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Defect-Accommodating Intermediates Yield Selective Low-Temperature Synthesis of YMnO3 Polymorphs
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Nitrogen fertilization effects on aged Miscanthus × giganteus stands: Exploring biomass yield, yield components, and biomass prediction using in–season morphological traits
For sustainable biomass production of Miscanthus × giganteus (hereafter miscanthus), understanding the impact of stand age and nitrogen (N) fertilization on biomass yield is crucial. This study investigated the effects of varying N fertilization rates (0, 56, 112, and 168 kg N ha –1 ) on yield components (tiller height, density, and weight) and their correlations with end-of-season biomass yield in miscanthus. We also explored end-of-season biomass yield prediction using in-season traits (canopy height, leaf area index, and leaf chlorophyll content [LCC]). The study was conducted at two sites in Illinois: a previously unfertilized 10-year-old miscanthus research stand at Urbana and a 16-year-old commercial stand at Pesotum with a history of annual 56N application. Results from 2018 to 2021 in Urbana and 2020 to 2021 in Pesotum showed increased biomass yields with N fertilization, varying by rate, year, and location. Biomass yield in Pesotum peaked at 56N, while in Urbana, it increased significantly at 112 kg N ha –1 . Biomass yield was strongly correlated with tiller height and weight measured at Urbana across N rates. Morphological traits measured every 2–3 weeks during the 2020 and 2021 growing seasons showed that canopy height was the strongest single predictor of miscanthus biomass yield, followed by LCC. Mid-August to September measurements of these traits were the best predictors of biomass yield. Multiple regressions involving the canopy height and LCC further improved yield predictions. We conclude that while N enhances biomass yields of aging miscanthus, the optimum rate depends on the site, environmental conditions, and management history.
Data from: Biomass yield, yield components and growing season phenotypic measurements of Miscanthus
For sustainable biomass production of Miscanthus × giganteus (hereafter miscanthus), understanding the impact of stand age and nitrogen (N) fertilization on biomass yield is crucial. This study investigated the effects of varying N fertilization rates (0, 56, 112, and 168 kg N ha-1) on yield components (tiller height, density, and weight) and their correlations with end-of-season biomass yield in miscanthus. We also explored end-of-season biomass yield prediction using in-season traits (canopy height, leaf area index (LAI), and leaf chlorophyll content (LCC)). The study was conducted at two sites in Illinois: a previously unfertilized 10-year-old miscanthus research stand at Urbana and a 16-year-old commercial stand at Pesotum with a history of annual 56N application. Results from 2018-2021 in Urbana and 2020-2021 in Pesotum showed increased biomass yields with N fertilization, varying by rate, year, and location. Biomass yield in Pesotum peaked at 56N, while in Urbana, it increased significantly at 112 kg N ha-1. Biomass yield was strongly correlated with tiller height and weight measured at Urbana across N rates. Morphological traits measured every 2-3 weeks during the 2020 and 2021 growing seasons showed that canopy height was the strongest single predictor of miscanthus biomass yield, followed by LCC. Mid-August to September measurements of these traits were the best predictors of biomass yield. Multiple regressions involving the canopy height and LCC further improved yield predictions. We conclude that while N enhances biomass yields of aging miscanthus, the optimum rate depends on the site, environmental conditions, and management.
Maximization of carbon nanotube yield by solid carbon-assisted dewetting of iron catalyst films
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Rheology of enzyme liquefied corn stover slurries: The effect of solids concentration on yielding and flow behavior
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Woody bioenergy crop selection can have large effects on water yield: A southeastern United States case study
Short-rotation woody crops in the southeastern United States will make a significant contribution to the growing renewable energy supply over the 21st century; however, there are few studies that investigate how species selection may affect water yield. Here we assessed the impact of species selection on annual and seasonal water budgets in unvegetated plots and late-rotation 14–15-year-old intensively managed loblolly pine (Pinus taeda L.) and sweetgum (Liquidambar styraciflua L.) stands in South Carolina USA. We found that while annual aboveground net primary productivity and bioenergy produced was similar between species, sweetgum transpiration was 53% higher than loblolly pine annually and 92% greater during the growing season. Canopy interception was 10.5% of annual precipitation and was not significantly different between the two species. Soil evaporation was less than 1.3% of annual precipitation and did not differ between species, but was 26% of precipitation in unvegetated plots. Annual water yield was 69% lower for sweetgum than loblolly pine, with water yield to precipitation ratios of 0.13 and 0.39 for sweetgum and loblolly pine, respectively. If planted at a large scale, the high transpiration and low water yield in sweetgum could result in declines in downstream water availability relative to loblolly pine by the end of the growing season when storage in groundwater, streams, and water supply reservoirs are typically at their lowest. Our results suggest that species selection is of critical importance when establishing forest plantations for woody bioenergy production due to potential impacts on downstream water yield.
Improved Cumulative Fission Yield Measurements with Fission Spectrum Neutrons on 235 U
Two isotopically-characterized targets of high-purity (99.84±0.03%) 235 U-oxide and a neutron dosimetry package were exposed to a pulsed neutron irradiation using the Godiva critical assembly at the National Criticality Experiments Research Center. Following irradiation, the fissioned targets were counted with a broad-energy germanium detector. Estimates of the total fissions for each target were made using measurements of well-known fission products. The total fission values were then used to measure the fission yields of 21 fission products with half-lives between 636 and 119,700 seconds. Mean values of seventeen of the measured fission products fell within the 95% confidence level of the Evaluated Nuclear Data Files VII.1/b (ENDF/B-VII.1) using the larger of the two uncertainties: 84g Br, 89 Rb, 91 Sr, 93 Y, 97 Zr, 101 Mo, 105 Ru, 128 Sn, 129 Sb, 130g Sb, 131 Sb, 131m Te, 133 I, 135 I, 141 Ba, 142 Ba, and 142 La. Seven isotopes were measured to better precision than is listed in the ENDF/B-VII.1 database: 89 Rb, 93 Y, 128 Sn, 129 Sb, 130g Sb, 131m Te, and 133 I. Four of the measured isotopes were found to be statistically different from the ENDF/B-VII.1 database: 94 Y, 134 Te, 134 I, and 138 Xe. Two of the isotopic analyses conducted in this paper fit the parent and daughter data simultaneously. The parent-daughter pairs measured in this way were the 134 Te/I and 142 Ba/La pairs. The fission yield results obtained in this way are unique, especially for 134 I, because the parent and daughter half-lives are so close. Here, given the limited number of direct measurements of the 134 Te/I pair from fast neutron induced fission and the seemingly high estimate for 134 Te from previous work, it is likely that the value in this paper is more accurate; however, additional measurements of this pair are needed to validate this assertion.
Stochastically estimated covariance matrices for independent and cumulative fission yields in the ENDF/B-VIII.0 and JEFF-3.3 evaluations
A Monte-Carlo method for the generation of correlation and covariance matrices for independent and cumulative fission yields has been developed. The method uses a constrained Monte-Carlo resampling structure in order to vary evaluated fission yield libraries in a way that meets basic conservation principles. This results in the generation of correlation/covariance matrices with limited model bias and uncertainty; the matrices are primarily reflective of the evaluated fission yield uncertainties and correlations that arise from the evaluation process. This method has been applied to generate correlation and covariance matrices for all of the fissioning systems of the ENDF/B-VIII.0 and JEFF-3.3 evaluations, marking the first time such matrices have been generated for all of these systems. These covariance matrices have been published online for immediate public use. These correlation and covariance matrices can be used to improve uncertainty estimation in calculations of reactor antineutrino emission rates, decay heat problems, and nuclear forensics.
Genome‐wide association study of multiple yield traits in a diversity panel of polyploid sugarcane ( Saccharum spp.)
Abstract Sugarcane ( Saccharum spp.) is an important economic crop, contributing up to 80% of sugar and approximately 60% of biofuel globally. To meet the increased demand for sugar and biofuel supplies, it is critical to breed sugarcane cultivars with robust performance in yield traits. Therefore, dissection of causal DNA sequence variants is of great importance, as it provides genetic resources and fundamental information for crop improvement. In this study, we analyzed nine yield traits in a sugarcane diversity panel consisting of 308 accessions primarily selected from the World Collection of Sugarcane and Related Grasses. By genotyping the diversity panel via target enrichment sequencing, we identified a large number of sequence variants. Genome‐wide association studies between the markers and traits were conducted, taking dosages and gene actions into consideration. In total, 217 nonredundant markers and 225 candidate genes were identified to be significantly associated with the yield traits, which can serve as a comprehensive genetic resource database for future gene identification, characterization, and selection for sugarcane improvement. We further investigated runs of homozygosity (ROH) in the sugarcane diversity panel. We characterized 282 ROHs and found that the occurrence of ROHs in the genome were nonrandom and probably under selection. The ROHs were associated with total weight and dry weight, and high ROHs resulted in a decrease in the two traits. This study suggests that genomic inbreeding has led to negative impacts on sugarcane yield.
Data for High Yield Production of 3-Hydroxypropionic Acid Using Issatchenkia orientalis
Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.
Low energy light yield of fast plastic scintillators
Compact neutron imagers using double-scatter kinematic reconstruction are being designed for localization and characterization of special nuclear material. These neutron imaging systems rely on scintillators with a rapid prompt temporal response as the detection medium. As n-p elastic scattering is the primary mechanism for light generation by fast neutron interactions in organic scintillators, proton light yield data are needed for accurate assessment of scintillator performance. The proton light yield of a series of commercial fast plastic organic scintillators—EJ-200, EJ-204, and EJ-208—was measured via a double time-of-flight technique at the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory. Using a tunable deuteron breakup neutron source, target scintillators housed in a dual photomultiplier tube configuration, and an array of pulse-shape- discriminating observation scintillators, the fast plastic scintillator light yield was measured over a broad and continuous energy range down to proton recoil energies of approximately 50 keV. Furthermore, this work provides key input to event reconstruction algorithms required for utilization of these materials in emerging neutron imaging modalities.
The Importance of Vane Configuration on Yield Stress Measurements of Cement Slurry
Vane methods combined with direct shear tests are widely applied to measure the yield stress $τ_0$ in concentrated suspensions such as cement slurries. This report reviews three different vanes with different shapes and sizes, and examines the relationship between the yield stress versus the torque and the shear rate versus the angular velocity. This research shows that vanes with conical shapes or reduced height/diameter ratio $(H/D)$ result in larger yield stress values.
Imitating the “breeder's eye”: Predicting grain yield from measurements of non‐yield traits
Abstract Plant breeding relies on information gathered from field trials to select promising new crop varieties for release to farmers and to develop genomic prediction models that can enhance the efficiency of genetic improvement in future breeding cycles. However, generating the genetic marker data required to apply genomic prediction at the early stages of a breeding program remains costly for many public‐sector breeding programs as well as for many plant breeders operating in developing countries. As the pace of climate change intensifies, the time lag of developing and deploying new crop varieties requires plant breeders to make selection decisions without knowing the future environments those crop varieties will encounter in farmers’ fields. Therefore, both lower cost and higher accuracy methods for prediction of crop performance are essential for creating and maintaining resilient agricultural systems in the latter half of the 21 st century. To address this challenge, we conducted linked yield trials of 752 public maize ( Zea mays ) genotypes in two distinct environments. We developed and trained a phenotypic prediction model to predict yield from manually scored plant traits. The phenotypic prediction approach we employed outperformed genomic prediction in predicting yields in a second environment, with 8.7%–63% higher R 2 and 4%–13% less root mean square error than the genomic prediction. The phenotypic prediction has the potential to be applied to a wider range of breeding programs, including those that lack the resources to genotype large populations, such as programs in the developing world, breeding programs for specialty crops, and public sector programs.
Yield and Emplacement Depth Effects on Acoustic Signals from Buried Explosions in Hard Rock
Subterranean energy releases such as explosions and earthquakes may disturb the Earth-atmosphere interface, creating acoustic waves that can travel great distances. These waves provide a record of the ground motion directly above the event. The information they encode may provide critical insight into the depth and size of underground explosions, the sequence of events immediately before volcanic eruptions, and the magnitude of strong motion resulting from earthquakes. However, the effect of event size and burial depth on the resulting acoustic wave has not been explored in detail. The relationship between acoustic amplitude, frequency, and energy is investigated for a series of well-characterized underground chemical explosions in granite. Acoustic amplitude was found to vary linearly with explosive yield divided by emplacement depth. Peak acoustic frequency appears to be a function of explosive yield alone. The ratio of radiated acoustic energy to source energy had a relatively poor fit to yield, depth, and combinations thereof. These relationships suggest that acoustic analysis can be used to determine the size and depth of a buried explosion. The results presented here have particular relevance to the nuclear monitoring community, because depth is difficult to determine with seismic methods.
BLUP and mean yields of selected top 25 high yielding half-sib families
BLUP and mean yields of selected top 25 high yielding half-sib families. The yield BLUP were estimated using mixed linear models. The family column indicates the families with progeny column showing the corresponding progenies to selected families. ‘Wat’ here has been used to denote Watkinsville, ‘Tif’ for Tifton and ‘TN’ for Tennessee.