Microbial agents such as the Bacillus species are recognized for their role as biocontrol agents against various phytopathogens through the production of diverse bioactive compounds. This study evaluates the effectiveness of Bacillus subtilis PE7 in inhibiting the growth of Didymella bryoniae, the pathogen responsible for gummy stem blight (GSB) in cucurbits. Dual culture assays demonstrate significant antifungal activity of strain PE7 against D. bryoniae. Volatile organic compounds (VOCs) produced by strain PE7 effectively impede mycelial formation in D. bryoniae, resulting in a high inhibition rate. Light microscopy revealed that D. bryoniae hyphae exposed to VOCs exhibited abnormal morphology, including swelling and excessive branching. Supplementing a potato dextrose agar (PDA) medium with a 30% B. subtilis PE7 culture filtrate significantly decreased mycelial growth. Moreover, combining a 30% culture filtrate with half the recommended concentration of a chemical fungicide yielded a more potent antifungal effect than using the full fungicide concentration alone, inducing dense mycelial formation and irregular hyphal morphology in D. bryoniae. Strain PE7 was highly resilient and was able to survive in fungicide solutions. Additionally, B. subtilis PE7 enhanced the nutrient content, growth, and development of melon plants while mitigating the severity of GSB compared to fungicide and fertilizer treatments. These findings highlight B. subtilis PE7 as a promising biocontrol candidate for integrated disease management in crop production.

Tomato leaf curl New Delhi virus (ToLCNDV) is a begomovirus causing significant melon (Cucumis melo) crop losses globally. This study aims to map the ToLCNDV resistance in the PI 414723 melon accession, previously identified and characterized through phenotypic studies, thereby exploring shared genomic regions with the established resistant source WM-7. In the present study, WM-7 and PI 414723 were crossed with the susceptible accessions \'Rochet\' and \'Blanco\' respectively, to generate F1 hybrids. These hybrids were self-pollinated to generate the populations for mapping the ToLCNDV resistance region and designing markers for marker-assisted selection. Disease evaluation included visual symptom scoring, viral-load quantification and tissue printing. Genotyping-by-sequencing and SNP markers were used for quantitative trait loci (QTL) mapping. For genetic analysis, qPCR and bulked segregant RNA-seq (BSR-seq) were performed. Gene expression was assessed using RNA-seq, and qRT-PCR was used for confirmation. The research narrows the candidate region for resistance in WM-7 and identifies overlapping QTLs on chromosome 11 in PI 414723, found in the region of the DNA primase large subunit. BSR-seq and expression analyses highlight potential regulatory roles of chromosome 2 in conferring resistance. Differential expression was confirmed for six genes in the candidate region on chromosome 2. This study confirms the existence of common resistance genes in PI 414723 and WM-7.

BACKGROUND: Ripeness is a phenotype that significantly impacts the quality of fruits, constituting a crucial factor in the cultivation and harvesting processes. Manual detection methods and experimental analysis, however, are inefficient and costly.
RESULTS: In this study, we propose a lightweight and efficient melon ripeness detection method, MRD-YOLO, based on an improved object detection algorithm. The method combines a lightweight backbone network, MobileNetV3, a design paradigm Slim-neck, and a Coordinate Attention mechanism. Additionally, we have created a large-scale melon dataset sourced from a greenhouse based on ripeness. This dataset contains common complexities encountered in the field environment, such as occlusions, overlapping, and varying light intensities. MRD-YOLO achieves a mean Average Precision of 97.4% on this dataset, achieving accurate and reliable melon ripeness detection. Moreover, the method demands only 4.8 G FLOPs and 2.06 M parameters, representing 58.5% and 68.4% of the baseline YOLOv8n model, respectively. It comprehensively outperforms existing methods in terms of balanced accuracy and computational efficiency. Furthermore, it maintains real-time inference capability in GPU environments and demonstrates exceptional inference speed in CPU environments. The lightweight design of MRD-YOLO is anticipated to be deployed in various resource constrained mobile and edge devices, such as picking robots. Particularly noteworthy is its performance when tested on two melon datasets obtained from the Roboflow platform, achieving a mean Average Precision of 85.9%. This underscores its excellent generalization ability on untrained data.
CONCLUSIONS: This study presents an efficient method for melon ripeness detection, and the dataset utilized in this study, alongside the detection method, will provide a valuable reference for ripeness detection across various types of fruits.

Nitrogen is the primary nutrient for plants. Low nitrogen generally affects plant growth and fruit quality. Melon, as an economic crop, is highly dependent on nitrogen. However, the response mechanism of its self-rooted and grafted seedlings to low-nitrogen stress has not been reported previously. Therefore, in this study, we analyzed the transcriptional differences between self-rooted and grafted seedlings under low-nitrogen stress using fluorescence characterization and RNA-Seq analysis. It was shown that low-nitrogen stress significantly inhibited the fluorescence characteristics of melon self-rooted seedlings. Analysis of differentially expressed genes showed that the synthesis of genes related to hormone signaling, such as auxin and brassinolide, was delayed under low-nitrogen stress. Oxidative stress response, involved in carbon and nitrogen metabolism, and secondary metabolite-related differentially expressed genes (DEGs) were significantly down-regulated. It can be seen that low-nitrogen stress causes changes in many hormonal signals in plants, and grafting can alleviate the damage caused by low-nitrogen stress on plants, ameliorate the adverse effects of nitrogen stress on plants, and help them better cope with environmental stresses.

The constant changes experienced in agricultural activities due to climate change pose a great challenge to melon production. Hence, this research examined the determinants of melon farmers\' adaptation strategies to cope with climate change hazards in southern-southern Nigeria. The research ultimately depended on primary data collected by using a set of questionnaires and interviews. The data were obtained from 260 samples retrieved from melon farmers by using multistage sampling techniques. The data were analyzed using the multivariate probit (MVP) model and partial eta squared test. The results of the MVP model showed that age (- 0.009), marital status (0.200), access to information on climate change (0.567) and crop insurance (0.214) were significant at the 0.01 level, while household size (- 0.030) was significant at the 0.05 level and determined the adoption of crop diversification. Educational level (0.012), extension contact (0.138) and access to credit (0.122) were significant at the 0.05 level, while access to information on climate change (0.415) was significant at the 0.01 level and determined the adoption of change in planting dates. Age (- 0.010) and access to information on climate change (0.381) were significant at the 0.01 level, while sex (- 0.139), marital status (0.158) and off-farm income (- 2.3E-7) were significant at the 0.05 level and determined the adoption of mixed farming. Farming experience (0.005) is significant at the 0.05 level, while access to information on climate change (0.529) and crop insurance (0.272) are significant at the 0.01 level and determine the adoption of drought-tolerant crop species. Access to information on climate change (0.536) is significant at the 0.01 level, indicating the adoption of improved crop species. Age (- 0.010), farm size (- 0.085) and crop insurance (0.206) were significant at the 0.05 level, while access to information on climate change (0.353) was significant at the 0.01 level and determined the adoption of off-farm job opportunities. The study recommends the availability and accessibility of credit, climate-smart agricultural practices, and the establishment of public‒private partnerships, among others.

The objective of this study was to explore the fungistatic mechanism of fig leaf extract against Fusarium and to provide a theoretical basis for the development of new plant-derived fungicides.
UNASSIGNED: The fungistaticity of fig leaf extract were analyzed by the ring of inhibition method. Fusarium equiseti was selected as the target for analyzing its fungistatic mechanism in terms of mycelial morphology, ultrastructure, cell membrane permeability, membrane plasma peroxidation, reactive oxygen species (ROS) content and changes in the activity of protective enzymes. The effect of this extract was verified in melon, and its components were determined by metabolite analysis using ultraperformance liquid chromatography‒mass spectrometry (UPLC‒MS).
UNASSIGNED: Fig leaf extract had an obvious inhibitory effect on Fusarium, and the difference was significant (P < 0.05) or highly significant (P < 0.01). Scanning and transmission electron microscopy revealed that F. equiseti hyphae exhibited obvious folding, twisting and puckering phenomena, resulting in an increase in the cytoplasmic leakage of spores, interstitial plasma, and the concentration of the nucleus, which seriously damaged the integrity of the fungal cell membrane. This phenomenon was confirmed by propidium iodide (PI) and fluorescein diacetate (FAD) staining, cell membrane permeability and malondialdehyde (MDA) content. Fig leaf extract also induced the mycelium to produce excessive H2O2,which led to lipid peroxidation of the cell membrane, promoted the accumulation of MDA, accelerated protein hydrolysis, induced an increase in antioxidant enzyme activity, and disrupted the balance of ROS metabolism; these findings showed that fungal growth was inhibited, which was verified in melons. A total of 1,540 secondary metabolites were detected by broad-targeted metabolomics, among which the fungistatic active substances flavonoids (15.45%), phenolic acids (15%), and alkaloids (10.71%) accounted for a high percentage and the highest relative content of these substances 1,3,7,8-tetrahydroxy-2- prenylxanthone, 8-hydroxyquinoline and Azelaic acid were analysed for their antimicrobial, anti-inflammatory, antioxidant, preventive effects against plant diseases and acquisition of resistance by plants. This confirms the reason for the fungicidal properties of fig leaf extracts.
UNASSIGNED: Fig leaf extract has the potential to be developed into a plant-derived fungicide as a new means of postharvest pathogen prevention and control in melon.

Bio-stimulants, such as selenium nanoparticles and melatonin, regulate melon growth. However, the effects of individual and combined applications of selenium nanoparticles and melatonin on the growth of melon seedlings have not been reported. Here, two melon cultivars were sprayed with selenium nanoparticles, melatonin, and a combined treatment, and physiological and biochemical properties were analyzed. The independent applications of selenium nanoparticles, melatonin, and their combination had no significant effects on the plant heights and stem diameters of Jiashi and Huangmengcui melons. Compared with the controls, both selenium nanoparticle and melatonin treatments increased soluble sugars (6-63%) and sucrose (11-88%) levels, as well as the activity of sucrose phosphate synthase (171-237%) in melon leaves. The phenylalanine ammonia lyase (29-95%), trans cinnamate 4-hydroxylase (32-100%), and 4-coumaric acid CoA ligase (26-113%), as well as mRNA levels, also increased in the phenylpropanoid metabolism pathway. Combining the selenium nanoparticles and melatonin was more effective than either of the single treatments. In addition, the levels of superoxide dismutase (43-130%), catalase (14-43%), ascorbate peroxidase (44-79%), peroxidase (25-149%), and mRNA in melon leaves treated with combined selenium nanoparticles and melatonin were higher than in controls. The results contribute to our understanding of selenium nanoparticles and melatonin as bio-stimulants that improve the melon seedlings\' growth by regulating carbohydrate, polyamine, and antioxidant capacities.

BACKGROUND: Phosphorus (P) deficiency, a major nutrient stress, greatly hinders plant growth. Phosphate (Pi) uptake in plant roots relies on PHT1 family transporters. However, melon (Cucumis melo L.) lacks comprehensive identification and characterization of PHT1 genes, particularly their response patterns under diverse stresses.
RESULTS: This study identified and analyzed seven putative CmPHT1 genes on chromosomes 3, 4, 5, 6, and 7 using the melon genome. Phylogenetic analysis revealed shared motifs, domain compositions, and evolutionary relationships among genes with close histories. Exon number varied from 1 to 3. Collinearity analysis suggested segmental and tandem duplications as the primary mechanisms for CmPHT1 gene family expansion. CmPHT1;4 and CmPHT1;5 emerged as a tandemly duplicated pair. Analysis of cis-elements in CmPHT1 promoters identified 14 functional categories, including putative PHR1-binding sites (P1BS) in CmPHT1;4, CmPHT1;6, and CmPHT1;7. We identified that three WRKY transcription factors regulated CmPHT1;5 expression by binding to its W-box element. Notably, CmPHT1 promoters harbored cis-elements responsive to hormones and abiotic factors. Different stresses regulated CmPHT1 expression differently, suggesting that the adjusted expression patterns might contribute to plant adaptation.
CONCLUSIONS: This study unveils the characteristics, evolutionary diversity, and stress responsiveness of CmPHT1 genes in melon. These findings lay the foundation for in-depth investigations into their functional mechanisms in Cucurbitaceae crops.

In this study, the effects of soil conditioners on the growth and development of melons and the rhizosphere soil environment were explored. The optimal amount of added soil conditioner was screened to solve the practical production problems of high-quality and high-yield thin-skinned melon. The melon variety \"Da Shetou\" was used as the material. Under the conditions of conventional fertilization and cultivation technology management, different soil conditioners were set up for potted melons. The effects of Pastoral soil (CK), 95% Pastoral soil + 5% volcanic ash soil conditioner (KT1), 85% Pastoral soil + 15% volcanic ash soil conditioner (KT2), 75% Pastoral soil + 25% volcanic ash soil conditioner (KT3), 65% Pastoral soil + 35% volcanic ash soil conditioner (KT4), and 55% Pastoral soil + 45% volcanic ash soil conditioner (KT5) on melon yield, quality, and rhizosphere soil characteristics were investigated. The soil microbial community was analyzed using Illumina MiSeq technology. Compared to CK, KT1, KT3, KT4, and KT5, the KT2 treatment could improve the single fruit yield of melon, increasing it by 4.35%, 2.48%, 2.31%, 5.92%, and 2.92%. Meanwhile, the highest contents of soluble protein, soluble solid, and soluble sugar in the KT2 treatment were 1.89 mg·100 g-1, 16.35%, and 46.44 mg·g-1, which were significantly higher than those in the control treatment. The contents of organic matter, total nitrogen, alkali-soluble nitrogen, nitrate nitrogen, ammonium nitrogen, available potassium, and available phosphorus in melon rhizosphere soil were the highest in the KT2 treatment. Through Alpha diversity analysis, it was found that the Chao1 index, Shannon index, and ACE index were significantly higher in the KT1 treatment than in the control, while, among all groups, the Simpson index and coverage were not significantly different. The dominant bacteria in the six treated samples were mainly Actinobacteriota, Proteobacteria, Cyanobacteria, Chloroflexi, Acidobacteria, Bacteroidetes, Myxomycota, Firmicutes, Gemmatimonadota, Verrucomicrobia, and Planctomycetes, which accounted for 96.59~97.63% of the relative abundance of all bacterial groups. Through redundancy analysis (RDA), it was found that the organic matter, electrical conductivity, available phosphorus, and nitrate nitrogen of melon rhizosphere soil were the dominant factors of bacterial community change at the dominant genus level. In summary, 15% ash soil conditioner applied on melon was the selected treatment to provide a theoretical reference for the application of soil conditioner in facility cultivation.

Carpel number (CN) is an important trait affecting the fruit size and shape of melon, which plays a crucial role in determining the overall appearance and market value. A unique non-synonymous single nucleotide polymorphism (SNP) in CmCLAVATA3 (CmCLV3) is responsible for the variation of CN in C. melo ssp. agrestis (hereafter agrestis), but it has been unclear in C. melo ssp. melo (hereafter melo). In this study, one major locus controlling the polymorphism of 5-CN (multi-CN) and 3-CN (normal-CN) in melo was identified using bulked segregant analysis (BSA-seq). This locus was then fine-mapped to an interval of 1.8 Mb on chromosome 12 using a segregating population containing 1451 progeny. CmCLV3 is still present in the candidate region. A new allele of CmCLV3, which contains five other nucleotide polymorphisms, including a non-synonymous SNP in coding sequence (CDS), except the SNP reported in agrestis, was identified in melo. A cis-trans test confirmed that the candidate gene, CmCLV3, contributes to the variation of CNs in melo. The qRT-PCR results indicate that there is no significant difference in the expression level of CmCLV3 in the apical stem between the multi-CN plants and the normal-CN plants. Overall, this study provides a genetic resource for melon fruit development research and molecular breeding. Additionally, it suggests that melo has undergone similar genetic selection but evolved into an independent allele.