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The Jinhua–Quzhou basin in China is one of the most susceptible areas to drought. Due to the loss of vegetation and great fluctuations in rainfall and surface temperature, global warming occurs. Timely, accurate, and effective drought monitoring is crucial for protecting local vegetation and determining which vegetation is most vulnerable to increased LST during the period 1982–2019. It assumes a strong correlation between loss of vegetation cover, changes in monsoon climate, drought, and increases in land surface temperature (LST). Due to significantly increased in LST, low precipitation and vegetation cover, NDVI, TVDI, VCI, and NAP are useful in characterizing drought mitigation strategies. The temperature vegetation drought index (TVDI), normalized difference vegetation index (NDVI), vegetation condition index (VCI), and monthly precipitation anomaly percentage (NAP) can be helped to characterize drought reduction strategies. Monthly NDVI, NAP, VCI, TVDI, normalized vegetation supply water index (NVSWI), temperature condition index (TCI), vegetation health index (VHI), and heat map analysis indicate that the Jinhua–Quzhou basin experienced drought during 1984, 1993, 2000, and 2011. Seasonal SR, WVP, WS, NDVI, VCI, and NAP charts confirm that the Jinhua–Quzhou basin was affected by severe drought in 1984, which continued and led to severe droughts in 1993, 2000, and 2011. Regression analysis showed a significant positive correlation between NDVI, TVDI, VCI, and NAP values, while NVSWI, TVDI, and VHI showed positive signs of good drought monitoring strategies. The research results confirm the correlation between loss of vegetation cover and LST, which is one of the causes of global warming. The distribution of drought changed a trend indicating that compared with the Jinhua region; the Quzhou region has more droughts. The changing trend of drought has characteristics from 1982 to 2019, and there are significant differences in drought changing trends between different Jinhua–Quzhou basin areas. Overall, from 1982 to 2019, the frequency of drought showed a downward trend. We believe that these results will provide useful tools for drought management plans and play a relevant role in mitigating the effects of drought and protecting humanity from climate hazards. [ABSTRACT FROM AUTHOR]

This study examines the response of the BRICS and MSCI emerging stock market indices to the COVID-19 outbreak. For this purpose, this study uses a multifractal detrended fluctuation analysis (MF-DFA) to investigate the market efficiency dynamics of these indices and then ranks them based on their market efficiency. Overall, our results indicate that the returns from all the stock indices exhibit long-range correlations, implying that these markets are not weak-form efficient. Specifically, China showed the highest level of multifractality (i.e., inefficiency), which can be attributed to its highly volatile market structure. Using a subsample analysis, we further explore the impact of COVID-19 on these markets' efficiency by dividing the dataset into pre- and post-COVID periods. The findings indicate that COVID-19 adversely affected the efficiency of all the indices. Surprisingly, improvement in the Chinese market's inefficiency was witnessed, which can be attributed to the prompt and effective measures (i.e., timely imposition of health-related measures such as lockdowns and resident quarantines to contain COVID-19 and financial packages designed to curtail the economic meltdown) introduced by the Chinese government. The findings of this study may help investors, policymakers and regulators in refining their financial and policy decisions according to the new efficiency levels of these markets. [ABSTRACT FROM AUTHOR]

Traditional agrosystems, where humans, crops and microbes have coevolved over long periods, can serve as models to understand the ecoevolutionary determinants of disease dynamics and help the engineering of durably resistant agrosystems. Here, we investigated the genetic and phenotypic relationship between rice (Oryza sativa) landraces and their rice blast pathogen (Pyricularia oryzae) in the traditional Yuanyang terraces of flooded rice paddies in China, where rice landraces have been grown and bred over centuries without significant disease outbreaks. Analyses of genetic subdivision revealed that indica rice plants clustered according to landrace names. Three new diverse lineages of rice blast specific to the Yuanyang terraces coexisted with lineages previously detected at the worldwide scale. Population subdivision in the pathogen population did not mirror pattern of population subdivision in the host. Measuring the pathogenicity of rice blast isolates on landraces revealed generalist life history traits. Our results suggest that the implementation of disease control strategies based on the emergence or maintenance of a generalist lifestyle in pathogens may sustainably reduce the burden of disease in crops. [ABSTRACT FROM AUTHOR]

Recently among modern molecular tools, novel DNA barcode approach has gained significant importance for the accurate identification of animal species. However, still much remains unknown about the utility of DNA barcodes for plant species identification. To fill this research and knowledge gap, a study was designed to determine the efficacy of plant-based DNA barcodes for identification of spinach cultivars. In land plants, standard DNA barcode markers are Maturase K (matK) and RNA polymerase subunit beta' (rpoC1). Data for DNA barcoding of local spinach species were established based on matK and rpoC1 barcode using the modest taxonomic range. The results pertaining to the nucleotide sequence of matK markers from spinach exhibited maximum homology with sugar beet (Accession ID: HM850762) from Portugal, whereas rpoC1 sequence showed homology with two different plant species from China i.e., Spinach (Accession ID: AJ400848) and sugar beet (Accession id: EF534108). Our results demonstrate the promising potential of chloroplast marker genes as an effective and viable tool for species identification for spinach cultivars. [ABSTRACT FROM AUTHOR]

Understanding countrywide pathogen population structure and inter‐epidemic region spread is crucial for deciphering crop potential losses. Wheat stripe rust caused by Puccinia striiformis f. sp. tritici is a destructive disease that affects worldwide wheat production, widespread in China, representing largest epidemic region globally. This study aimed to understand the population structure and migration route of P. striiformis f. sp. tritici across China based on sampling from 15 provinces representing six epidemic zones, viz., over‐summering, over‐wintering, eastern, Yun‐Gui, Xinjiang and Tibet epidemic regions. High genotypic diversity was recorded in over‐summering, Tibet and over‐wintering epidemic regions. Epidemic regions partly explain population subdivision with variable divergence (FST = 0.005–0.344). Xinjiang and Tibet epidemic regions were independent epidemic zones with least sharing of genotypes. Among other epidemic zones, i.e. over‐summering, over‐wintering, eastern and Yun‐Gui epidemic zones, re‐sampling MLGs, clustering‐based structure, DAPC analyses, relative migration and low divergence (FST from 0.006 to 0.073) revealed frequent geneflow. Yun‐Gui epidemic regions, with a potential for both over‐summering and over‐wintering, could play an important role in causing epidemics in main wheat‐cultivating areas of China. High diversity, recombination signatures and inter‐epidemic region migration patterns need to be considered in host‐resistant cultivar development in China and neighbouring countries, considering risk of long‐distance migration capacity of pathogen. [ABSTRACT FROM AUTHOR]

Identification of the right parental combinations to maximize heterosis is the major goal of hybrid breeding, which could be achieved through identification of heterotic groups. The main objective of this study was to identify promising heterotic groups for future rice breeding programs. A collection of 359 rice genotypes of diverse origins of China and abroad, composed of inbreds, maintainers, restorers, and temperature-sensitive genic male sterile (TGMS) lines were genotyped using 10K SNP chips. The SNP data set was subjected to genomic analyses for estimation of genetic divergence and diversity. Significant variations were observed in the germplasm with the identification of six different genetic groups. These lines were assigned to the genetic groups independent of their origin. Taking an account of commercially used heterotic groups present in each cluster, three cytoplasmic male sterile (CMS) lines and 14 inbred and restorer lines with moderate to high genetic distances selected from five heterotic patterns were crossed and obtained 42 F1 hybrids. A total of 14 hybrids were found with significant maximum mid- and better-parent heterosis, namely, TaifengA × Guang122, TaifengA × Wushansimiao, and TaifengA × Minghui63 for earliness; Guang8A × Huazhan for dwarf stature; and Guang8A × Huanghuzhan-1, TaifengA × Yuexiangzhan, Guang8A × Minhui3301, TianfengA × Guang122, Guang8A × Yahui2115, TianfengA × Huanghuazhan, TianfengA × Minghui63, TianfengA × Minhui3301, TaifengA × Gui99, and Guang8A × Yuenongsimiao for yield and yield-related traits. Mid-parent and better-parent heterotic F1 hybrids were in positive correlation with the genetic distances as that manifested by commercially used heterotic groups, encouraging the use of genotypic data for identification of heterotic groups. Our study provides an informative strategy for the development of early maturing, lodging resistant and high-yielding commercial hybrids and cultivars in future heterosis breeding programs. [ABSTRACT FROM AUTHOR]

• Himalayan populations of Pakistan, Nepal and Bhutan have been previously compared, and a little is known about the relative divergence and diversity in Puccinia striiformis populations of Pakistan and China. • A clear divergence was observed between the bordering regions of Pakistan and China. • The closest subpopulations across the two countries were Xinjiang and Gilgit-Baltistan, which were close geographically. • High diversity and recombinant population structure was observed in both populations, though slightly higher in China than in Pakistan. • The lack of gene flow for a long-distance migrating pathogen due to geographical barriers. The wheat yellow rust pathogen has been shown to be diverse and potentially originated in the Himalayan region. Although Himalayan populations of Pakistan, Nepal and Bhutan have been previously compared, little is known about the relative divergence and diversity in Puccinia striiformis populations in the bordering regions of Pakistan and China. To assess the relative diversity and divergence in these regions of Pakistan (Gilgit-Baltistan, Hazara and Azad Jammu Kashmir) and China (Xinjiang, Qinghai, Tibet, Sichuan, Guizhou and Yunnan), a total of 1245 samples were genotyped using 17 microsatellite SSR markers. A clear divergence was observed between the bordering regions of Pakistan and China (F ST = 0.28) without any resampling of genetic groups and multilocus genotypes across two sides of the Himalayan mountains. The closest subpopulations across the two countries were Xinjiang and Gilgit-Baltistan (Nei's distance = 0.147), which were close geographically. A very high diversity and recombinant population structure was observed in both populations, though slightly higher in China (Genotypic diversity = 0.970; r¯d = 0.000) than in Pakistan (Genotypic diversity = 0.902; r¯d = 0.065). The distribution of genetic groups and resampling of MLGs revealed more gene flow across Yunnan, Guizhou and Sichuan regions in China, while between Hazara and Azad-Jammu Kashmir in Pakistan. The lack of gene flow between Pakistan and China populations is due to geographical barriers and a large patch of land without wheat. The information on the relative diversity and divergence in different geographical zones of the pathogen center of diversity and neighboring region should be considered in resistant wheat deployment while considering the invasion potential of the pathogen at regional and global contexts. [ABSTRACT FROM AUTHOR]

According to the United Nations Agenda, the 2023 sustainable environment is necessary to secure this planet's future; public-private partnerships investment in energy is crucial to sustainable development. The research examines the quantile association between public-private partnership ventures in energy and environmental degradation in ten developing nations, and data is used from January 1998-December 2016. The advanced econometrics quantile-on-quantile regression approach is used to control the issues of heterogeneity and asymmetric relationship. According to the quantile-on-quantile approach, there is a strong positive association between public-private partnerships in energy and environmental degradation in Argentina, Brazil, Bangladesh, and India. But the negative relationship is observed on different quantiles of China, Malaysia, Mexico, Peru, Thailand, and the Philippines. The findings suggest that the world needs to act as a single community and divert its resources toward renewable energy sources to control climate change; also, to accomplish the UN 15-year road map of Agenda 2023 with 17-SDGs; out of these 17 sustainable goals, SDG-7 is related to affordable and clean energy, SDG-11 is about sustainable cities and communities, and SDG-13 focuses on climate action for sustainable development., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)