Drought imprints on crops can reduce yield loss: Nature\u27s insights for food security

The Midwestern “Corn-Belt” in the United States is the most productive agricultural region on the planet despite being predominantly rainfed. In this region, global climate change is driving precipitation patterns toward wetter springs and drier mid- to late-summers, a trend that is likely to intensify in the future. The lack of precipitation can lead to crop water limitations that ultimately impact growth and yields. Young plants exposed to water stress will often invest more resources into their root systems, possibly priming the crop for any subsequent mid- or late-season drought. The trend toward wetter springs, however, suggests that opportunities for crop priming may lessen in the future. Here, we test the hypothesis that early season dry conditions lead to drought priming in field-grown crops and this response will protect crops against growth and yield losses from late-season droughts. This hypothesis was tested for the two major Midwestern crop, maize and soybean, using high-resolution daily weather data, satellite-derived phenological metrics, field yield data, and ecosystem-scale model (Agricultural Production System Simulator) simulations. The results from this study showed that priming mitigated yield losses from a late season drought of up to 4.0% and 7.0% for maize and soybean compared with unprimed crops experiencing a late season drought. These results suggest that if the trend toward wet springs with drier summers continues, the relative impact of droughts on crop productivity is likely to worsen. Alternatively, identifying opportunities to breed or genetically modify pre-primed crop species may provide improved resilience to future climate change

Life Cycle Greenhouse Gas Emission Comparison of Steel Products with Other Materials

This paper outlines the background of Life-Cycle Inventory/ Life-Cycle Assessment (LCI/LCA) and reviews an undergraduate design project in progress at the University of Missouri - Rolla (UMR) comparing LCI/LCA of steel products with similar products produced from competing materials. GaBi 4 LCI/LCA software is being used to model LCI/LCA with a demonstration of the use of the software for a typical steelmaking operation.1 Future research utilizing the LCI/LCA methodology is being applied to compare the environmental impact of steel products to other alternative engineering materials. This work involves 13 undergraduate students working in four design teams under a FeMET design grant provided by the American Iron and Steel Institute (AISI) and the Association of Iron and Steel Technology (AIST) Foundation

Advances in field-based high-throughput photosynthetic phenotyping

Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and respiration of plants from cellular to ecosystem scales. These techniques remain the gold standard for inferring photosynthetic rates and underlying physiology/biochemistry, although their utility for high-throughput phenotyping (HTP) of photosynthesis is limited both by the number of gas exchange systems available and the number of personnel available to operate the equipment. Remote sensing techniques have long been used to assess ecosystem productivity at coarse spatial and temporal resolutions, and advances in sensor technology coupled with advanced statistical techniques are expanding remote sensing tools to finer spatial scales and increasing the number and complexity of phenotypes that can be extracted. In this review, we outline the photosynthetic phenotypes of interest to the plant science community and describe the advances in high-throughput techniques to characterize photosynthesis at spatial scales useful to infer treatment or genotypic variation in field-based experiments or breeding trials. We will accomplish this objective by presenting six lessons learned thus far through the development and application of proximal/remote sensing-based measurements and the accompanying statistical analyses. We will conclude by outlining what we perceive as the current limitations, bottlenecks, and opportunities facing HTP of photosynthesis

Mars Science Laboratory Drill

This drill (see Figure 1) is the primary sample acquisition element of the Mars Science Laboratory (MSL) that collects powdered samples from various types of rock (from clays to massive basalts) at depths up to 50 mm below the surface. A rotary-percussive sample acquisition device was developed with an emphasis on toughness and robustness to handle the harsh environment on Mars. It is the first rover-based sample acquisition device to be flight-qualified (see Figure 2). This drill features an autonomous tool change-out on a mobile robot, and novel voice-coil-based percussion. The drill comprises seven subelements. Starting at the end of the drill, there is a bit assembly that cuts the rock and collects the sample. Supporting the bit is a subassembly comprising a chuck mechanism to engage and release the new and worn bits, respectively, and a spindle mechanism to rotate the bit. Just aft of that is a percussion mechanism, which generates hammer blows to break the rock and create the dynamic environment used to flow the powdered sample. These components are mounted to a translation mechanism, which provides linear motion and senses weight-on-bit with a force sensor. There is a passive-contact sensor/stabilizer mechanism that secures the drill fs position on the rock surface, and flex harness management hardware to provide the power and signals to the translating components. The drill housing serves as the primary structure of the turret, to which the additional tools and instruments are attached. The drill bit assembly (DBA) is a passive device that is rotated and hammered in order to cut rock (i.e. science targets) and collect the cuttings (powder) in a sample chamber until ready for transfer to the CHIMRA (Collection and Handling for Interior Martian Rock Analysis). The DBA consists of a 5/8-in. (.1.6- cm) commercial hammer drill bit whose shank has been turned down and machined with deep flutes designed for aggressive cutting removal. Surrounding the shank of the bit is a thick-walled maraging steel collection tube allowing the powdered sample to be augured up the hole into the sample chamber. For robustness, the wall thickness of the DBA was maximized while still ensuring effective sample collection. There are four recesses in the bit tube that are used to retain the fresh bits in their bit box. The rotating bit is supported by a back-to-back duplex bearing pair within a housing that is connected to the outer DBA housing by two titanium diaphragms. The only bearings on the drill in the sample flow are protected by a spring-energized seal, and an integrated shield that diverts the ingested powdered sample from the moving interface. The DBA diaphragms provide radial constraint of the rotating bit and form the sample chambers. Between the diaphragms there is a sample exit tube from which the sample is transferred to the CHIMRA. To ensure that the entire collected sample is retained, no matter the orientation of the drill with respect to gravity during sampling, the pass-through from the forward to the aft chamber resides opposite to the exit tube

To have value, comparisons of high-throughput phenotyping methods need statistical tests of bias and variance

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson’s correlation coefficient (r) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method

High C3 photosynthetic capacity and high intrinsic water use efficiency underlies the high productivity of the bioenergy grass Arundo donax

AbstractArundo donax has attracted interest as a potential bioenergy crop due to a high apparent productivity. It uses C3 photosynthesis yet appears competitive with C4 grass biomass feedstock’s and grows in warm conditions where C4 species might be expected to be that productive. Despite this there has been no systematic study of leaf photosynthetic properties. This study determines photosynthetic and photorespiratory parameters for leaves in a natural stand of A. donax growing in southern Portugal. We hypothesise that A. donax has a high photosynthetic potential in high and low light, stomatal limitation to be small and intrinsic water use efficiency unusually low. High photosynthetic rates in A. donax resulted from a high capacity for both maximum Rubisco (Vc,max 117 μmol CO2 m−2 s−1) and ribulose-1:5-bisphosphate limited carboxylation rate (Jmax 213 μmol CO2 m−2 s−1) under light-saturated conditions. Maximum quantum yield for light-limited CO2 assimilation was also high relative to other C3 species. Photorespiratory losses were similar to other C3 species under the conditions of measurement (25%), while stomatal limitation was high (0.25) resulting in a high intrinsic water use efficiency. Overall the photosynthetic capacity of A. donax is high compared to other C3 species and comparable to C4 bioenergy grasses.</jats:p

Evidence for a Shallow Evolution in the Volume Densities of Massive Galaxies at z=4z=4 to 88 from CEERS

We analyze the evolution of massive (log$_{10}$ [$M_\star/M_\odot$] $>10$) galaxies at $z \sim$ 4--8 selected from the JWST Cosmic Evolution Early Release Science (CEERS) survey. We infer the physical properties of all galaxies in the CEERS NIRCam imaging through spectral energy distribution (SED) fitting with dense basis to select a sample of high redshift massive galaxies. Where available we include constraints from additional CEERS observing modes, including 18 sources with MIRI photometric coverage, and 28 sources with spectroscopic confirmations from NIRSpec or NIRCam wide-field slitless spectroscopy. We sample the recovered posteriors in stellar mass from SED fitting to infer the volume densities of massive galaxies across cosmic time, taking into consideration the potential for sample contamination by active galactic nuclei (AGN). We find that the evolving abundance of massive galaxies tracks expectations based on a constant baryon conversion efficiency in dark matter halos for $z \sim$ 1--4. At higher redshifts, we observe an excess abundance of massive galaxies relative to this simple model. These higher abundances can be explained by modest changes to star formation physics and/or the efficiencies with which star formation occurs in massive dark matter halos, and are not in tension with modern cosmology.Comment: 20 pages, 10 figure

The Chromatin Remodeler SPLAYED Regulates Specific Stress Signaling Pathways

Organisms are continuously exposed to a myriad of environmental stresses. Central to an organism's survival is the ability to mount a robust transcriptional response to the imposed stress. An emerging mechanism of transcriptional control involves dynamic changes in chromatin structure. Alterations in chromatin structure are brought about by a number of different mechanisms, including chromatin modifications, which covalently modify histone proteins; incorporation of histone variants; and chromatin remodeling, which utilizes ATP hydrolysis to alter histone-DNA contacts. While considerable insight into the mechanisms of chromatin remodeling has been gained, the biological role of chromatin remodeling complexes beyond their function as regulators of cellular differentiation and development has remained poorly understood. Here, we provide genetic, biochemical, and biological evidence for the critical role of chromatin remodeling in mediating plant defense against specific biotic stresses. We found that the Arabidopsis SWI/SNF class chromatin remodeling ATPase SPLAYED (SYD) is required for the expression of selected genes downstream of the jasmonate (JA) and ethylene (ET) signaling pathways. SYD is also directly recruited to the promoters of several of these genes. Furthermore, we show that SYD is required for resistance against the necrotrophic pathogen Botrytis cinerea but not the biotrophic pathogen Pseudomonas syringae. These findings demonstrate not only that chromatin remodeling is required for selective pathogen resistance, but also that chromatin remodelers such as SYD can regulate specific pathways within biotic stress signaling networks

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Single-cell multi-omics analysis of the immune response in COVID-19

Peer reviewedPublisher PD