Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars-Reference-Cited by-同舟云学术

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Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars

Published:2019-03-18 Issue:8 Volume:11 Page:956-970
ISSN:1757-1693
Container-title:GCB Bioenergy
language:en
Short-container-title:GCB Bioenergy

Author:

Zhang Li¹^ORCID,Juenger Thomas E.¹,Lowry David B.²,Behrman Kathrine D.¹

Affiliation:

1. Department of Integrative Biology The University of Texas at Austin Austin Texas

2. Department of Plant Biology Michigan State University East Lansing Michigan

Funder

National Science Foundation

Office of Science

U.S. Department of Energy

Biological and Environmental Research

Publisher

Wiley

Subject

Waste Management and Disposal,Agronomy and Crop Science,Renewable Energy, Sustainability and the Environment,Forestry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcbb.12609

Reference67 articles.

1. Plant fitness in a rapidly changing world

2. Genotypic variation in traits linked to climate and aboveground productivity in a widespread C 4 grass: evidence for a functional trait syndrome

3. Examing plant physiological responses to calimte change through an evolutionary lens;Becklin K. M.;Plant Physiology,2016

4. Spatial forecasting of switchgrass productivity under current and future climate change scenarios

5. Spatial land use trade-offs for maintenance of biodiversity, biofuel, and agriculture

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1. Artificial Intelligence for Biomass Detection, Production and Energy Usage in Rural Areas: A review of Technologies and Applications;Sustainable Energy Technologies and Assessments;2023-12

2. Predicting Biomass Yields of Advanced Switchgrass Cultivars for Bioenergy and Ecosystem Services Using Machine Learning;Energies;2023-05-18

3. Local adaptation of switchgrass drives trait relations to yield and differential responses to climate and soil environments;GCB Bioenergy;2023-03-16

4. One hundred years into the study of ecotypes, new advances are being made through large-scale field experiments in perennial plant systems;Current Opinion in Plant Biology;2022-04

5. Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach;Frontiers in Earth Science;2021-12-20

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