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Olive (Olea europaea ssp. europaea) is the most important oil fruit crop in temperate areas, but the origin of the cultivated olive remains unclear. The existence of one or several domestication events in the Mediterranean Basin (MB) is still debated. We analyzed a dataset of 387 cultivated and wild accessions that were genotyped at 25 simple‐sequence repeat (SSR) loci. The sample represented genetic diversity at the geographic extremes of the MB. We inferred relationships among samples and also applied approximate Bayesian computation to estimate the most probable demographic model of our samples. Cultivated olives clustered into three different gene pools (Q1, Q2 and Q3), corresponding loosely to the west, central and eastern MB, respectively. Q1 consisted primarily of accessions from southern Spain, retained the fingerprint of a genetic bottleneck, and was closely related to accessions from the eastern MB. Q2 showed signs of recent admixture with wild olives and may derive from a local domestication event in the central MB. Overall our results suggest that admixture shaped olive germplasm and perhaps also local domestication events.

A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well.

Global climate change will cause significant changes in climate parameters, especially temperature increases and changes in precipitation regimes worldwide. Since the life of living things is directly related to climate parameters, this process will inevitably affect all living things. The plants will be the most affected living things from this process because they do not have an effective movement and migration mechanism. Therefore, global climate change will cause significant species and population losses in plants. To minimize the potential loss of species and populations, it is necessary to predetermine the potential changes in species’ distribution areas and take necessary actions. Therefore, this study was aimed to determine the distribution areas of three Tilia species ( Tilia tomentosa , Tilia cordata , and Tilia platyphyllos ), which have economic, ecologic, and social value and show the local distribution in Turkey and to determine how they will be affected by global climate change. Within this scope, nineteen bioclimatic variables, Emberger climate classification, aspect, and topographic altitude variable were used in the modeling process. By modeling the scenarios SSP 245 and SSP 585, the projections were made for 2040, 2060, 2080, and 2100 regarding the areas suitable for the growth of these species and how these areas will change compared to their current situation. The results suggest that the distribution areas of all three  Tilia  species will change due to climate change, and the area of loss will be 43.5 km 2 (4%) for  T. tomentosa , 9953.6 km 2 (15%) for  T. platyphyllos , and 448.0 km 2 (19%) for  T. cordata . Moreover, a more important point here is that increases and decreases will be observed in their distribution areas, and these changes will occur in a short process and at significant levels. In this case, the migration mechanism that these species will require must be provided by humans.

Georeferenced information on road infrastructure is essential for spatial planning, socio-economic assessments and environmental impact analyses. Yet current global road maps are typically outdated or characterized by spatial bias in coverage. In the Global Roads Inventory Project we gathered, harmonized and integrated nearly 60 geospatial datasets on road infrastructure into a global roads dataset. The resulting dataset covers 222 countries and includes over 21 million km of roads, which is two to three times the total length in the currently best available country-based global roads datasets. We then related total road length per country to country area, population density, GDP and OECD membership, resulting in a regression model with adjusted R2 of 0.90, and found that that the highest road densities are associated with densely populated and wealthier countries. Applying our regression model to future population densities and GDP estimates from the Shared Socioeconomic Pathway (SSP) scenarios, we obtained a tentative estimate of 3.0-4.7 million km additional road length for the year 2050. Large increases in road length were projected for developing nations in some of the world's last remaining wilderness areas, such as the Amazon, the Congo basin and New Guinea. This highlights the need for accurate spatial road datasets to underpin strategic spatial planning in order to reduce the impacts of roads in remaining pristine ecosystems.

In potato breeding, morphological tuber traits are important selection targets to meet the demands of the fresh and processing markets. Understanding the genetic basis of tuber traits should guide selection and improve breeding efficiencies. However, this is challenging in potato due to the complexity of the traits and the polyploid nature of the potato genome. High-throughput affordable molecular markers and new software specific for polyploid species have the potential to unlock previously unattainable levels of understanding of the genetic basis of tuber traits in tetraploid potato. In this study, we genotyped a diversity panel of 214 advanced clones with the 22 K SNP potato array and phenotyped it in three field environments in Texas. We conducted a genome-wide association study using the GWASpoly software package to identify genomic regions associated with tuber morphological traits. Some of the QTLs discovered confirmed prior studies, whereas others were discovered for the first time. The main QTL for tuber shape was detected on chromosome 10 and explained 5.8% of the phenotypic variance. GWAS analysis of eye depth detected a significant QTL on chromosome 10 and explained 3.9% of the phenotypic variance. Our study found that multiple QTLs govern russeting in potato. A major QTL for flesh color on chromosome 3 that explained 26% of the phenotypic variance likely represents the Y locus responsible for yellow flesh in potato tubers. Several QTLs were detected for purple skin color on chromosome 11. Furthermore, genomic estimated breeding values were obtained, which will aid in the early identification of superior parental clones that should increase the chances of producing progenies with higher frequencies of the desired tuber traits. These findings will contribute to a better understanding of the genetic basis of morphological traits in potato, as well as to identifying parents with the best breeding values to improve selection efficiency in our potato breeding program.

Drought risk assessment can identify high‐risk areas and bridge the gap between impacts and adaptation. It is thus vital to investigate changes in drought risk and exposed social economy under climate change. Here, the future global meteorological drought risk is projected for the 2021–2100 period under four combined scenarios of Representative Concentration Pathways and Shared Socioeconomic Pathways (SSPs), i.e., SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5. And then the exposed population and Gross Domestic Product (GDP) under high risk are analyzed. Drought risk will further strengthen in the future under SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, with large increases distributed in South Asia, the Mediterranean, East Asia, Southeast Asia, and Central America. The strongest increasing trends in drought risk are concentrated in equatorial regions including South Asia, West Africa, and Central America. A large percentage of the population and economy are exposed to high drought risk. The exposed population under the highest risk level is the largest under SSP5‐8.5 and the smallest under SSP3‐7.0 for regions in North America, while being the largest under SSP3‐7.0 for other regions. The exposed GDP under the highest risk level is the highest under SSP5‐8.5 and the lowest under SSP3‐7.0, while the disparity among diverse scenarios is larger for the rich regions than the developing ones. Plain Language Summary Drought increasingly affects society, economy, and ecosystems as a frequent natural disaster. Drought risk assessment can help understand the extent of drought threat to the human system. Therefore, we projected 0.5° × 0.5° future drought risk for the 2021–2100 period under four scenarios and investigated the exposed population and Gross Domestic Product (GDP) under high risk. We find that high‐risk regions mainly concentrate in South Asia, the Mediterranean, East Asia, Southeast Asia, Central America, eastern North America, North Europe, and West Africa, and global drought risk will increase in the future. The population exposed to high drought risk for South Asia, West Africa, and East Asia is much larger than other regions. GDP exposed to high drought risk is the largest for East and South Asia. Large exposed population and GDP occur under high forcing fossil‐fueled development pathways. Our findings help policymakers develop adaptive disaster prevention measures. Key Points Drought risk will increase worldwide in the future, being the highest under SSP5‐8.5 and the lowest under SSP1‐2.6 for most regions Exposed population under high risk is the largest under SSP5‐8.5 for regions in North America while under SSP3‐7.0 for other regions Exposed Gross Domestic Product under high risk is significantly higher under SSP5‐8.5 than the other scenarios and the lowest under SSP3‐7.0 for all regions

Yangtze River basin (YZB) experienced record‐breaking heat in the summer of 2022. Here, we focused on daytime‐nighttime compound heat waves, and used the magnitude index that considers both duration and intensity to investigate the risk of the 2022 extreme heat. The magnitude of heatwaves in 2022 was much larger than the historical average level, which was estimated as a 1‐in‐64‐year event over 1979–2014 climate. Without mitigation efforts (SSP585), the record‐breaking heat would emerge as normal during 2050s, and would affect ∼70% of land and projected population in the basin before global mean temperature change reaches 3°C. Such an emergence could be progressively delayed and impacts could be reduced under lower warming levels. The affected area would be 60% lesser at 2°C warming, and the emergence could be avoided by limiting warming to 1.5°C. Our results call for urgent mitigation efforts for reducing the risk of compound heat extremes. Plain Language Summary Persistent extreme high temperature occurred in Yangtze River basin (YZB) during summer 2022, leading to widespread droughts, heat‐related disease and socioeconomic losses. The physical drivers and future risk of the heat extremes have attracted extensive attention. Focusing on daytime‐nighttime compound heat waves, which have more adverse effect on human health and ecosystem, we investigated the magnitude of compound heat waves occurred in 2022, and future risk under different warming levels and emission scenarios. Observations show that the magnitude was the strongest since records began in 1979, and the return period was 64 (95% CI: 30–223) years over the 1979–2014 climate. Projections show that such unprecedented heat in observed records would emerge as normal since 2053 (2081) under nonmitigation (moderate mitigation) scenario. Moderate climate mitigation efforts could delay the time by 28 years. Compared with the 2°C global warming level, about 10% of lands and population would be avoided to normally expose to such heat at 1.5°C warming level. However, the exposures would increase by 60% from 2°C to 3°C warming level. This study suggests that mitigation actions for accomplishing 2°C warming goal and further pursuing the ambitious goal of 1.5°C can substantially reduce the exposure risk of such unprecedented heat. Key Points The 2022 record‐breaking compound heat waves in Yangtze River basin would become normal during 2050s under a nonmitigation scenario Moderate climate mitigation efforts would delay the time of emergence by 28 years Compared to 3°C, limiting warming to 2°C and 1.5°C could avoid 60% and 70% of lands that are normally affected by such rare heat, respectively

Background One future challenge of agriculture will be maintaining food security in times of climate change. Future plant breeding, therefore, has to account for the genotypes’ survival during drought and a good recovery ability after rainfall events. We aimed at investigating the re-tillering behavior of selected barley genotypes (cultivars and wild barley introgression lines) in different drought and re-watering scenarios, which were applied in a high-throughput phenotyping facility. Re-tillering describes the activation of additional tillers after post-stress irrigation. Results Twenty-three selected genotypes of the barley NAM population HEB-25, along with three control genotypes, were evaluated in four replicates under five distinct treatment conditions. In this experiment, re-tillering was particularly pronounced in an alternating watering and stress treatment, where the resumption of irrigation post-stress enabled full recovery of the plants. However, it was noted that while re-watering after a stress period promotes tiller activation and the development of fertile ears, it also tends to increase the number of sterile ears. The degree of sterile ear formation varied significantly among different genotypes, highlighting the critical role of genetic factors in modulating plant responses to re-tillering and post-stress irrigation. It is important to note that excessive re-tillering has been shown to exhibit a negative correlation with fertile ear weight. Conclusions The impact of focusing on tiller number and re-tillering behavior in future barley breeding may be significant, particularly in the context of climate change. By selecting for genotypes with appropriate tillering plasticity, breeders can develop barley varieties that are more resilient to stress conditions such as drought.

In our study, we performed a population genetic analysis in all three native oak species of Cyprus and addressed whether two intermediate individuals arose from intersectional hybridization between ssp. and ssp. . For this purpose, we successfully tested chloroplast and nuclear microsatellites initially developed for other oak species. We identified a set of markers that can be efficiently used for species identification and study of hybridization. Haplotypes based on the chloroplast microsatellites could resolve different maternal lineages and distinguish between the two sections represented in the study area. Using the nuclear microsatellites, we described patterns of genetic diversity across species with the endemic exhibiting reduced genetic diversity. Additionally, we employed a multivariate analysis, which could clearly differentiate among the three species. The two intermediate individuals clustered within the point cloud of ssp. and also possessed a chloroplast haplotype typical for this species. Therefore, we rejected the hypothesis of intersectional hybridization and interpreted their phenotypic appearance as the result of high phenotypic plasticity within ssp.

The remarkable biological activities of oregano essential oils (EOs) have recently prompted a host of studies aimed at exploring their potential innovative applications in the food and pharmaceutical industries. The chemical composition and biological activities of EOs from two Origanum vulgare genotypes, widely cultivated in Sicily and not previously studied for their biological properties, were characterized. Plants of the two genotypes, belonging to the carvacrol (CAR) and thymol (THY) chemotypes and grown in different cultivation environments, were considered for this study. The chemical profiles, including the determination of enantiomeric distribution, of the EOs, obtained by hydrodistillation from dried leaves and flowers, were investigated by GC–MS. Biological activity was evaluated as antimicrobial properties against different pathogen indicator strains, while intestinal barrier integrity, reduction in pathogen adhesion and anti-inflammatory actions were assayed in the intestinal Caco-2 cell line. The chemical profile of the CAR genotype was less complex and characterized by higher levels of the most active compound, i.e., carvacrol, when compared to the THY genotype. The enantiomeric distribution of chiral constituents did not vary across genotypes, while being markedly different from that observed in Origanum vulgare genotypes from other geographical origins. In general, all EOs showed high antimicrobial activity, both in vitro and in a food matrix challenge test. Representative EOs from the two genotypes resulted not altering epithelial monolayer sealing only for concentrations lower than 0.02%, were able to reduce the adhesion of selected pathogens, but did not exert relevant anti-inflammatory effects. These results suggest their potential use as control agents against a wide spectrum of foodborne pathogens.