Common bean (Phaseolus vulgaris L.) is an essential food staple and source of income for small-holder farmers across Africa. However, yields are greatly threatened by fungal diseases like root rot induced by Rhizoctonia solani. This study aimed to evaluate an integrated approach utilizing vermicompost tea (VCT) and antagonistic microbes for effective and sustainable management of R. solani root rot in common beans. Fourteen fungal strains were first isolated from infected common bean plants collected across three Egyptian governorates, with R. solani being the most virulent isolate with 50% dominance. Subsequently, the antagonistic potential of vermicompost tea (VCT), Serratia sp., and Trichoderma sp. was assessed against this destructive pathogen. Combinations of 10% VCT and the biocontrol agent isolates displayed potent inhibition of R. solani growth in vitro, prompting in planta testing. Under greenhouse conditions, integrated applications of 5 or 10% VCT with Serratia marcescens, Trichoderma harzianum, or effective microorganisms (EM1) afforded up to 95% protection against pre- and post-emergence damping-off induced by R. solani in common bean cv. Giza 6. Similarly, under field conditions, combining VCT with EM1 (VCT + EM1) or Trichoderma harzianum (VCT + Trichoderma harzianum) substantially suppressed disease severity by 65.6% and 64.34%, respectively, relative to untreated plants. These treatments also elicited defense enzyme activity and distinctly improved growth parameters including 136.68% and 132.49% increases in pod weight per plant over control plants. GC-MS profiling of Trichoderma harzianum, Serratia marcescens, and vermicompost tea (VCT) extracts revealed unique compounds dominated by cyclic pregnane, fatty acid methyl esters, linoleic acid derivatives, and free fatty acids like oleic, palmitic, and stearic acids with confirmed biocontrol and plant growth-promoting activities. The results verify VCT-mediated delivery of synergistic microbial consortia as a sustainable platform for integrated management of debilitating soil-borne diseases, enhancing productivity and incomes for smallholder bean farmers through regeneration of soil health. Further large-scale validation can pave the adoption of this climate-resilient approach for securing food and nutrition security.

This study investigated a novel probiotic-enriched ice cream containing fermented white kidney bean homogenate to explore its potential health benefits in the future. We assessed the viability of various probiotic strains during ice cream production and storage, focusing on their potential to reach the gut, and evaluated overall antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2\'-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), ferric reducing antioxidant power (FRAP), and total polyphenol content (TPC) assays. The incorporation of fermented white bean homogenate significantly increased antioxidant capacity compared to the control group. Notably, strains such as Lacticaseibacillus rhamnosus GG and Lactiplantibacillus plantarum 299v demonstrated the most pronounced effects on antioxidant activity, suggesting potential synergistic benefits between probiotics and bioactive compounds in fermented white beans. Although all probiotic strains experienced decreased viability during storage, certain strains, particularly L. plantarum 299v and Lacticaseibacillus casei DN-114001, showed promising survival rates even after 6 months. These results suggest the potential for developing probiotic ice cream containing viable bacteria capable of reaching the gut and contributing to a healthy gut microbiota. Overall, this study highlights the potential of probiotic-enriched ice cream with fermented white kidney bean homogenate to combine the established benefits of probiotics for gut health with the enjoyment of consuming ice cream.

Skin aging is an inevitable and intricate process instigated, among others, by oxidative stress. The search for natural sources that inhibit this mechanism is a promising approach to preventing skin aging. The purpose of our study was to evaluate the composition of phenolic compounds in the micellar extract of Phaseolus vulgaris sprouts. The results of a liquid chromatography-mass spectrometry (LC-MS) analysis revealed the presence of thirty-two constituents, including phenolic acids, flavanols, flavan-3-ols, flavanones, isoflavones, and other compounds. Subsequently, the extract was assessed for its antioxidant, anti-inflammatory, anti-collagenase, anti-elastase, anti-tyrosinase, and cytotoxic properties, as well as for the evaluation of collagen synthesis. It was demonstrated that micellar extract from common bean sprouts has strong anti-aging properties. The performed WST-8 (a water-soluble tetrazolium salt) assay revealed that selected concentrations of extract significantly increased proliferation of human dermal fibroblasts compared to the control cells in a dose-dependent manner. A similar tendency was observed with respect to collagen synthesis. Our results suggest that micellar extract from Phaseolus vulgaris sprouts can be considered a promising anti-aging compound for applications in cosmetic formulations.

Common beans (CB), a vital source for high protein content, plays a crucial role in ensuring both nutrition and economic stability in diverse communities, particularly in Africa and Latin America. However, CB cultivation poses a significant threat to diseases that can drastically reduce yield and quality. Detecting these diseases solely based on visual symptoms is challenging, due to the variability across different pathogens and similar symptoms caused by distinct pathogens, further complicating the detection process. Traditional methods relying solely on farmers\' ability to detect diseases is inadequate, and while engaging expert pathologists and advanced laboratories is necessary, it can also be resource intensive. To address this challenge, we present a AI-driven system for rapid and cost-effective CB disease detection, leveraging state-of-the-art deep learning and object detection technologies. We utilized an extensive image dataset collected from disease hotspots in Africa and Colombia, focusing on five major diseases: Angular Leaf Spot (ALS), Common Bacterial Blight (CBB), Common Bean Mosaic Virus (CBMV), Bean Rust, and Anthracnose, covering both leaf and pod samples in real-field settings. However, pod images are only available for Angular Leaf Spot disease. The study employed data augmentation techniques and annotation at both whole and micro levels for comprehensive analysis. To train the model, we utilized three advanced YOLO architectures: YOLOv7, YOLOv8, and YOLO-NAS. Particularly for whole leaf annotations, the YOLO-NAS model achieves the highest mAP value of up to 97.9% and a recall of 98.8%, indicating superior detection accuracy. In contrast, for whole pod disease detection, YOLOv7 and YOLOv8 outperformed YOLO-NAS, with mAP values exceeding 95% and 93% recall. However, micro annotation consistently yields lower performance than whole annotation across all disease classes and plant parts, as examined by all YOLO models, highlighting an unexpected discrepancy in detection accuracy. Furthermore, we successfully deployed YOLO-NAS annotation models into an Android app, validating their effectiveness on unseen data from disease hotspots with high classification accuracy (90%). This accomplishment showcases the integration of deep learning into our production pipeline, a process known as DLOps. This innovative approach significantly reduces diagnosis time, enabling farmers to take prompt management interventions. The potential benefits extend beyond rapid diagnosis serving as an early warning system to enhance common bean productivity and quality.

Vertical transmission, the transfer of pathogens across generations, is a critical mechanism for the persistence of plant viruses. The transmission mechanisms are diverse, involving direct invasion through the suspensor and virus entry into developing gametes before achieving symplastic isolation. Despite the progress in understanding vertical virus transmission, the environmental factors influencing this process remain largely unexplored. We investigated the complex interplay between vertical transmission of plant viruses and pollination dynamics, focusing on common bean (Phaseolus vulgaris). The intricate relationship between plants and pollinators, especially bees, is essential for global ecosystems and crop productivity. We explored the impact of virus infection on seed transmission rates, with a particular emphasis on bean common mosaic virus (BCMV), bean common mosaic necrosis virus (BCMNV), and cucumber mosaic virus (CMV). Under controlled growth conditions, BCMNV exhibited the highest seed transmission rate, followed by BCMV and CMV. Notably, in the field, bee-pollinated BCMV-infected plants showed a reduced transmission rate compared to self-pollinated plants. This highlights the influence of pollinators on virus transmission dynamics. The findings demonstrate the virus-specific nature of seed transmission and underscore the importance of considering environmental factors, such as pollination, in understanding and managing plant virus spread.

The NAC family of transcription factors includes no apical meristem (NAM), Arabidopsis thaliana transcription activator 1/2 (ATAF1/2), and cup-shaped cotyledon (CUC2) proteins, which are unique to plants, contributing significantly to their adaptation to environmental challenges. In the present study, we observed that the PvNAC52 protein is predominantly expressed in the cell membrane, cytoplasm, and nucleus. Overexpression of PvNAC52 in Arabidopsis strengthened plant resilience to salt, alkali, osmotic, and ABA stresses. PvNAC52 significantly (p < 0.05) reduced the degree of oxidative damage to cell membranes, proline content, and plant water loss by increasing the expression of MSD1, FSD1, CSD1, POD, PRX69, CAT, and P5CS2. Moreover, the expression of genes associated with abiotic stress responses, such as SOS1, P5S1, RD29A, NCED3, ABIs, LEAs, and DREBs, was enhanced by PvNAC52 overexpression. A yeast one-hybrid assay showed that PvNAC52 specifically binds to the cis-acting elements ABRE (abscisic acid-responsive elements, ACGTG) within the promoter. This further suggests that PvNAC52 is responsible for the transcriptional modulation of abiotic stress response genes by identifying the core sequence, ACGTG. These findings provide a theoretical foundation for the further analysis of the targeted cis-acting elements and genes downstream of PvNAC52 in the common bean.

This study aimed to investigate the availability of flavonoids, anthocyanins, and phenolic acids in mutant bean seeds, focusing on M7 mutant lines, and their corresponding initial and local cultivars. HPLC-DAD-MS/MS and HPLC-MS/MS were used to analyze twenty-eight genotypes of common bean. The obtained results suggest that the mutations resulted in four newly synthesized anthocyanins in the mutant bean seeds, namely, delphinidin 3-O-glucoside, cyanidin 3-O-glucoside, pelargonidin 3-O-glucoside, and petunidin 3-O-glucoside, in 20 accessions with colored seed shapes out of the total of 28. Importantly, the initial cultivar with white seeds, as well as the mutant white seeds, did not contain anthocyanins. The mutant lines were classified into groups based on their colors as novel qualitative characteristics. Five phenolic acids were further quantified: ferulic, p-coumaric, caffeic, sinapic, and traces of chlorogenic acids. Flavonoids were represented by epicatechin, quercetin, and luteolin, and their concentrations in the mutant genotypes were several-fold superior compared to those of the initial cultivar. All mutant lines exhibited higher concentrations of phenolic acids and flavonoids. These findings contribute to the understanding of the genetics and biochemistry of phenolic accumulation and anthocyanin production in common bean seeds, which is relevant to health benefits and might have implications for common bean breeding programs and food security efforts.

The 11S globulin legumin typically accounts for approximately 3% of the total protein in common beans (Phaseolus vulgaris). It was previously reported that a legumin peptide of approximately 20 kDa is resistant to pepsin digestion. Sequence prediction suggested that the pepsin-resistant peptide is located at the C-terminal end of the α-subunit, within a glutamic acid-rich domain, overlapping with a chymotrypsin-resistant peptide. Using purified legumin, the peptide of approximately 20 kDa was found to be resistant to pepsin digestion in a pH-dependent manner, and its location was determined by two-dimensional gel electrophoresis and LC-MS-MS. The location of the chymotrypsin-resistant peptide was confirmed by immunoblotting with peptide-specific polyclonal antibodies. The presence of a consensus site for proline hydroxylation and arabinosylation, the detection of hydroxyproline residues, purification by lectin affinity chromatography, and a difference in electrophoretic migration between the chymotrypsin- and pepsin-resistant peptides suggest the presence of a large O-glycan within these peptides.

BACKGROUND: Disease can drastically impair common bean (Phaseolus vulgaris L.) production. Anthracnose, caused by the fungal pathogen Colletotrichum lindemuthianum (Sacc. and Magnus) Briosi and Cavara, is one of the diseases that are widespread and cause serious economic loss in common bean.
RESULTS: Transcriptome analysis of the early response of common bean to anthracnose was performed using two resistant genotypes, Hongyundou and Honghuayundou, and one susceptible genotype, Jingdou. A total of 9,825 differentially expressed genes (DEGs) responding to pathogen infection and anthracnose resistance were identified by differential expression analysis. By using weighted gene coexpression network analysis (WGCNA), 2,051 DEGs were found to be associated with two resistance-related modules. Among them, 463 DEGs related to anthracnose resistance were considered resistance-related candidate genes. Nineteen candidate genes were coexpressed with three resistance genes, Phvul.001G243600, Phvul.001G243700 and Phvul.001G243800. To further identify resistance genes, 46 candidate genes were selected for experimental validation using salicylic acid (SA) and methyl jasmonate (MeJA). The results indicated that 38 candidate genes that responded to SA/MeJA treatment may be involved in anthracnose resistance in common bean.
CONCLUSIONS: This study identified 38 resistance-related candidate genes involved in the early response of common bean, and 19 resistance-related candidate genes were coexpressed with anthracnose resistance genes. This study identified putative resistance genes for further resistance genetic investigation and provides an important reference for anthracnose resistance breeding in common bean.

Common bean provides diet rich in vitamins, fiber, minerals, and protein, which could contribute into food security of needy populations in many countries. Developing genotypes that associate favorable agronomic and grain quality traits in the common bean crop could increase the chances of adopting new cultivars black bean. In this context, the present study aimed at selection of superior black bean lines using multi-variate indexes, Smith-Hazel-index, and genotype by yield*trait biplot analysis. These trials were conducted in Campos dos Goytacazes - RJ, in 2020 and 2021. The experimental design used was randomized blocks, with 28 treatments and three replications. The experimental unit consisted of four rows 4.0 m long, spaced at 0.50 m apart, with a sowing density of 15 seeds per meter. The two central rows were used for the evaluations. The selection of superior genotypes was conducted using the multiple trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index, and Genotype by Yield*Trait Biplot (GYT). The multivariate indexes efficiently selected the best black bean genotypes, presenting desirable selection gains for most traits. The use of multivariate indexes and GYT enable the selection of early genotypes with higher grain yields. These lines G9, G13, G17, G23, and G27 were selected based on their performance for multiple traits closest to the ideotype and could be recommended as new varieties.