Exploring Metabolic Characteristics in Different Geographical Locations and Yields of Nicotiana tabacum L. Using Gas Chromatography-Mass Spectrometry Pseudotargeted Metabolomics Combined with Chemometrics.

The quality of crops is closely associated with their geographical location and yield, which is reflected in the composition of their metabolites. Hence, we employed GC-MS pseudotargeted metabolomics to investigate the metabolic characteristics of high-, medium-, and low-yield Nicotiana tabacum (tobacco) leaves from the Bozhou (sweet honey flavour) and Shuicheng (light flavour) regions of Guizhou Province. A total of 124 metabolites were identified and classified into 22 chemical categories. Principal component analysis revealed that the geographical location exerted a greater influence on the metabolic profiling than the yield. Light-flavoured tobacco exhibited increased levels of sugar metabolism- and glycolysis-related intermediate products (trehalose, glucose-6-phosphate, and fructose-6-phosphate) and a few amino acids (proline and leucine), while sweet honey-flavoured tobacco exhibited increases in the tricarboxylic acid cycle (TCA cycle) and the phenylpropane metabolic pathway (p-hydroxybenzoic acid, caffeic acid, and maleic acid). Additionally, metabolite pathway enrichment analysis conducted at different yields and showed that both Shuicheng and Bozhou exhibited changes in six pathways and four of them were the same, mainly C/N metabolism. Metabolic pathway analysis revealed higher levels of intermediates related to glycolysis and sugar, amino acid, and alkaloid metabolism in the high-yield samples, while higher levels of phenylpropane in the low-yield samples. This study demonstrated that GC-MS pseudotargeted metabolomics-based metabolic profiling can be used to effectively discriminate tobacco leaves from different geographical locations and yields, thus facilitating a better understanding of the relationship between metabolites, yield, and geographical location. Consequently, metabolic profiles can serve as valuable indicators for characterizing tobacco yield and geographical location.

Impact of green credit policy on sustainability performance of high-pollution enterprises.

Green credit is a financial service that potentially mitigates the impact of environment problems such as climate change, one of the greatest challenges of our time. The effectiveness of a policy that promotes green credit, however, remains controversial. We use China's "Green Credit Guidelines" in 2012 as a quasi-natural experiment to identify the causal impact of green credit policy (GCP) on enterprise sustainability performance (ESP), which integrates the financial and environmental social responsibility performance of heavily polluting firms. Our PSM-DID analysis shows that GCP significantly improves ESP, especially among the small and private highly polluting firms and firms located in regions with a higher level of marketization. Furthermore, GCP leads to more green innovation which, together with government subsidies, plays a positive moderating role between GCP and ESP. Our results have important policy implications.