DOE Bioenergy Technologies Office (BETO) 2023 Project Peer Review - Next-Generation Feedstocks for the Emerging Bioeconomy - April 4, 2023

Sep 15, 2026

DOE Bioenergy Technologies Office (BETO) 2023 Project Peer Review presents work on next-generation warm-season perennial feedstock systems (2019-2024) focused on productive switchgrass production on marginal croplands across the U.S. Midwest. The project targets field-scale high-yielding cultivars and links management choices to sustainability and bioeconomy outcomes, including ecosystem services such as greenhouse-gas emissions, nutrient leaching, evapotranspiration and biodiversity, supported by technoeconomic and machine-learning yield prediction.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages31

Reading Time1 h 18 min

AccessFree to download

High-level Project Goal

Project Framework and Objectives

Technical Approach and Metrics

Potential Challenges

Progress and Outcomes (Field-scale, FY 21-22)

Progress and Outcomes (Small-scale, FY 21-22)

Progress and Outcomes (Machine Learning, FY 21-22)

DOE Bioenergy Technologies Office (BETO) 2023 Project Peer Review Next-Generation Feedstocks for the Emerging Bioeconomy 60% of Completion (2019-2024) Date: April 4, 2023 Feedstock Technologies Program D.K. Lee University of Illinois at Urbana-Champaign High-level Project Goal Develop productive, cost-effective, and sustainable warm-season perennial bioenergy feedstock production systems on marginal croplands across geographic locations in the Midwest High-yielding bioenergy switchgrass On-farm field scale production on marginal Land Sustainable feedstock Production across geographic Biomass (dry ton ac-1) New cultivar Independence Liberty WS-10L Predecessor cultivar 'Independence' Kanlow Shawnee Sunburst regions in Midwest 21-acre field * 2-acre CRP Watertown, SD Mead, NE Ames, IA * **** Urbana, IL Edwardsville, IL 0.0 2.0 1st Growing season 4.0 6.0 8.0 2nd Growing season Context and project history: • Limited data availability on field-scale research with high-yielding switchgrass cultivars • Need to demonstrate ecosystem service benefits of energy-type switchgrass on marginal lands Project Framework Feedstock Sustainability Bioeconomy Objective 1&2 ▪ Potentials of high-yielding switchgrass at field scale ▪ Best Management Practices ▪ Harvest logistics ▪ Feedstock quality Objective 4 Ecosystem services (ES) ▪ CO2 , N2 O, CH4 emissions ▪ Nutrient leaching (N&P) ▪ Water quantity (ET) ▪ Biodiversity ▪ Soil quality (SOC, WAS, etc. ) Objective 5 ▪ Develop a regional feedstock cost-rate model for delivering switchgrass to biorefinery locations Plot-scale (100 ft2) to field-scale (1 acre) Objective 3 Harvest logistics Machine learning (ML) Input • Soil data • Weather data • Field management • Growth and development • Phenotypical data • ES measurements • GPS coordinates + Technoeconomic analysis Prediction Yield&ES 2 – Approach (Technical Metrics) M✓etr6icston:/ac biomass yield 2 – Approach (Technical metrics) Establishment ▪ Seed bed preparation/Planting ▪ Weed control Maintenance and harvest ▪ Fertilization/Weed control ▪ Sustainable biomass harvest Ecosystem service ▪ Water quality/quantity ▪ Soil health/C sequestration/GHG Liberty Switchgrass Iowa, Sept 2022 ▪ Biodiversity Field preparation Fertilization Vegetative growth Carthage switchgrass SD, Sept 2022 Low diversity mixture NE, Aug 2022 Independence Switchgrass IL, Urbana Sept 2022 Harvest Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Soil sensors with 3 depths for evapotranspiration (ET) Biodiversity measurements ▪ Avian acoustic monitoring (Left) ▪ Insects & pollinators (Middle, Right) Ecosystem service measurements 2 – Approach (potential challenges) Challenge 1: ▪ Establishment challenges on marginal lands (spring flooding) during the first year, delay weed control and fertilization Challenge 2: ▪ Cold winter in South Dakota during the third growing year causing stand damage, winter kill Challenge 3: ▪ Drought challenge in the third growing year in ILand NE impacted on productivity Challenge 3: ▪ Machine breakdown limits timely operations such as seeding, spraying, harvesting, and ultimately limits data collection points Spring flooding Winter damage Machine breakdown 4 – Progress and Outcomes (Field-scale, FY 21-22) Task 1: Management of field-scale switchgrass production system ▪ Comparing switchgrass and corn production system: Productivity, ecosystem services and biodiversity benefits ▪ Annual nitrogen application rates ▪ Switchgrass: 25 and 50 lbs N /acre ▪ Corn: 180 lbs N /acre Grain and Biomass yield of corn in 2022 | Site | Grain yield (ton/acre) | Total Biomass
(ton/acre) | | --- | --- | --- | | IL Urbana | 2.5 | 5.0 | | Nebraska | 2.3 | 4.6 | | South Dakota | 2.8 | 5.5 | Corn Switchgrass June 2022 Harvesting in Fall 2022

FAQs

What is the main goal of this BETO project?

Develop productive, cost-effective, sustainable warm-season perennial bioenergy feedstock production systems on marginal croplands across Midwest geographic locations.

Which ecosystem services and sustainability indicators are evaluated?

Assessments include CO2, N2O, CH4 emissions, nutrient leaching (N&P), water quantity via evapotranspiration (ET), biodiversity, and soil quality/soil carbon-related metrics.

How does the project use machine learning in FY 21-22?

It develops, validates, and publishes remote-sensing and machine-learning models to estimate biomass yield at harvest, plus biomass moisture and crude protein using a multi-year dataset.

Sep 15, 2026

Uploaded by Felix Montgomery