Empirical Evidence for the Potential Climate Benefits of Decarbonizing Light Vehicle Transport in the U.S. with Bioenergy from Purpose-Grown Biomass with and without BECCS.

Climate mitigation scenarios limiting global temperature increases to 1.5 °C rely on decarbonizing vehicle transport with bioenergy production plus carbon capture and storage (BECCS), but climate impacts for producing different bioenergy feedstocks have not been directly compared experimentally or for ethanol vs electric light-duty vehicles. A field experiment at two Midwest U.S. sites on contrasting soils revealed that feedstock yields of seven potential bioenergy cropping systems varied substantially within sites but little between. Bioenergy produced per hectare reflected yields: miscanthus > poplar > switchgrass > native grasses ≈ maize stover (residue) > restored prairie ≈ early successional. Greenhouse gas emission intensities for ethanol vehicles ranged from 20 to -179 g CO2e MJ-1: maize stover ≫ miscanthus ≈ switchgrass ≈ native grasses ≈ poplar > early successional ≥ restored prairie; direct climate benefits ranged from ∼80% (stover) to 290% (restored prairie) reductions in CO2e compared to petroleum and were similar for electric vehicles. With carbon capture and storage (CCS), reductions in emission intensities ranged from 204% (stover) to 416% (restored prairie) for ethanol vehicles and from 329 to 558% for electric vehicles, declining 27 and 15%, respectively, once soil carbon equilibrates within several decades of establishment. Extrapolation based on expected U.S. transportation energy use suggests that, once CCS potential is maximized with CO2 pipeline infrastructure, negative emissions from bioenergy with CCS for light-duty electric vehicles could capture >900 Tg CO2e year-1 in the U.S. In the future, as other renewable electricity sources become more important, electricity production from biomass would offset less fossil fuel electricity, and the advantage of electric over ethanol vehicles would decrease proportionately.

Carbon-Negative Biofuel Production.

Achievement of the 1.5 °C limit for global temperature increase relies on the large-scale deployment of carbon dioxide removal (CDR) technologies. In this article, we explore two CDR technologies: soil carbon sequestration (SCS), and carbon capture and storage (CCS) integrated with cellulosic biofuel production. These CDR technologies are applied as part of decentralized biorefinery systems processing corn stover and unfertilized switchgrass grown in riparian zones in the Midwestern United States. Cover crops grown on corn-producing lands are chosen from the SCS approach, and biogenic CO2 in biorefineries is captured, transported by pipeline, and injected into saline aquifers. The decentralized biorefinery system using SCS, CCS, or both can produce carbon-negative cellulosic biofuels (≤-22.2 gCO2 MJ-1). Meanwhile, biofuel selling prices increase by 15-45% due to CDR costs. Economic incentives (e.g., cover crop incentives and/or a CO2 tax credit) can mitigate price increases caused by CDR technologies. A combination of different CDR technologies in decentralized biorefinery systems is the most efficient method for greenhouse gas (GHG) mitigation, and its total GHG mitigation potential in the Midwest is 0.16 GtCO2 year-1.

Determination of isoflavone (genistein and daidzein) concentration of soybean seed as affected by environment and management inputs.

BACKGROUND: Isoflavones, such as genistein and daidzein, are produced in soybean seed [Glycine max (L.) Merr.] and may be associated with health benefits in the human diet. More research is required to determine the effect of agronomic soybean treatments on isoflavone concentration. In this study from 2012 to 2014 at Michigan State University and Breckenridge locations, we have evaluated agronomic input management systems which are marketed to increase or protect potential soybean grain yield, including: nitrogen fertilization, herbicide-defoliant, foliar applied fertilizer, a biological-based foliar application, foliar applied fungicide, foliar applied insecticide, a seed applied fungicide, and a maximized seed treatment that included fungicide and insecticide as well as an inoculant and lipo-chitooligosaccharide nodulation promoter, for their effect on soybean seed genistein and daidzein concentrations. RESULTS: Paired comparisons were made between treatments receiving a designated management input and those without the input. Year and location had a significant effect on isoflavone concentrations. Agronomic management inputs impacted soybean seed daidzein concentrations in 15 of 48 field observations and genistein concentrations in 11 of 48 observations. CONCLUSION: The research supports findings that soybean seed isoflavone levels exhibit a location specific response, and the temporal variability experienced between years appears to influence changes in soybean isoflavone levels more than location. © 2016 Society of Chemical Industry.

A high solids field-to-fuel research pipeline to identify interactions between feedstocks and biofuel production.

BACKGROUND: Environmental factors, such as weather extremes, have the potential to cause adverse effects on plant biomass quality and quantity. Beyond adversely affecting feedstock yield and composition, which have been extensively studied, environmental factors can have detrimental effects on saccharification and fermentation processes in biofuel production. Only a few studies have evaluated the effect of these factors on biomass deconstruction into biofuel and resulting fuel yields. This field-to-fuel evaluation of various feedstocks requires rigorous coordination of pretreatment, enzymatic hydrolysis, and fermentation experiments. A large number of biomass samples, often in limited quantity, are needed to thoroughly understand the effect of environmental conditions on biofuel production. This requires greater processing and analytical throughput of industrially relevant, high solids loading hydrolysates for fermentation, and led to the need for a laboratory-scale high solids experimentation platform. RESULTS: A field-to-fuel platform was developed to provide sufficient volumes of high solids loading enzymatic hydrolysate for fermentation. AFEX pretreatment was conducted in custom pretreatment reactors, followed by high solids enzymatic hydrolysis. To accommodate enzymatic hydrolysis of multiple samples, roller bottles were used to overcome the bottlenecks of mixing and reduced sugar yields at high solids loading, while allowing greater sample throughput than possible in bioreactors. The roller bottle method provided 42-47% greater liquefaction compared to the batch shake flask method for the same solids loading. In fermentation experiments, hydrolysates from roller bottles were fermented more rapidly, with greater xylose consumption, but lower final ethanol yields and CO2 production than hydrolysates generated with shake flasks. The entire platform was tested and was able to replicate patterns of fermentation inhibition previously observed for experiments conducted in larger-scale reactors and bioreactors, showing divergent fermentation patterns for drought and normal year switchgrass hydrolysates. CONCLUSION: A pipeline of small-scale AFEX pretreatment and roller bottle enzymatic hydrolysis was able to provide adequate quantities of hydrolysate for respirometer fermentation experiments and was able to overcome hydrolysis bottlenecks at high solids loading by obtaining greater liquefaction compared to batch shake flask hydrolysis. Thus, the roller bottle method can be effectively utilized to compare divergent feedstocks and diverse process conditions.

The importance of dominance and genotype-by-environment interactions on grain yield variation in a large-scale public cooperative maize experiment.

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.

Maize genomes to fields (G2F): 2014-2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets.

OBJECTIVES: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017. DATA DESCRIPTION: Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

Assessing Variation in US Soybean Seed Composition (Protein and Oil).

Soybean [Glycine max (L.) Merr.] seed composition and yield are a function of genetics (G), environment (E), and management (M) practices, but contribution of each factor to seed composition and yield are not well understood. The goal of this synthesis-analysis was to identify the main effects of G, E, and M factors on seed composition (protein and oil concentration) and yield. The entire dataset (13,574 data points) consisted of 21 studies conducted across the United States (US) between 2002 and 2017 with varying treatments and all reporting seed yield and composition. Environment (E), defined as site-year, was the dominant factor accounting for more than 70% of the variation for both seed composition and yield. Of the crop management factors: (i) delayed planting date decreased oil concentration by 0.007 to 0.06% per delayed week (R 2∼0.70) and a 0.01 to 0.04 Mg ha-1 decline in seed yield per week, mainly in northern latitudes (40-45 N); (ii) crop rotation (corn-soybean) resulted in an overall positive impact for both seed composition and yield (1.60 Mg ha-1 positive yield difference relative to continuous soybean); and (iii) other management practices such as no-till, seed treatment, foliar nutrient application, and fungicide showed mixed results. Fertilizer N application in lower quantities (10-50 kg N ha-1) increased both oil and protein concentration, but seed yield was improved with rates above 100 kg N ha-1. At southern latitudes (30-35 N), trends of reduction in oil and increases in protein concentrations with later maturity groups (MG, from 3 to 7) was found. Continuing coordinated research is critical to advance our understanding of G × E × M interactions.

Cellulosic biofuel contributions to a sustainable energy future: Choices and outcomes.

Cellulosic crops are projected to provide a large fraction of transportation energy needs by mid-century. However, the anticipated land requirements are substantial, which creates a potential for environmental harm if trade-offs are not sufficiently well understood to create appropriately prescriptive policy. Recent empirical findings show that cellulosic bioenergy concerns related to climate mitigation, biodiversity, reactive nitrogen loss, and crop water use can be addressed with appropriate crop, placement, and management choices. In particular, growing native perennial species on marginal lands not currently farmed provides substantial potential for climate mitigation and other benefits.

Enzymatic digestibility and ethanol fermentability of AFEX-treated starch-rich lignocellulosics such as corn silage and whole corn plant.

BACKGROUND: Corn grain is an important renewable source for bioethanol production in the USA. Corn ethanol is currently produced by steam liquefaction of starch-rich grains followed by enzymatic saccharification and fermentation. Corn stover (the non-grain parts of the plant) is a potential feedstock to produce cellulosic ethanol in second-generation biorefineries. At present, corn grain is harvested by removing the grain from the living plant while leaving the stover behind on the field. Alternatively, whole corn plants can be harvested to cohydrolyze both starch and cellulose after a suitable thermochemical pretreatment to produce fermentable monomeric sugars. In this study, we used physiologically immature corn silage (CS) and matured whole corn plants (WCP) as feedstocks to produce ethanol using ammonia fiber expansion (AFEX) pretreatment followed by enzymatic hydrolysis (at low enzyme loadings) and cofermentation (for both glucose and xylose) using a cellulase-amylase-based cocktail and a recombinant Saccharomyces cerevisiae 424A (LNH-ST) strain, respectively. The effect on hydrolysis yields of AFEX pretreatment conditions and a starch/cellulose-degrading enzyme addition sequence for both substrates was also studied. RESULTS: AFEX-pretreated starch-rich substrates (for example, corn grain, soluble starch) had a 1.5-3-fold higher enzymatic hydrolysis yield compared with the untreated substrates. Sequential addition of cellulases after hydrolysis of starch within WCP resulted in 15-20% higher hydrolysis yield compared with simultaneous addition of hydrolytic enzymes. AFEX-pretreated CS gave 70% glucan conversion after 72 h of hydrolysis for 6% glucan loading (at 8 mg total enzyme loading per gram glucan). Microbial inoculation of CS before ensilation yielded a 10-15% lower glucose hydrolysis yield for the pretreated substrate, due to loss in starch content. Ethanol fermentation of AFEX-treated (at 6% w/w glucan loading) CS hydrolyzate (resulting in 28 g/L ethanol at 93% metabolic yield) and WCP (resulting in 30 g/L ethanol at 89% metabolic yield) is reported in this work. CONCLUSIONS: The current results indicate the feasibility of co-utilization of whole plants (that is, starchy grains plus cellulosic residues) using an ammonia-based (AFEX) pretreatment to increase bioethanol yield and reduce overall production cost.