Banana (Musa spp.) is one of the most economically important horticultural crops. There are many types of banana, with differing ploidy (usually diploid, triploid, or tetraploid) and genome types (most containing the A or/and B genome). Currently, observation and genome type detection are commonly used to identify banana germplasm resources. However, observation is tedious, while genome type detection cannot distinguish categories below genome types. It is, therefore, urgent to establish a simple and effective method for identifying banana germplasm resources. This study sequenced and analyzed the ribosomal DNA internal transcribed spacer (ITS) sequences of 62 banana germplasm resources and found that the sequencing peaks, especially the 20 bp region near the 420-bp position (referred to as the 420-bp region), exhibited relatively recognizable and repeatable polymorphism characteristics. Using the 420-bp region as a marker, we were able to quickly distinguish bananas belonging to different genome type groups or different subgroups in the same genome type group. Moreover, it appeared that Sanger sequencing of ITS could be used to identify hybrid banana offspring. In general, ITS sequencing simplifies the classification of banana germplasm resources and has potential application in several areas of Musa improvement.

Foxtail millet (FM) and green banana (GB) are rich in health-promoting nutrients and bioactive substances, like antioxidants, dietary fibers, and various essential macro and micronutrients. Utilizing GB and FM flour as prebiotics is attributed to their ability to support gut health and offer multiple health benefits. The present study aimed to evaluate the impact of incorporating 10% GB flour (GBF) and different proportions (10-40%) of FM flour (FMF) on the prebiotic potential, antioxidant, nutrient, color, cooking quality, water activity and sensory attributes of noodles. The prebiotic potential, antioxidant, and nutrient of the produced noodles were significantly improved by increasing the levels of FMF. Sensorial evaluation revealed that noodles containing 30% FMF and 10% GBF attained comparable scores to the control sample. Furthermore, the formulated noodles exhibited significantly (p < 0.05) higher levels of protein, essential minerals (such as iron, magnesium, and manganese), dietary fiber (9.37 to 12.71 g/100 g), total phenolic compounds (17.81 to 36.35 mg GA eq./100 g), and total antioxidants (172.57 to 274.94 mg AA eq./100 g) compared to the control. The enriched noodles also demonstrated substantially (p < 0.05) increased antioxidant capacity, as evidenced by enhanced DPPH and FRAP activities, when compared to the control noodles. Overall, the incorporation of 30% FMF and 10% GBF led to a noteworthy improvement in the nutritional and antioxidant qualities of the noodles, as well as the prebiotic potential of the noodles with regard to L. plantarum, L. rhamnosus, and L. acidophilus. The implementation of this enrichment strategy has the potential to confer a multitude of health advantages.

Banana peels, comprising about 35% of the fruit\'s weight, are often discarded, posing environmental and economic issues. This research focuses on recycling banana peel waste by optimizing advanced extraction techniques, specifically microwave-assisted (MAE) and ultrasound-assisted extraction (UAE), for the isolation of phenolic compounds. A choline chloride-based deep eutectic solvent (DES) with glycerol in a 1:3 ratio with a water content of 30% (w/w) was compared to 30% ethanol. Parameters, including sample-to-solvent ratio (SSR), extraction time, and temperature for MAE or amplitude for UAE, were varied. Extracts were analyzed for hydroxycinnamic acid (HCA) and flavonoid content, and antioxidant activity using FRAP and ABTS assays. DES outperformed ethanol, with HCA content ranging from 180.80 to 765.92 mg/100 g and flavonoid content from 96.70 to 531.08 mg/100 g, accompanied by higher antioxidant activity. Optimal MAE conditions with DES were an SSR of 1:50, a temperature of 60 °C, and a time of 10 min, whereas an SSR of 1:60, time of 5 min, and 75% amplitude were optimal for UAE. The polyphenolic profile of optimized extracts comprised 19 individual compounds belonging to the class of flavonols, flavan-3-ols, and phenolic acids. This study concluded that DESs, with their superior extraction efficiency and environmental benefits, are promising solvents for the extraction of high-value bioactive compounds from banana peels and offer significant potential for the food and pharmaceutical industries.

The fruit processing industry is responsible for disposing of huge amounts of byproducts, especially fruit peels (FPs), which are often discarded in landfills. Using FPs in biotechnological processes contributes to a circular economy, reducing the environmental burden of FPs and increasing the revenue of the fruit processing industry. This study was focused on upgrading the nutritional value of orange (OPs) and banana (BPs) peels by solid-state fermentation (SSF) with filamentous fungi. SSF factors (moisture, fermentation time, inoculum size, ammonium sulfate (AS), and corn steep liquor (CSL)) and fungi species (Aspergillus ibericus and Rhizopus oryzae) were studied by a variable screening Plackett-Burman design. Both fungi grew on untreated FPs, increasing their protein content and antioxidant activity. Moisture, AS, and CSL were further studied by a Box-Behnken design with A. ibericus. Fermented OPs at 70% moisture and 0.005 g/g AS increased their protein content by 200%, whereas BPs at 70% moisture and 0.005 g/g CSL increased by 123%. Fermented peels were enriched in protein, fiber, and minerals, with a low content of carbohydrates and soluble sugars. Fermented OPs and BPs showed higher antioxidant activity than unfermented peels. The SSF of these FPs is an innovative approach that contributes to obtaining rich nutrient-fermented peels for food.

Banana Fusarium wilt, caused by Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4), is a major disease of banana plants worldwide. Effector proteins play critical roles in banana-Foc TR4 interaction. Our previous studies highlighted a ribonuclease protein belonging to the T2 family (named as FocRnt2) in the Foc TR4 secretome, which was predicted to be an effector. However, its biological function in Foc TR4 infection is still unclear. Herein, we observed significant expression of FocRnt2 during the early stage of fungal infection in planta. A yeast signal sequence trap assay showed that FocRnt2 contained a functional signal peptide for secretion. FocRnt2 possessed ribonuclease activity that could degrade the banana total RNA in vitro. Subcellular localization showed that FocRnt2 was localized in the nucleus and cytoplasm of Nicotiana benthamiana leaves. Transient expression of FocRnt2 suppressed the expression of salicylic acid- and jasmonic acid-signalling marker genes, reactive oxygen species accumulation, and BAX-mediated cell death in N. benthamiana. FocRnt2 deletion limited fungal penetration, reduced fusaric acid biosynthesis in Foc TR4, and attenuated fungal virulence against banana plants, but had little effect on Foc TR4 growth and sensitivity to various stresses. Furthermore, FocRnt2 deletion mutants induced higher expression of the defence-related genes in banana plants. These results suggest that FocRnt2 plays an important role in full virulence of Foc TR4, further improving our understanding of effector-mediated Foc TR4 pathogenesis.

Alpha-amylase (AMY) plays a significant role in regulating the growth, development, and postharvest quality formation in plants. Nevertheless, little is known about the genome-wide features, expression patterns, subcellular localization, and functional regulation of AMY genes (MaAMYs) in the common starchy banana (Musa acuminata). Twelve MaAMY proteins from the banana genome database were clustered into two groups and contained a conserved catalytic domain. These MaAMYs formed collinear pairs with the AMYs of maize and rice. Three tandem gene pairs were found within the MaAMYs and are indicative of putative gene duplication events. Cis-acting elements of the MaAMY promoters were found to be involved in phytohormone, development, and stress responses. Furthermore, MaAMY02, 08, 09, and 11 were actively expressed during fruit development and ripening. Specifically, MaAMY11 showed the highest expression level at the middle and later stages of banana ripening. Subcellular localization showed that MaAMY02 and 11 were predominately found in the chloroplast, whereas MaAMY08 and 09 were primarily localized in the cytoplasm. Notably, transient attenuation of MaAMY11 expression resulted in an obvious increase in the starch content of banana fruit, while a significant decrease in starch content was confirmed through the transient overexpression of MaAMY11. Together, these results reveal new insights into the structure, evolution, and expression patterns of the MaAMY family, affirming the functional role of MaAMY11 in the starch degradation of banana fruit.

Banana (Musa spp.) is the most widely consumed fruit globally. Fusarium wilt, caused by Fusarium oxysporum f. sp. cubense (Foc), is a highly threatening disease to banana production. Resistance genes to Foc exist in wild Musa genotypes such as Musa acuminata subsp. burmannicoides var. Calcutta 4. Whilst real-time PCR (RT-qPCR) is appropriate for accurate analysis of gene expression in pathways involved in host defence responses, reference genes with stable expression under specific biotic stress conditions and host tissue types are necessary for normalization of sample variation. In this context, the stability in potential host reference genes ACT1, APT, EF1α, GAPDH, αTUB, RAN, UBIQ1, UBIQ2, βTUB1, βTUB3, L2 and ACTA1 was evaluated in total RNA samples from root tissues in Calcutta 4 (resistant) and Musa sp. cultivar Prata-anã (susceptible) extracted during interaction with Foc subtropical race 4 (STR4). Expression stability was calculated using the algorithms geNorm, NormFinder and BestKeeper. βTUB3 and L2 were identified as the most stable in Calcutta 4, with ACTA1 and GAPDH the most stable in Prata-anã. These reference genes for analysis of gene expression modulation in the Musa-Foc STR4 pathosystem are fundamental for advancing understanding of host defence responses to this important pathogen.

Fusarium oxysporum f. sp. cubense (Foc) poses a significant threat to banana crops as a lethal fungal pathogen. The global spread of Foc underscores the formidable challenges associated with traditional management methods in combating this pathogen. This study delves into the hypovirulence-associated mycovirus in Foc. From Foc strain LA6, we isolated and characterized a novel member of the Hadakaviridae family, named Hadaka virus 1 strain LA6 (HadV1-LA6). HadV1-LA6 comprises 10 genomic RNA segments, with RNA1 to RNA7 sharing 80.9%-95.0% amino acid sequence identity with known HadV1-7n, while RNA8 to RNA10 display significantly lower identity. HadV1-LA6 demonstrates horizontal transmission capabilities in an all-or-none fashion between different Foc strains via coculturing. Phenotypic comparisons highlight that HadV1-LA6 significantly reduces the growth rates of its host fungus under cell wall stress and oxidative stress conditions. Importantly, HadV1-LA6 attenuates Foc\'s virulence in detached leaves and banana plants. This study represents the first introduction of a novel hypovirulence-associated Hadaka virus 1 in Foc.IMPORTANCEFusarium wilt of banana (FWB) is a severe fungal disease caused by soil-borne Fusarium oxysporum f. sp. cubense (Foc). Among various strategies, biocontrol emerges as a safe, ecologically friendly, and cost-effective approach to managing FWB. In this study, we focus on exploring the potential of a novel hypovirulent member of hadakavirid, HadV1-LA6. Previous reports suggest that HadV1 shows no apparent effect on the host. However, through phenotypic assessments, we demonstrate that HadV1-LA6 significantly impedes the growth rates of its host fungus under stress conditions. More importantly, HadV1-LA6 exhibits a remarkable capacity to attenuate Foc\'s virulence in detached leaves and banana plants. Furthermore, HadV1-LA6 could be horizontally transmitted between different Foc strains, presenting a promising resource for revealing the molecular mechanism of the interaction between Hadaka virus 1 and its host.

The Indian economy is greatly influenced by the Banana Industry, necessitating advancements in agricultural farming. Recent research emphasizes the imperative nature of addressing diseases that impact Banana Plants, with a particular focus on early detection to safeguard production. The urgency of early identification is underscored by the fact that diseases predominantly affect banana plant leaves. Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. This manuscript examines the prediction and detection of diseases in banana leaves, exploring various diseases, machine learning algorithms, and methodologies. The study makes a contribution by proposing two approaches for improved performance and suggesting future research directions. In summary, the objective is to advance understanding and stimulate progress in the prediction and detection of diseases in banana leaves. The need for enhanced disease identification processes is highlighted by the results of the survey. Existing models face a challenge due to their lack of rotation and scale invariance. While algorithms such as random forest and decision trees are less affected, initially convolutional neural networks (CNNs) is considered for disease prediction. Though the Convolutional Neural Network models demonstrated impressive accuracy in many research but it lacks in invariance to scale and rotation. Moreover, it is observed that due its inherent design it cannot be combined with feature extraction methods to identify the banana leaf diseases. Due to this reason two alternative models that combine ANN with scale-invariant Feature transform (SIFT) model or histogram of oriented gradients (HOG) combined with local binary patterns (LBP) model are suggested. The first model ANN with SIFT identify the disease by using the activation functions to process the features extracted by the SIFT by distinguishing the complex patterns. The second integrate the combined features of HOG and LBP to identify the disease thus by representing the local pattern and gradients in an image. This paves a way for the ANN to learn and identify the banana leaf disease. Moving forward, exploring datasets in video formats for disease detection in banana leaves through tailored machine learning algorithms presents a promising avenue for research.

Ethylene and ethylene oxide are widely used in the chemical industry, and ethylene is also important for its role in fruit ripening. Better sensing systems would assist risk management of these chemicals. Here, we characterise the ethylene regulatory system in Mycobacterium strain NBB4 and use these genetic parts to create a biosensor. The regulatory genes etnR1 and etnR2 and cognate promoter Petn were combined with a fluorescent reporter gene (fuGFP) in a Mycobacterium shuttle vector to create plasmid pUS301-EtnR12P. Cultures of M. smegmatis mc2-155(pUS301-EtnR12P) gave a fluorescent signal in response to ethylene oxide with a detection limit of 0.2 μM (9 ppb). By combining the epoxide biosensor cells with another culture expressing the ethylene monooxygenase, the system was converted into an ethylene biosensor. The co-culture was capable of detecting ethylene emission from banana fruit. These are the first examples of whole-cell biosensors for epoxides or aliphatic alkenes. This work also resolves long-standing questions concerning the regulation of ethylene catabolism in bacteria.