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.

Extraction of starch from waste is also an effective way to recover resources and provide new sources of starch. In this study, starch was isolated from white kidney bean residue, chickpea residue, and tiger nut meal after protein or oil extraction, and the morphology of starch particles was observed to determine their physicochemical properties and in vitro digestibility. All these isolated starches had unique properties, among which white kidney bean starch (KBS) had a high amylose content (43.48%), and its structure was better ordered. Scanning electron microscopy revealed distinct granular morphologies for the three starches. KBS and chickpea starch (CHS) were medium-granular starches, whereas tiger nut starch was a small granular starch. Fourier transform infrared spectroscopy analysis confirmed the absence of significant differences in functional groups and chemical bonds among the three starch molecules. In vitro digestibility studies showed that CHS is more resistant to enzymatic degradation. Overall, these results will facilitate the development of products based on the separation of nonconventional starches from waste.

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.

In this work, the metabolomics, physicochemical and in vitro digestion properties of black beans influenced by different calcium ion solutions (0, 0.5 %, 1 %, and 2 %) were explored. The addition of calcium ions had a significant effect on the metabolic processing of black beans, including 16 differential metabolites and 4 metabolic pathways related to the cell wall. From the results of FT-IR and ICP-OES, it was confirmed that calcium ions can interact with COO- in non-methylated galacturonic acid in pectin to form calcium carboxylate strengthening the middle lamellae of the cell wall. Based on this mechanism, the soaked beans with an intact and dense cell structure were verified by the analyses of SEM and CLSM. Compared with other soaked beans, BB-2 exhibited lower cell permeability with electrical conductivity value decreased to 0.60 μs·cm-1. Additionally, BB-2 demonstrated slower digestion properties with digestion rate coefficient at 0.0020 min-1 and digestion extent only at 30.83 %, which is attributed to its increasingly compact cell wall and densely cellular matrix. This study illustrates the effect of calcium ions on the cellular structure of black beans, providing an effective process method for low glycemic index diets.

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.

BACKGROUND: The phosphorylation of the Light-Harvesting Complex of photosystem II (LHCII) driven by STATE TRANSITION 7 (STN7) kinase is a part of one of the crucial regulatory mechanisms of photosynthetic light reactions operating in fluctuating environmental conditions, light in particular. There are evidenced that STN7 can also be activated without light as well as in dark-chilling conditions. However, the biochemical mechanism standing behind this complex metabolic pathway has not been deciphered yet.
RESULTS: In this work, we showed that dark-chilling induces light-independent LHCII phosphorylation in runner bean (Phaseolus coccineus L.). In dark-chilling conditions, we registered an increased reduction of the PQ pool which led to activation of STN7 kinase, subsequent LHCII phosphorylation, and possible LHCII relocation inside the thylakoid membrane. We also presented the formation of a complex composed of phosphorylated LHCII and photosystem I typically formed upon light-induced phosphorylation. Moreover, we indicated that the observed steps were preceded by the activation of the oxidative pentose phosphate pathway (OPPP) enzymes and starch accumulation.
CONCLUSIONS: Our results suggest a direct connection between photosynthetic complexes reorganization and dark-chilling-induced activation of the thioredoxin system. The proposed possible pathway starts from the activation of OPPP enzymes and further NADPH-dependent thioredoxin reductase C (NTRC) activation. In the next steps, NTRC simultaneously activates ADP-glucose pyrophosphorylase and thylakoid membrane-located NAD(P)H dehydrogenase-like complex. These results in starch synthesis and electron transfer to the plastoquinone (PQ) pool, respectively. Reduced PQ pool activates STN7 kinase which phosphorylates LHCII. In this work, we present a new perspective on the mechanisms involving photosynthetic complexes while efficiently operating in the darkness. Although we describe the studied pathway in detail, taking into account also the time course of the following steps, the biological significance of this phenomenon remains puzzling.