Drought stress (DS) is a hazardous abiotic prerequisite that is becoming increasingly severe around the world. As a result, new management measures to reduce the negative effects of DS are desperately needed to ensure improved agricultural productivity. This review focuses primarily on various DS mitigation strategies that can be utilized to overcome DS. In recent years, the application of biochar, plant growth promoting rhizobacteria (PGPR), and arbuscular mycorrhizal fungi (AMF) have emerged as major strategies for improving crop yields under DS conditions. PGPR increases osmolyte buildup, increases the aminocyclopropane-1-carboxylate (ACC) deaminase enzyme, and provides inaccessible nutrients to plants, hence boosting drought tolerance. Different genetic approaches, including as transcriptional engineering, miRNA engineering, and quantitative trait loci (QTL) mapping, have emerged as an incredibly efficient method for making drought-resistant plants. Drought-related phytohormones, signaling molecules, transcription factors, and transcriptional and translational changes are all affected by genomic intervention. It is critical for enhancing tolerance response to identify prospective transcription factors and target them for engineering the abiotic stress tolerance response in crop plants. Investigating novel QTLs for drought tolerance features using a fresh genetic resource would also be beneficial in dissecting the mechanisms governing the trait's diversity. This review aims to provide information to readers about drought mitigation measures including the usage of PGPR, AMF, biochar, phytohormones, chemicals, and genetic approaches.

The timing of maturity significantly impacts the quality of cigar tobacco leaves, with both premature and delayed maturation leading to quality degradation. Despite the known association between maturity and physiological metabolic activities, there is a paucity of concrete evidence detailing the physiological behavior of cigar leaves harvested at varying times. This research involved a comprehensive physiological and metabolomic examination of the cigar tobacco variety CX-014, cultivated in Danjiangkou City, Hubei Province. The study focused on leaves picked at 35 (T1), 42 (T2), 49 (T3), and 56 (T4) days following the removal of the apical inflorescence. As the harvest period progressed, the leaves’ hue transitioned from green to yellow, displaying white mature spots. Between T1 and T2, there was an uptick in pigment indices (like chlorophyll a and b) and photosynthetic traits (such as stomatal conductance), which then diminished in the T3 and T4 samples. Optimal levels of sugar-to-nicotine and potassium-to-chlorine ratios—key indicators of smoking quality and tobacco combustibility—were observed at T3, suggesting a more balanced chemical composition in the leaves harvested at this stage. Metabolomic analysis revealed 2,153 distinct metabolites, with the most significant changes occurring between T2 and T3, highlighting critical physiological transformations during this interval. Pathway enrichment analysis via KEGG pinpointed notable shifts in amino acid synthesis pathways, particularly those involving tryptophan, alanine, and aspartate. Tryptophan metabolism and zeatin biosynthesis were substantially altered, with compounds like indolepyruvic acid, N-formylpurine nucleotide, isopentenyladenine nucleotide, and dihydrozeatin showing marked reductions at T3. This study also explored how the timing of lower leaf harvest influences the physiological processes of middle leaves, finding that a plethora of metabolites associated with the breakdown of arachidonic acid—a primitive metazoan signaler implicated in plant stress and defense networks—were abundant in T3 leaves when lower leaves were harvested 43 to 38 days prior. These findings suggest that the harvest timing of lower leaves may sway the maturation physiology and environmental adaptability of middle leaves. Overall, this investigation sheds light on the intricate physiological dynamics of cigar leaves throughout maturation and pinpoints crucial metabolites that signify pivotal metabolic pathways.

The maturity of fresh tobacco leaves significantly impacts the quality of subsequent curing processes, making accurate recognition of tobacco leaves maturity crucial. The development of computer vision has facilitated the recognition of tobacco leaves maturity. However, the subtle variations in color and texture among different maturity levels pose a major challenge in effectively identifying various types of tobacco leaves maturity. In this study, tobacco leaves of different maturity levels were collected from tobacco fields for analysis. We propose an innovative and effective deep learning model called TobaccoNet to improve the accuracy of tobacco leaves maturity recognition. The model utilizes ResNet-34 as the backbone network and uniformly segments and recombines preprocessed tobacco leaf image data using a random jigsaw generator. Furthermore, a progressive training approach is employed to train multi-granularity image data, enabling accurate recognition of tobacco leaves maturity. The results demonstrate that the classification accuracy of the TobaccoNet model reaches 96.67 %, highlighting the practicality of our technology in tobacco leaves maturity classification.

Cigar variety CX-010 tobacco leaves produce localized green spots during the air-curing period, and spraying exogenous sucrose effectively alleviates the occurrence of the green spots. To investigate the alleviation effect of exogenous sucrose spraying, the total water content and the number and size of green spots on tobacco leaves were investigated during the air-curing period under four treatments; CK (pure water), T1 (0.1 M sucrose), T2 (0.2 M sucrose) and T3 (0.4 M sucrose). The results showed that the total water content of tobacco leaves showed a trend of T3 < CK < T2 < T1 in the early air-curing stage, and the number and size of green spots showed a trend of T3 < T2 < T1 < CK. All sucrose treatments alleviated the green spot phenomenon, and T3 had the fewest green spots. Thus, the tobacco leaves of the T3 and CK treatments at two air-curing stages were used to perform metabolomics analysis with nontargeted liquid chromatography‒mass spectrometry to determine the physiological mechanism. A total of 259 and 178 differentially abundant metabolites (DAMs) between T3- and CK-treated tobacco leaves were identified in the early air-curing and the end of air-curing stages, respectively. These DAMs mainly included lipid and lipid-like molecules, carbohydrates, and organic acids and their derivatives. Based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, the T3 treatment significantly altered carbohydrate metabolism (pentose phosphate pathway, sucrose and starch metabolism and galactose metabolism) and amino acid metabolism (tyrosine metabolism and tryptophan metabolism) in air-curing tobacco leaves. Sucrose treatment alleviated green spots by altering DAMs that affected chlorophyll degradation, such as tyrosine and citric acid, to promote the normal degradation of chlorophyll.