netherlands
                Author notes
                [*] [* ] Correspondence

                Yanmei Liu, Integrated Research on Energy, Environment and Soc—Energy and Sustainability Research Institute Groningen, University of Groningen, Nijenborgh 6, 9747 AG Groningen, The Netherlands.

                Email: yanmei.liu@ 123456rug.nl

                Author information
                https://orcid.org/0000-0003-4123-9002
                https://orcid.org/0000-0001-7607-8275
                Article
                GCBB12998 GCB-B-RA-22-040.R1
                10.1111/gcbb.12998
                9828430
                36636026
                cd789599-b029-48dc-9074-3c85bfa41a65
                © 2022 The Authors. GCB Bioenergy published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 August 2022
                : 13 April 2022
                : 19 August 2022
                Page count
                Figures: 10, Tables: 4, Pages: 22, Words: 11361
                Funding
                Funded by: UK Natural Environment Research Council
                Award ID: NE/M019691/1
                Funded by: Chinese Scholarship Council (CSC)
                Funded by: National Key Project of Intergovernmental Cooperation in International Scientific and Technological Innovation
                Award ID: 2018YFE0112400
                Funded by: EPSRC , doi 10.13039/501100000266;
                Funded by: BBSRC , doi 10.13039/501100000268;
                Award ID: BB/V011553/1
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                December 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.3 mode:remove_FC converted:09.01.2023

                bio‐energy,biomass production,genotype‐by‐environment interaction,genotype‐specific plant growth model,marginal land,switchfor model

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