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An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring
Unmanned aerial system (UAS)-based remote sensing can provide high spatial- and temporal-resolution crop monitoring for precision management. Existing crop monitoring UAS primarily use conventional techniques such as multi-spectral broadband vegetation indices (VIs) to track canopy structure/biomass. Recently developed lightweight hyperspectral sensors can track crop physiology and performance via complementary signals such as solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) that can be derived from hyperspectral reflectance. However, few existing UAS can acquire high-quality SIF and hyperspectral reflectance. Here, we designed a novel UAS that simultaneously captures far-red SIF and hyperspectral reflectance, using a single bifurcated fiber and motorized arm to measure downwelling and upwelling irradiance. The UAS was tested over (1) a heterogeneous corn field with spatially varying crop yield potential and (2) a set of soybean and corn plots under differing nutrient treatments. Our UAS can maintain stability under low-to-moderate winds (2–3 m/s) with <0.4 m geolocation accuracy, <0.1 m altitude drift, and <1.5° error of the fiber optic from nadir position during scanning. Weekly seasonal campaigns reveal that SIF outperforms conventional VIs such as the normalized difference vegetation index (NDVI) for distinguishing plots with different crop yield potential, especially after canopy closure when NDVI tends to saturate. The UAS can capture the diurnal dynamics of SIF and PRI for both corn and soybean. At the seasonal scale, SIF acquired from the UAS correlates well with that from a fixed SIF tower system ( R 2 = 0.81), which measured the same target albeit with different footprints, demonstrating the capability of UAS in characterizing the seasonal progression of crop activity. In conclusion, our newly developed UAS provides high-quality SIF and hyperspectral reflectance, facilitating mechanistic understanding of the physiological control on photosynthesis dynamics. Our findings also imply that this UAS could enable extension of fixed tower-based systems to monitor multiple targets from diurnal to seasonal scales and improve monitoring of heterogeneous fields.
Can upscaling ground nadir SIF to eddy covariance footprint improve the relationship between SIF and GPP in croplands?
Ground solar-induced chlorophyll fluorescence (SIF) is important for the mechanistic understanding of the dynamics of vegetation gross primary production (GPP) at fine spatiotemporal scales. However, eddy covariance (EC) observations generally cover larger footprint areas than ground SIF observations (a bare fiber with nadir), and this footprint mismatch between nadir SIF and GPP could complicate the canopy SIF-GPP relationships. Here, we upscaled nadir SIF observations to EC footprint and investigated the change in SIF-GPP relationships after the upscaling in cropland. We included 13 site-years data in our study, with seven site-years corn, four site-years soybeans, and two site-years miscanthus, all located in the US Corn Belt. All sites’ crop nadir SIF observations collected from the automated FluoSpec2 system (a hemispheric-nadir system) were upscaled to the GPP footprint-based SIF using vegetation indices (VIs) calculated from high spatiotemporal satellite reflectance data. We found that SIF-GPP relationships were not substantially changed after upscaling nadir SIF to GPP footprint at our crop sites planted with corn, soybean, and miscanthus, with R 2 change after the upscaling ranging from -0.007 to 0.051 and root mean square error (RMSE) difference from -0.658 to 0.095 umol m –2 s –1 relative to original nadir SIF-GPP relationships across all the site-years. The variation of the SIF-GPP relationship within each species across different site-years was similar between the original nadir SIF and upscaled SIF. Different VIs, EC footprint models, and satellite data led to marginal differences in the SIF-GPP relationships when upscaling nadir SIF to EC footprint. Furthermore, our study provided a methodological framework to correct this spatial mismatch between ground nadir SIF and GPP observations for croplands and potentially for other ecosystems. Our results also demonstrated that the spatial mismatch between ground nadir SIF and GPP might not significantly affect the SIF-GPP relationship in cropland that are largely homogeneous.
Evapotranspiration of advanced perennial bioenergy grasses produced on marginal land in the U.S. Midwest
The production of dedicated energy crops for biofuel and co-products can help develop a sustainable and viable bioeconomy under a changing climate. The co-production of perennial bioenergy and commodity crops in an agricultural landscape has the potential to reduce greenhouse gas emissions and provide numerous ecosystem services. However, as production of advanced, higher-yielding cultivars occurs, their impact on water resources needs to be considered. Estimates of evapotranspiration (ET) of perennial grasses compared to commodity crops are not always consistent in the literature. In this study, ET was estimated using an energy-balance model with Landsat satellite imagery and ground-based weather data to compare the large-scale production of advanced switchgrass cultivars (‘Independence’, ‘Liberty’, and ‘Carthage’), predecessor cultivars (‘Shawnee’ and ‘Sunburst’), and other perennial grasses (big bluestem and a low-diversity mixture) to corn grown continuously on marginal soils in the U.S. Midwest. Results showed significant differences in ET between corn and perennial grass treatments at four of the five field sites. However, differences between crop treatments were not consistent across sites, nor were the differences between advanced and predecessor switchgrass varieties. Production year played a large role in daily and cumulative ET across all sites. Differences in crop biomass yield between establishment and post-establishment years may contribute to these interannual differences. Site and interannual variations in precipitation and temperature may also be major contributing factors. Overall, the results of this study indicate that differences in ET between perennial bioenergy grasses and corn are likely dependent upon location of production and weather conditions.
Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China
Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.
Quantifying cover crop effects on soil health and productivity
The dataset presented here supports the research paper entitled “A calculator to quantify cover crop effects on soil health and productivity”. Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters – erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity – to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.
Automatic Responses of Crop Stocks and Policies Buffer Climate Change Effects on Crop Markets and Price Volatility
Climate change has the potential to affect crop prices and price volatility. However, the economic models used in prior assessments largely do not include known, automatic, stabilizing factors. Crop storage can stabilize prices and U.S. crop policy tends to provide support that moves opposite prices. We quantify effects of circa 2050 climate forcing on the inter-annual variability of U.S. Corn Belt corn and soybean yields using statistical crop models and climate scenarios from regional and global climate models. Climate change generally reduces mean yields and increases the inter-annual variability of yields in the Midwestern U.S. Using these yield impacts and an economic model with automatic market stabilizers, we find only modest increases in price volatility. Although individual producers and states are negatively affected by the yield reductions, the aggregate effect for all corn and soybean producer returns can be positive because of price increases. Moreover, agricultural policies based on price levels or revenue variation offset some of the impacts of market variation on farm income. Our results differ from other recent results and temper concerns that increasing climate instability necessarily translates to greater uncertainty about agricultural commodity uses, including as food and biofuels, in the near future.
Application of air classification and formulation to manage feedstock cost, quality and availability for bioenergy
Biomass such as agricultural residues, energy crops and yard waste has significant potential to be used as renewable feedstocks for production of fuels, chemicals and energy. However, in a given location, biomass availability, cost and quality can vary markedly. Strategies to manage these traits must be identified and implemented so that consistent low-cost and high-quality feedstocks can be delivered to biorefineries year round. In this study, we examine air classification as a method to mitigate high ash concentrations in corn stover, switchgrass, and grass clippings. Formulation techniques were then used to produce blends that met ash quality and biomass quantity specifications at the lowest possible cost for biopower and biochemical conversion applications. It was found that air classification can separate the biomass into light fractions which contain concentrated amounts of elemental ash components introduced through soil contamination such as sodium, alumina, silica, iron and titania; and heavy fractions that are depleted in these components and have relatively lower total ash content. Light fractions of corn stover and grass clippings were found to be suitable for combustion applications since they had less propensity to slag than the whole biomass material. The remaining heavy fractions of corn stover or grass clippings could then be blended with switchgrass to produce blends that met the 5% total ash specifications suggested for biochemical conversions. However, ternary blends of the three feedstocks were not possible due to the high ash content of grass clippings. Lastly, it was determined that air classification by itself was not suitable to prepare these feedstocks for pyrolysis due to high ash content.
Life Cycle Analysis of Renewable Natural Gas and Lactic Acid Production from Waste Feedstocks
Producing fuels and chemicals from waste is considered economically favorable, due to low feedstock cost, and environmentally favorable, due to avoided emissions from conventional waste management practices. In this study, we evaluate the life cycle greenhouse gas (GHG) emission reduction benefits of renewable natural gas (RNG) and lactic acid (LA) production from four types of wet waste feedstocks (wastewater sludge, food waste, swine manure, and fats, oil, and grease [FOG]) via anaerobic digestion (AD) and LA fermentation, respectively. RNG can be used as an alternative to fossil natural gas, while LA from waste feedstocks can displace conventional LA production pathways (mainly from corn via fermentation). Providing comprehensive life cycle GHG emissions of the combinations of waste feedstocks and products through different routes helps identify the GHG hotspots and show where emissions savings come from. The results show that the carbon intensities (CIs) of waste-derived RNG and LA are much lower than those of their counterparts. We estimated the life cycle GHG emissions for RNG to be between -146 and 27 g carbon dioxide equivalent (CO2e)/MJ, much lower than the CI of fossil fuels. Waste-derived LA pathways also show substantially lower CIs, ranging from -4.2 to -1.4 kgCO2e/kg LA, compared to the CIs of LA from corn and corn stover (1.2 and 0.3 kgCO2e/kg LA, respectively). We will also discuss that the low CIs of waste-derived products can come from low yields leading to high emission credits. Thus, life cycle analysis results presented per weight of treated waste can be used to support decisions about which waste feedstocks and products are to be used for sustainable waste valorization. In addition, we found that monetary emission reduction credits can play an important role in driving waste valorization.
Evaluating the sustainability of the 2017 US biofuel industry with an integrated techno-economic analysis and life cycle assessment
The United States produced more than 66.2 billion Liters of biofuel, primarily in the form of corn ethanol (61 billion Liters) and soybean biodiesel (6 billion Liters), for the transportation industry in 2017. No work currently exists that evaluates both the economic and environmental outcomes of this industry with adequate geospatial resolution and national scope. In this study, a model framework is constructed to perform Techno-Economic Analysis and Life Cycle Assessment using high-resolution input datasets to provide a granular estimation of corn ethanol and soybean biodiesel sustainability performance in most counties in the United States in 2017 (the most recent year for which data is available). Results show a total life cycle, greenhouse gas emission volume of 99.5 million Mg CO 2-eq produced in 2017 by these two biofuels (94.8 million Mg from corn ethanol, and 4.7 million Mg from soybean biodiesel), excluding indirect land use change emissions. Further, this volume corresponds to a combined carbon intensity of 65.3 gCO 2-eq /MJ, which is a greenhouse gas improvement compared to petroleum-based gasoline (the carbon intensity of conventional gasoline is 93.0 gCO 2-eq /MJ). However, these biofuels are produced at an additional economic cost ($1.8 billion over the displaced gas/diesel). Additionally, these biofuels generate unfavorable impacts in other environmental categories when compared to petroleum-based fuels, particularly in areas of water, land, and nitrogen intensity. This work enables stakeholders to assess the specific value of biofuels as a means of emission reduction and determine if the attained improvements are worth the associated opportunity costs.
Impact of biomass ash content on biocomposite properties
Owing to its low cost and sustainable nature, lignocellulosic biomass has been utilized for reinforcing polymers, but it is crucial to understand the impact of high-ash concentrations in biomass on composite strength and processing. Biomass is not only desirable for biofuel production but could also have a strong market, if high-ash biomass is acceptable, for biocomposites. In this work, natural fibers (switchgrass and corn stover) were used to reinforce polylactic acid (PLA) to produce biocomposites. Natural fibers were pretreated to obtain fibers that contain different percentages of ash. The mechanical properties (such as Young's modulus, tensile strength, failure strain, storage modulus) of corn stover/PLA composites remained largely unaffected by the ash concentration of the biomass fibers, despite the large range of ash contents (2.2–11.9 wt%). Furthermore, the tensile strengths of switchgrass/PLA composites were slightly negatively affected by the ash concentration of the switchgrass fibers (0.7–2.1 wt%). Both the switchgrass/PLA and the corn stover/PLA composites exhibited a high-enough tensile strength (49–57 MPa) and suitable complex viscosity (2.0–7.0 kPa·s at the frequency of 3.2 rad/s). They are expected to be 3D-printable through an extrusion-based additive manufacturing process.
Production of Furfural from Process-Relevant Biomass-Derived Pentoses in a Biphasic Reaction System
Furfural is an important fuel precursor which can be converted to hydrocarbon fuels and fuel intermediates. In this work, the production of furfural by dehydration of process-relevant pentose rich corn stover hydrolyzate using a biphasic batch reaction system has been investigated. Methyl isobutyl ketone (MIBK) and toluene have been used to extract furfural and enhance overall furfural yield by limiting its degradation to humins. The effects of reaction time, temperature, and acid concentration (H 2 SO 4 ) on pentose conversion and furfural yield were investigated. For the dehydration of 8 wt % pentose-rich corn stover hydrolyzate under optimum reaction conditions, 0.05 M H 2 SO 4 , 170 degrees C for 20 min with MIBK as the solvent, complete conversion of xylose (98-100%) and a furfural yield of 80% were obtained. Under these same conditions, except with toluene as the solvent, the furfural yield was 77%. Additionally, dehydration of process-relevant pentose rich corn stover hydrolyzate using solid acid ion-exchange resins under optimum reaction conditions has shown that Purolite CT275 is as effective as H 2 SO 4 for obtaining furfural yields approaching 80% using a biphasic batch reaction system. In conclusion, this work has demonstrated that a biphasic reaction system can be used to process biomass-derived pentose rich sugar hydrolyzates to furfural in yields approaching 80%.
Enhancing Enzyme-Mediated Hydrolysis of Mechanical Pulps by Deacetylation and Delignification
Alkaline induced deacetylation of the hemicellulose combined with subsequent mechanical refining enhanced the enzyme-mediated hydrolysis of pretreated corn stover. The addition of either NaOH (80 °C) or mild KOH (25 °C) to corn stover prior to mechanical refining led to greater than 80% deacetylation with the NaOH treatment also solubilizing low-molecular-weight lignin that was enriched in $β$-O-4 linkages with more than 25% and 13% of the total and surface lignin removed, respectively. Furthermore, the influence of deacetylation and delignification were further enhanced when NaOH was supplemented with 3% Na 2 SO 3 , resulting in 100% deacetylation, 34% delignification, and a >20% increase in the hydrolysis yield of the substrate xylan. A milder KOH treatment resulted in the retention of more than 95% of the lignin within the cellulose rich, water-insoluble fraction with no apparent change in the surface lignin. However, both methods resulted in enhanced xylan hydrolysis when treated with xylanases, suggesting that deacetylation had enhanced accessibility to the xylan present in the pretreated of corn stover. It was apparent that cellulose accessibility was also enhanced by partial delignification, as NaOH treatment resulted in a 65% and 43% increase in the Water Retention Value and Directed Orange dye adsorption, respectively.
Tall Tower Ammonia Observations and Emission Estimates in the U.S. Midwest
Abstract Atmospheric ammonia (NH 3 ) has increased dramatically as a consequence of the production of synthetic nitrogen (N) fertilizer and proliferation of intensive livestock systems. It is a chemical of environmental concern as it readily reacts with atmospheric acids to produce fine particulate matter and indirectly contributes to nitrous oxide (N 2 O) emissions. Here, we present the first tall tower observations of NH 3 within the U.S. Corn Belt for the period April 2017 through December 2018. Hourly average NH 3 mixing ratios were measured at 100 and 56 m above the ground surface and fluxes were estimated using a modified gradient approach. The highest NH 3 mixing ratios (>30 nmol mol −1 ) occurred during early spring and late fall, coinciding with the timing of fertilizer application within the region and the occurrence of warm air temperatures. Net ecosystem NH 3 exchange was greatest in spring and fall with peak emissions of about +50 nmol m −2 s −l . Annual NH 3 emissions estimated using state‐of‐the‐art inventories ranged from 0.6 to 1.4 × the mean annual gross tall tower fluxes (+2.1 nmol m −2 s −1 ). If the tall tower observations are representative of the Upper Midwest and broader U.S. Corn Belt regions, the annual gross emissions were +720 Gg NH 3 ‐N y −1 and +1,340 Gg NH 3 ‐N y −1 , respectively. Finally, considering the N 2 O budget over the same region, we estimated total reactive N emissions (i.e., N 2 O + NH 3 ) of approximately 1,790 Gg N y −1 from the U.S. Corn Belt, representing ~23% of the current annual new N input.
Assessing the Impacts of Recent Crop Expansion on Water Quality in the Missouri River Basin Using the Soil and Water Assessment Tool
The Missouri River Basin (MORB) has experienced a resurgence of grassland conversion to crop production, which raised concerns on water quality. We applied the Soil and Water Assessment Tool (SWAT) to address how this conversion would impact water quality. We designed three crop production scenarios representing conversion of grassland to: (a) continuous corn; (b) corn/soybean rotation; and (c) corn/wheat rotation to assess the impact. The SWAT model results showed: (a) the lower MORB produced high total nitrogen (TN) and total phosphorus (TP) load before conversion (baseline) due mainly to high precipitation and high agricultural activity; (b) the greatest percentage increases of TN and TP occurred in the North and South Dakotas, coinciding with the highest amount of grassland conversion to cropland; and (c) grassland conversion to continuous corn resulted in the greatest increase in TN and TP loads, followed by conversion to corn/soybean and then conversion to corn/wheat. Although the greatest percentage increases of TN and TP occurred in the North and South Dakotas, these areas still contributed relatively low TN and TP to total basin loads after conversion. However, watersheds, predominantly in the lower MORB continued to be “hotspots” that contributed the greatest amounts of TN and TP to the total basin loads—driven by a combination of grassland conversion, high precipitation, and loading from pre-existing cropland. At the watershed outlet, the TN and TP loads were increased by 6.4% (13,800 t/yr) and 8.7% (3,400 t/yr), respectively, during the 2008–2016 period for the conversion to continuous corn scenario.
Impact of vegetation physiology and phenology on watershed hydrology in a semiarid watershed in the Pacific Northwest in a changing climate
Concurrent with changes in climate conditions, increases in atmospheric composition and transport can affect land surface processes by regulating physiological and phenological responses of plants, and consequently perturb water, carbon, and nitrogen (N) dynamics at multiple scales. Howerver, the relationships bwtween plants physiological and phenological and land surface processes in a changing climate are less well known due to the limitation of representing palnts properties in traditional hydrological models. In this study, we use the Community Land Model version 5 (CLM5) to investigate how projected changes in large scale atmospheric conditions can affect hydrologic and biogeochemical dynamics in the Upper Columbia-Priest Rapids (UCPR) watershed, a typical semi-arid watershed located in the north-western United States dominated by croplands. Six numerical experiments considering climate change, CO2 concentration, and N deposition consistent with the Representative Concentration Pathways (RCPs) 4.5 and 8.5 are performed at 1-km resolution over the period of 2015-2099. Our results show that, compared with historical results (1985-2014), the elevated CO2 directly increases plants N uptake rates that provide additional leaf N to enhance photosynthesis by the end of 21st century (2070-2099). The higher GPP leads to changes in stomatal resistance and increased leaf area index (LAI) that affect evaporatranspiration (ET) and its components. As a result of stomatal responses to a higher CO2 concentration, ET over corn fields declines by 24.6 mm yr-1 under RCP4.5, and by 64.0 mm yr-1 under RCP8.5, respectively by the end of the century from its historical mean of 428 mm yr-1. Meanwhile, ET over soybean fields increases by 27.7 mm yr-1 under RCP4.5 and 9.98 mm yr-1 under RCP8.5 from its historical mean of 507 mm yr-1 as a result of CO2 fertilization as soybeans are able to uptake more N to increase LAI significantly. Furtherfore, the changes in physiological and phenological in corn and soybean can strongly modulate water budget terms over the watershed in response to expected changes in greenhouse gas concentrations and atmospheric composition. Additionally, increases in CO2 concentration and N deposition are beneficial for improving water use efficiency of corn and soybean, therefore lead to less water consumption per unit gram of carbon produced from these crops. Our study elucidates the need to jointly consider effects of surface climate and atmospheric composition and transport in understanding and predicting watershed hydrologic and biogeochemical responses, especially for an agricultural watershed.
Crop yield response to climate change varies with crop spatial distribution pattern
The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40% by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.