A co-located QTL for seven spike architecture-related traits shows promising breeding use potential in common wheat (Triticum aestivum L.).

KEY MESSAGE: A co-located novel QTL for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs with potential of improving wheat yield was identified and validated. Spike-related traits, including fertile florets per spike (FFS), kernel weight per spike (KWS), total florets per spike (TFS), florets per spikelet (FPs), florets in the middle spikelet (FMs), fertile florets per spikelet (FFPs), and kernel weight per spikelet (KWPs), are key traits in improving wheat yield. In the present study, quantitative trait loci (QTL) for these traits evaluated under various environments were detected in a recombinant inbred line population (msf/Chuannong 16) mainly genotyped using the 16 K SNP array. Ultimately, we identified 60 QTL, but only QFFS.sau-MC-1A for FFS was a major and stably expressed QTL. It was located on chromosome arm 1AS, where loci for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs were also simultaneously co-mapped. The effect of QFFS.sau-MC-1A was further validated in three independent segregating populations using a Kompetitive Allele-Specific PCR marker. For the co-located QTL, QFFS.sau-MC-1A, the presence of a positive allele from msf was associate with increases for all traits: + 12.29% TFS, + 10.15% FPs, + 13.97% FMs, + 17.12% FFS, + 14.75% FFPs, + 22.17% KWS, and + 19.42% KWPs. Furthermore, pleiotropy analysis showed that the positive allele at QFFS.sau-MC-1A simultaneously increased the spike length, spikelet number per spike, and thousand-kernel weight. QFFS.sau-MC-1A represents a novel QTL for marker-assisted selection with the potential for improving wheat yield. Four genes, TraesCS1A03G0012700, TraesCS1A03G0015700, TraesCS1A03G0016000, and TraesCS1A03G0016300, which may affect spike development, were predicted in the physical interval harboring QFFS.sau-MC-1A. Our results will help in further fine mapping QFFS.sau-MC-1A and be useful for improving wheat yield.

China's industrial green development and its influencing factors under the background of carbon neutrality.

To measure and analyze the evolution characteristics and influencing factors of China's industrial green development level is of great significance in achieving carbon neutrality goal. Based on the panel data from 2000 to 2018 of 30 provinces in China, this research uses the super slack-based measuring model and the Malmquist-Luenberger index to calculates China's industrial green total factor productivity and to describe its evolution characteristics using the kernel density function and moreover uses the Spatial Durbin model and the partial differential method to explores its main influencing factors. This study finds that China's overall industrial green development level is not high but shows an upward trend year by year; carbon emissions, fiscal decentralization, and urbanization are not conducive to improving the national industrial green development level, whereas economic development, foreign direct investment, industrial structure, and technological progress are positive contributors. At the same time, the level of economic development and technological progress have significant direct and spatial spillover effect. Our findings also provide some policy implications for improving China's industrial green development.

Identification and validation of a locus for wheat maximum root length independent of parental reproductive environment.

Maximum root length (MRL) plays an important role in the uptake of nutrients and resisting abiotic stresses. Understanding the genetic mechanism of root development is of great significance for genetic improvement of wheat. Previous studies have confirmed that parental reproductive environment (PRE) has a significant impact on growth and development of the next generation in the whole life cycle of a given plant. In this study, a recombinant inbred line population genotyped using the Wheat55K SNP array, was used to map quantitative trait loci (QTL) for wheat seedling MRL based on the harvested seeds from five different PREs. A total of 5 QTL located on chromosomes 3D and 7A were identified. Among them, QMrl.sicau-2SY-3D.2 located in a 4.0 cM interval on chromosome 3D was likely independent of PREs. QMrl.sicau-2SY-7A.2 was detected in two tests and probably influenced by PREs. The effect of QMrl.sicau-2SY-3D.2 was further validated using the tightly linked kompetitive allele specific PCR (KASP) marker, KASP-AX-111589572, in populations with different genetic backgrounds. Lines with a combination of positive alleles from QMrl.sicau-2SY-3D.2 and QMrl.sicau-2SY-7A.2 have significantly longer MRL. Furthermore, four genes (TraesCS3D03G0612000, TraesCS3D03G0608400, TraesCS3D03G0613600, and TraesCS3D03G0602400) mainly expressed in wheat root were predicted to be associated with root growth. Taken together, this study reports on a major QTL independent of PREs and lays a foundation for understanding the regulation mechanism of wheat MRL at the seedling stage.

A major quantitative trait locus for wheat total root length associated with precipitation distribution.

Optimizing root system architecture (RSA) allows crops to better capture water and nutrients and adapt to harsh environment. Parental reproductive environment (PRE) has been reported to significantly affect growth and development throughout the life cycle of the next generation. In this study, 10 RSA-related traits were evaluated in seedling stage from five independent hydroponic tests using seeds harvested from five different PREs. Based on the Wheat55K SNP array-based genetic map, quantitative trait loci (QTL) for these traits were detected in a recombinant inbred line population. Twenty-eight putative QTL for RSA-related traits were detected, covering thirteen chromosomal regions. A major QTL, QTrl.sicau-2SY-4D for total root length (TRL), which was likely independent of PREs, explained 15.81-38.48% of phenotypic variations and was located at 14.96-19.59 Mb on chromosome arm 4DS. Interestingly, it showed pleiotropic effects on TRL, root area, root volume, root forks, root dry weight, and shoot dry weight. The functional marker KASP-Rht-D1 for Rht-D1 was used to genotype 2SY population and remapping QTL for TRL showed that QTrl.sicau-2SY-4D was not linked to Rht-D1. The kompetitive allele-specific PCR (KASP) marker, KASP-AX-110527441 linked to this major QTL, was developed and used to successfully validate its effect in three different genetic populations. Further analysis suggested that the positive allele at QTrl.sicau-2SY-4D was mainly utilized in wheat breeding of northwest China where precipitation was significantly lower, indicating that wheat requires longer TRL to capture water and nutrients in arid or semi-arid regions due to deficient precipitation. Additionally, four genes (TraesCS4D03G0059800, TraesCS4D03G0057800, TraesCS4D03G0064000, and TraesCS4D03G0064400) possibly related to root development were predicted in physical interval of QTrl.sicau-2SY-4D. Taken together, these results enrich our understanding on the genetic basis of RSA and provide a potentially valuable TRL QTL for wheat breeding.

Human Health, Environmental Quality and Governance Quality: Novel Findings and Implications From Human Health Perspective.

Human health and wellbeing are intimately linked to the state of the environment. The current study emphasizes the role of environmental quality, government policies, and human health. This paper provides a detailed literature review of existing findings regarding our key variables of interest. The results argue that the implications of poor government policies and environmental pollution for rising economic development have led to poor environmental quality and health issues for humans. Based on earlier investigations, the present study reviewed the state-of-the-art review and determined innovative insights for outdoor and indoor environment difficulties. This study provides a detailed review of human health, environmental quality, and governance quality. In addition, the study conducts an empirical analysis using the annual data of low-income countries from 1996 to 2020. Government actions and health systems must be modified immediately to address these rising concerns successfully. The report offers policy recommendations for addressing health, governance, and environmental change mitigation issues, all of which are directly or indirectly related to the study. This article presents an overview of environmental change's health impacts and explores how health hazards may be reduced or eliminated through effective adaptation strategies.

Spatial and Temporal Differences in the Health Expenditure Efficiency of China: Reflections Based on the Background of the COVID-19 Pandemic.

The outbreak of the COVID-19 pandemic has brought several challenges to China's national health services, causing great risks and uncertainties to people's lives. Considering China's huge population and relatively small medical investment and its good performance in the COVID-19 pandemic, this research utilizes the hybrid meta-frontier model to analyze health expenditure efficiencies of 30 provinces in China from 1999 to 2018 and compares spatial and temporal differences of the efficiencies in regards to regional forward position and national common frontier. The results show an obvious difference in health expenditure efficiency in different provinces along the regional frontier, in which the efficiency gap in the eastern region is the largest. Moreover, the room for improvement in health expenditure efficiency varies from region to region. For the national common frontier, Beijing is the most efficient, while Guizhou is the least. The eastern region owns the most efficient technical level of health expenditure efficiency, and there is a large efficiency distance between it and the western region. The findings offer effective guidance for elevating the expenditure structure and spatial resource allocation of public health and for promoting the equalization of high quality basic medical services.

The impact of green credit policy on energy efficient utilization in China.

Green credit policy is an innovative measure in the financial industry and can help enterprises reduce energy consumption, reverse the situation of environmental pollution and resource waste, and promote sustainable development of the economy and society based on guiding fund flows into the green environmental protection industry. This research thus uses panel data of 30 provinces and cities in China from 2000 to 2017 to examine the impact of a green credit policy on the level of energy efficient utilization. We establish the EBM (epsilon-based measure) super-efficiency model to measure the level of energy efficient utilization in China, apply the regression discontinuity design (RDD) model to empirically study the net effect of the green credit policy on the level of energy efficient utilization, and assess the policy's regional heterogeneity. Finds present that the level of energy efficient utilization in China exhibits a fluctuating upward trend, and there are certain spatial heterogeneities across its regions. The overall level of the eastern region's energy efficient utilization is the best, followed by the central and western regions in that order. The results of RDD based on the national perspective indicate that the green credit policy has a significantly positive effect on the level of energy efficient utilization, while subregional regression results reveal that improvement caused by implementation of the green credit policy varies across regions in China. The performance of improving energy efficiency in the eastern region is excellent, but the improvement effect in the central and western regions is so far not desirable.

Spatial-temporal characteristics and influencing factors of atmospheric environmental efficiency in China.

This research constructs a super efficiency slack-based measure (SBM) model based on the Malmquist-Luenberger (ML) index to analyze the atmospheric environmental efficiency (AEE) of 30 provinces in China from 2000 to 2016 and explores the spatial and temporal differences of AEE by using the coefficient of variation method. This paper further analyzes the internal influencing factors of AEE via the ML index decomposition approach and establishes a panel data regression model to explore AEE's influencing factors in China. The results show some regional differences of the AEE level in China, with it the best in the eastern region and followed in order by the western and central region, and these differences exhibit an increasing trend year by year. During the study period, the development trend of AEE in China is similar to that in the eastern and western regions, showing a "W" shape, where in the central region it has a "U" pattern. The conclusion is that technical progress (TC) is the dominant factor affecting AEE, technical efficiency (EC) fails to effectively promote AEE improvement, and TC and EC present varying degrees of influence and different directions of action in the regions. The analysis results show that the influence effect of economic development on AEE presents a "U" pattern of first declining and then rising. The degree of China opening up to the outside world and its carbon dioxide emissions intensity have significant negative effects on AEE, whereas the increase of pollution control input effectively improves AEE.