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

A comparative analysis of near-infrared image colorization methods for low-power NVIDIA Jetson embedded systems

The near-infrared (NIR) image obtained by an NIR camera is a grayscale image that is inconsistent with the human visual spectrum. It can be difficult to perceive the details of a scene from an NIR scene; thus, a method is required to convert them to visible images, providing color and texture information. In addition, a camera produces so much video data that it increases the pressure on the cloud server. Image processing can be done on an edge device, but the computing resources of edge devices are limited, and their power consumption constraints need to be considered. Graphics Processing Unit (GPU)-based NVIDIA Jetson embedded systems offer a considerable advantage over Central Processing Unit (CPU)-based embedded devices in inference speed. For this study, we designed an evaluation system that uses image quality, resource occupancy, and energy consumption metrics to verify the performance of different NIR image colorization methods on low-power NVIDIA Jetson embedded systems for practical applications. The performance of 11 image colorization methods on NIR image datasets was tested on three different configurations of NVIDIA Jetson boards. The experimental results indicate that the Pix2Pix method performs best, with a rate of 27 frames per second on the Jetson Xavier NX. This performance is sufficient to meet the requirements of real-time NIR image colorization

Triglyceride-glucose index and the risk of heart failure: Evidence from two large cohorts and a mendelian randomization analysis.

The relationship between triglyceride-glucose (TyG) index, an emerging marker of insulin resistance, and the risk of incident heart failure (HF) was unclear. This study thus aimed to investigate this relationship. Subjects without prevalent cardiovascular diseases from the prospective Kailuan cohort (recruited during 2006-2007) and a retrospective cohort of family medicine patients from Hong Kong (recruited during 2000-2003) were followed up until December 31st, 2019 for the outcome of incident HF. Separate adjusted hazard ratios (aHRs) summarizing the relationship between TyG index and HF risk in the two cohorts were combined using a random-effect meta-analysis. Additionally, a two-sample Mendelian randomization (MR) of published genome-wide association study data was performed to assess the causality of observed associations. In total, 95,996 and 19,345 subjects from the Kailuan and Hong Kong cohorts were analyzed, respectively, with 2,726 cases of incident HF in the former and 1,709 in the latter. Subjects in the highest quartile of TyG index had the highest risk of incident HF in both cohorts (Kailuan: aHR 1.23 (95% confidence interval: 1.09-1.39), P<sub>Trend</sub> <0.001; Hong Kong: aHR 1.21 (1.04-1.40), P<sub>Trend</sub> =0.007; both compared with the lowest quartile). Meta-analysis showed similar results (highest versus lowest quartile: HR 1.22 (1.11-1.34), P < 0.001). Findings from MR analysis, which included 47,309 cases and 930,014 controls, supported a causal relationship between higher TyG index and increased risk of HF (odds ratio 1.27 (1.15-1.40), P < 0.001). A higher TyG index is an independent and causal risk factor for incident HF in the general population. URL: https://www.chictr.org.cn ; Unique identifier: ChiCTR-TNRC-11,001,489. [Abstract copyright: © 2022. The Author(s).

Triglyceride-glucose index and the risk of heart failure: Evidence from two large cohorts and a mendelian randomization analysis

The relationship between triglyceride-glucose (TyG) index, an emerging marker of insulin resistance, and the risk of incident heart failure (HF) was unclear. This study thus aimed to investigate this relationship. Subjects without prevalent cardiovascular diseases from the prospective Kailuan cohort (recruited during 2006-2007) and a retrospective cohort of family medicine patients from Hong Kong (recruited during 2000-2003) were followed up until December 31st, 2019 for the outcome of incident HF. Separate adjusted hazard ratios (aHRs) summarizing the relationship between TyG index and HF risk in the two cohorts were combined using a random-effect meta-analysis. Additionally, a two-sample Mendelian randomization (MR) of published genome-wide association study data was performed to assess the causality of observed associations. In total, 95,996 and 19,345 subjects from the Kailuan and Hong Kong cohorts were analyzed, respectively, with 2,726 cases of incident HF in the former and 1,709 in the latter. Subjects in the highest quartile of TyG index had the highest risk of incident HF in both cohorts (Kailuan: aHR 1.23 (95% confidence interval: 1.09-1.39), P<sub>Trend</sub> <0.001; Hong Kong: aHR 1.21 (1.04-1.40), P<sub>Trend</sub> =0.007; both compared with the lowest quartile). Meta-analysis showed similar results (highest versus lowest quartile: HR 1.22 (1.11-1.34), P < 0.001). Findings from MR analysis, which included 47,309 cases and 930,014 controls, supported a causal relationship between higher TyG index and increased risk of HF (odds ratio 1.27 (1.15-1.40), P < 0.001). A higher TyG index is an independent and causal risk factor for incident HF in the general population

Isolation of A Novel <i>Bacillus thuringiensis</i> Phage Representing A New Phage Lineage and Characterization of Its Endolysin

Phages, the parasites of bacteria, are considered as a new kind of antimicrobial agent due to their ability to lyse pathogenic bacteria. Due to the increase of available phage isolates, the newly isolated phage showed increasing genomic similarities with previously isolated phages. In this study, the novel phage vB_BthS_BMBphi, infecting the Bacillus thuringiensis strain BMB171, is isolated and characterized together with its endolysin. This phage is the first tadpole-like phage infecting the Bacillus strains. Genomic analysis shows that the phage genome is dissimilar to all those of previously characterized phages, only exhibiting low similarities with partial regions of the B. thuringiensis prophages. Phylogenetic analysis revealed that the phage was distant from the other Bacillus phages in terms of evolution. The novel genome sequence, the distant evolutionary relationship, and the special virion morphology together suggest that the phage vB_BthS_BMBphi could be classified as a new phage lineage. The genome of the phage is found to contain a restriction modification system, which might endow the phage with immunity to the restriction modification system of the host bacterium. The function of the endolysin PlyBMB encoded by the phage vB_BthS_BMBphi was analyzed, and the endolysin could lyse all the tested Bacillus cereus group strains, suggesting that the endolysin might be used in controlling pathogenic B. cereus group strains. The findings of this study enrich the understanding of phage diversity and provide a resource for controlling the B. cereus group pathogenic bacteria

Phage Reduce Stability for Regaining Infectivity during Antagonistic Coevolution with Host Bacterium

The coevolution between phage and host bacterium is an important force that drives the evolution of the microbial community, yet the coevolution mechanisms have still not been well analyzed. Here, by analyzing the interaction between a Bacillus phage vB_BthS_BMBphi and its host bacterium, the coevolution mechanisms of the first-generation phage-resistant bacterial mutants and regained-infectivity phage mutants were studied. The phage-resistant bacterial mutants showed several conserved mutations as a potential reason for acquiring phage resistance, including the mutation in flagellum synthesis protein FlhA and cell wall polysaccharide synthesis protein DltC. All the phage-resistant bacterial mutants showed a deleted first transmembrane domain of the flagellum synthesis protein FlhA. Meanwhile, the regain-infectivity phage mutants all contained mutations in three baseplate-associated phage tail proteins by one nucleotide, respectively. A polymorphism analysis of the three mutant nucleotides in the wild-type phage revealed that the mutations existed before the interaction of the phage and the bacterium, while the wild-type phage could not infect the phage-resistant bacterial mutants, which might be because the synchronized mutations of the three nucleotides were essential for regaining infectivity. This study for the first time revealed that the synergism mutation of three phage baseplate-associated proteins were essential for the phages&#8217; regained infectivity. Although the phage mutants regained infectivity, their storage stability was decreased and the infectivity against the phage-resistant bacterial mutants was reduced, suggesting the phage realized the continuation of the species by way of &#8220;dying to survive&#8222;

Ductility deterioration induced by L21 phase in ferritic alloy through Ti addition

Ductility deterioration induced by L21-Ni2AlTi precipitates in the aged ferritic alloys was examined systematically by using a combination of scanning transmission electron microscope (STEM), mechanical tests and first-principles thermodynamic calculations. The experimental studies revealed that the strength and hardness of the aged Fe–10Cr–5Ni–1Al–1Ti ferritic alloy containing B2–NiAl and L21-Ni2AlTi precipitates were higher than that of the aged Fe–10Cr–5Ni–1Al ferritic alloy containing NiAl precipitates, whereas the elongation-to-failure decreased dramatically from 9.3% to 0.3% indicating an obvious ductility deterioration due to the formation of L21-Ni2AlTi precipitates. This was also confirmed by the observation of fracture transition mode from dimpled failure to cleavage failure. The first-principles calculations, concerning the precipitate/matrix interface, were carried out to provide a theoretical analysis for the ductile–brittle transition by means of empirical ductility criteria ratios G/B and (C12–C44)/B as well as cleavage energy. The cleavage energy results indicated an intrinsic brittleness of the L21-Ni2AlTi phase and the L21-Ni2AlTi/BCC-Fe interface. Our analysis revealed that the intrinsic brittleness of L21-Ni2AlTi phase and L21-Ni2AlTi/BCC-Fe interface plays a vital role in determining the deformation behavior of the aged Fe–10Cr–5Ni–1Al–1Ti alloy.Godkänd;2023;Nivå 0;2023-08-08 (joosat);Funder: Natural Science Foundation of China (52074032, 51974029, 52101152, 52130407); Natural Science Foundation of Hunan Province (2022JJ30564, 2022JJ40438); Guangdong Basic and Applied Basic Research Foundation (2021B1515120033); Beijing Natural Science Foundation (2232084); State Key Laboratory of Powder Metallurgy, Central South University, Changsha, ChinaLicens fulltext: CC BY-NC-ND License</p

Formation and Identification of Lignin-Carbohydrate Complexes in Pre-hydrolysis Liquors

Funding Information: This work was supported by the National Natural Science Foundation of China (nos. 21908048, 32001705, and 32071722), the China Scholarship Council (nos. 201908420037 and 201908420032), the Canada Excellence Research Chair Program (CERC-2018-00006), and the Canada Foundation for Innovation (project number 38623). Publisher Copyright: © 2023 The Authors. Published by American Chemical Society.The lignin-carbohydrate complexes (LCCs) typically present in the liquors produced in the pre-hydrolysis of biomass cause severe difficulties in downstream fractionation. To address this issue, a series of LCC samples were accessed from solutions obtained from the pre-hydrolysis of extractive-free pine wood meal (H-LCC) and compared with LCC obtained from the corresponding residues (B-LCC). Chromatographic and spectroscopic techniques revealed that 8.2% of the lignins were degraded at 160 °C, resulting from the breakage of β-O-4′ linkages during pre-hydrolysis. Meanwhile, (reactive) hemicelluloses were mainly removed from the fibers' cell walls. Some hemicelluloses in the pre-hydrolysis liquor, such as glucomannans, were associated with degraded lignin fragments via ether and ester bonds. However, the newly formed LCCs were pH-labile and underwent rapid hydrolysis. Overall, we reveal details about LCC formation and degradation during pre-hydrolysis at given temperatures, critically important in efforts to improve biomass processing and valorization.Peer reviewe

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

Wheat is the most important staple crop grown in Australia, and Australia is one of the top wheat exporting countries globally. Timely and reliable wheat yield prediction in Australia is important for regional and global food security. Prior studies use either climate data, or satellite data, or a combination of these two to build empirical models to predict crop yield. However, though the performance of yield prediction using empirical methods is improved by combining the use of climate and satellite data, the contributions from different data sources are still not clear. In addition, how the regression-based methods compare with various machine-learning based methods in their performance in yield prediction is also not well understood and needs in-depth investigation. This work integrated various sources of data to predict wheat yield across Australia from 2000 to 2014 at the statistical division (SD)level. We adopted a well-known regression method (LASSO, as a benchmark)and three mainstream machine learning methods (support vector machine, random forest, and neural network)to build various empirical models for yield prediction. For satellite data, we used the enhanced vegetation index (EVI)from MODIS and solar-induced chlorophyll fluorescence (SIF)from GOME-2 and SCIAMACHY as metrics to approximate crop productivity. The machine-learning based methods outperform the regression method in modeling crop yield. Our results confirm that combining climate and satellite data can achieve high performance of yield prediction at the SD level (R ˜ 0.75). The satellite data track crop growth condition and gradually capture the variability of yield evolving with the growing season, and their contributions to yield prediction usually saturate at the peak of the growing season. Climate data provide extra and unique information beyond what the satellite data have offered for yield prediction, and our empirical modeling work shows the added values of climate variables exist across the whole season, not only at some certain stages. We also find that using EVI as an input can achieve better performance in yield prediction than SIF, primarily due to the large noise in the satellite-based SIF data (i.e. coarse resolution in both space and time). In addition, we also explored the potential for timely wheat yield prediction in Australia, and we can achieve the optimal prediction performance with approximately two-month lead time before wheat maturity. The proposed methodology in this paper can be extended to different crops and different regions for crop yield prediction