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Leaf stacking fermentation involves enzymatic actions of many microorganisms and is an efficient and environmentally benign process for degrading macromolecular organic compounds. We investigated the dynamics of metabolite profiles, bacterial and fungal communities and their interactions during fermentation using cigar leaves from three geographic regions. The results showed that the contents of total sugar, reducing sugar, starch, cellulose, lignin, pectin, polyphenol and protein in cigar tobacco leaves was significantly decreased during fermentation. Notably, the furfural, neophytadiene, pyridine, benzyl alcohol, geranylacetone, 3-hydroxy-2-butanone, N-hexanal, 3-Methyl-1-butanol and 2,3-pentanedione were important features volatile aroma compounds during fermentation. The α-diversity of fungi and bacteria initially increased and then decreased during fermentation. An analysis of variance showed that microbial diversity was influenced by fermentation stages and growing locations, in which the all stages had greater impacts on α- and β-diversity than all regions. Microbiome profiling had identified several core bacteria including Sphingomonas, Bacillus, Staphylococcus, Pseudomonas, Ralstonia, Massilia and Fibrobacter. Fungal biomarkers included Aspergillus, Penicillium, Fusarium, Cladosporium and Trichomonascus. Interestingly, the molecular ecological networks showed that the core taxa had significant correlations with metabolic enzymes and physicochemical properties; bacteria and fungi jointly participated in the carbohydrate and nitrogen compound degrading and volatile aroma compound chemosynthesis processes during fermentation. These studies provide insights into the coupling of material conversion and microbial community succession during leaf fermentation., (© 2023. The Author(s).)

Metabolic enzyme activity and microbial composition of the air-curing and fermentation processes determine the quality of cigar tobacco leaves (CTLs). In this study, we reveal the evolution of the dominant microorganisms and microbial community structure at different stages of the air-curing and fermentation processes of CTLs. The results showed that the changes in metabolic enzymes occurred mainly during the air-curing phase, with polyphenol oxidase (PPO) being the most active at the browning phase. Pseudomonas, Bacteroides, Vibrio, Monographella, Bipolaris, and Aspergillus were the key microorganisms in the air-curing and fermentation processes. Principal coordinate analysis revealed significant separation of microbial communities between the air-curing and fermentation phases. Redundancy analysis showed that bacteria such as Proteobacteria, Firmicutes, Bacteroidota, and Acidobacteriota and fungi such as Ascomycota and Basidiomycota were correlated with enzyme activity and temperature and humidity. Bacteria mainly act in sugar metabolism, lipid metabolism, and amino acid metabolism, while fungi mainly degrade lignin, cellulose, and pectin through saprophytic action. Spearman correlation network analysis showed that Firmicutes, Proteobacteria, and Actinobacteria were the key bacterial taxa, while Dothideomycetes, Sordariomycetes, and Eurotiomycetes were the key fungal taxa. This research provides the basis for improving the quality of cigars by improving the air-curing and fermentation processes. KEY POINTS: • Changes in POD and PPO activity control the color change of CTLs at the air-curing stage. • Monographella, Aspergillus, Pseudomonas, and Vibrio play an important role in air-curing and fermentation. • Environmental temperature and humidity mainly affect the fermentation process, whereas bacteria such as Proteobacteria, Firmicutes, Bacteroidota, and Acidobacteriota and fungi such as Ascomycota and Basidiomycota are associated with enzyme activity and temperature and humidity., (© 2023. The Author(s).)

Changes in volatile metabolites during cigar tobacco leaves fermentation as well as the metabolic pathways of metabolites with significant differences were investigated to determine the influence of cigar tobacco leaves fermentation on its flavor. The volatile substances in cigar tobacco leaves at different stages were detected by headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS), and the main differences in volatile substances in cigar tobacco leaves at different fermentation stages of Yunxue1 in Yuxi production area were analyzed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The results show that in the process of cigar tobacco leaves fermentation (YXF0, YXF1, YXF2, YXF3, YXF4, YXF5), a total of 613 volatile metabolites were detected, and a significant difference was found in 263 kinds of metabolites. Among them, the main upregulated differential metabolites were 1,3,6,10-Cyclotetradecatetraene, 3,7,11-trimethyl-14-(1-methylethyl)-, [ S -(E,Z,E,E)]-, Benzoic acid, Benzaldehyde, etc. While the main downregulated differential metabolites included beta.-Myrcene, trans -Farnesol, etc. The metabolites with significant differences are mainly concentrated in the biosynthesis of monoterpenes, diterpenes, sesquiterpenes and triterpenes, the degradation metabolism of amino acids, such as valine, leucine and isoleucine, and the biosynthesis of phenylpropyl. There were 8 different metabolites in 5 groups, including 4- (1-methylethyl) -1-cyclohexene-1-formaldehyde、2, 4-dihydroxyacetophenone、2-methylbutyl 3-methylbutyrate and methylpyrazine, all of which showed upregulation trend during fermentation. In the fermentation process, volatile metabolites participate in various synthesis and degradation pathways. The biosynthesis pathway of terpenes and amino acid synthesis and degradation pathway are connected to produce various terpenes, aldehydes and other substances, such as 1,3,6,10-Cyclotetradecatetraene, 3,7,11-trimethyl-14-(1-methylethyl)-, [ S -(E,Z,E,E)]-、benzaldehyde and 4-hydroxybenzaldehyde, which are conducive to the overall flavor and quality of cigar tobacco leaves., Competing Interests: There are no conflicts of interest in the submission of this manuscript, and manuscript is approved by all authors for publication., (© 2023 The Authors. Published by Elsevier B.V.)

Begomoviruses (family Geminiviridae) cause serious diseases in many crops. In this study, we characterized a begomovirus isolated from a tobacco plant with leaf curl in Puer, Yunnan Province, China. Analysis of the viral genome obtained from a symptomatic Nicotiana tabacum plant showed that it belonged to a novel monopartite begomovirus. The genome (2741 nt) shared the highest nucleotide sequence identity (83.43%) with that of tomato yellow leaf curl Vietnam virus (TYLCVV). Based on the current taxonomic criteria of the International Committee on Taxonomy of Viruses, this virus, for which the name "tobacco leaf curl Puer virus" is proposed, represents a new species of begomovirus., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Land plants have a unique vascular bundle system that ranges in length from a few centimeters to hundreds of meters. These systems integrate the various organs of the whole plant, perform material exchange between different plant tissues and mediate the transmission of signals between cells or over long distances. Grafting and parasitism can reshape the vascular tissues of different ecotypes or species and represent two important systems for studying plant systemic signaling. In recent years, with the advancement of genomics and sequencing technology, the transportation, identification, and function of systemic plant macromolecules have been extensively studied. Here, we review the current body of knowledge of the transport pathways and regulatory mechanisms of macromolecules in plants and assess systemic, long-distance signal trafficking that mediates stress responses, and plant-environment or plant-insect community interactions. Additionally, we propose several methods for identifying mobile mRNAs and proteins. Finally, we discuss the challenges facing systemic signaling research and put forth the most urgent questions that need to be answered to advance our understanding of plant systemic signaling., (© 2021 Scandinavian Plant Physiology Society.)

With the implementation of the Belt and Road Initiative and the national strategy of "Ecological Protection and High-Quality Development in the Yellow River Basin", the tourism development of the Yellow River basin of China is facing important opportunity. However, the spatial differences of tourism economy and the unbalanced development of interprovincial resources has become a threat for the sustainable development of the basin. By using the statistical data from 2003 to 2018, this paper aims to identify the numerical feature and spatial patterns of tourism development in the Yellow River Basin from the aspects of tourist volume (domestic tourists and inbound tourists) and tourism income (income from domestic tourism and inbound tourism) at provincial and prefectural scales. Analysis of spatial autocorrelation reveals significant clusters and outliers of tourist volume and tourism income at prefectural scale. Location condition, terrain condition, culture resources, regional policies, the interregional relationship and tourism infrastructure were the main factors influencing the spatial differences of tourism development in the Yellow River Basin. The study could offer useful information for the regional tourism management in the Yellow River Basin., Competing Interests: The authors have declared that no competing interests exist.

Tomato/potato heterografting-triggered phenotypic variations are well documented, yet the molecular mechanisms underlying grafting-induced phenotypic processes remain unknown. To investigate the phenotypic and transcriptomic responses of grafting parents in heterografting in comparison with self-grafting, tomato (Sl) was grafted onto potato rootstocks (St), and comparative phenotyping and transcriptome profiling were performed. Phenotypic analysis showed that Sl/St heterografting induced few phenotypic changes in the tomato scion. A total of 209 upregulated genes were identified in the tomato scion, some of which appear to be involved in starch and sucrose biosynthesis. Sl/St heterografting induced several modifications in the potato rootstocks (St-R), stolon number, stolon length and tuber number decreased significantly, together with an increase in GA 3 content of stolon and tuber, compared with self-grafted potato (St-WT). These results indicate that the tomato scion is less effective at producing substances or signals to induce tuberization but promotes stolon development into aerial stems and sprouting. RNA-Seq data analysis showed that 1529 genes were upregulated and 1329 downregulated between St-WT and St-R; some of these genes are involved in plant hormone signal transduction, with GID1-like gibberellin receptor (StGID1) and DELLA protein (StDELLA) being upregulated. Several genes in auxin, abscisic acid and ethylene pathways were differentially expressed as well. Various hormone signals engage in crosstalk to regulate diverse phenotypic events after grafting. This work provides abundant transcriptome profile data and lays a foundation for further research on the molecular mechanisms underlying RNA-based interactions between rootstocks and scions after tomato/potato heterografting., (© 2018 Scandinavian Plant Physiology Society.)

Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.