Search Results (211)

Microbe–microbe interactions have been explored at the molecular level to a lesser degree than plant–pathogen interactions, primarily due to the economic impact of crop losses caused by pathogenic microorganisms. Effector proteins are well known for their role in disease development in many plant–pathogen pleinteractions, but there is increasing evidence showing their involvement in other types of interaction, including microbe–microbe interactions. Through the use of LC-MS/MS sequencing, effector candidates were identified in the in vitro interaction between a banana pathogen, Pseudocercospora fijiensis and a biological control agent, Trichoderma harzianum. The diverse interaction secretome revealed various glycoside hydrolase families, proteases and oxidoreductases. T. harzianum secreted more proteins in the microbial interaction compared to P. fijiensis, but its presence induced the secretion of more P. fijiensis proteins that were exclusive to the interaction secretome. The interaction secretome, containing 256 proteins, was screened for effector candidates using the algorithms EffHunter and WideEffHunter. Candidates with common fungal effector motifs and domains such as LysM, Cerato-platanin, NPP1 and CFEM, among others, were identified. Homologs of true effectors and virulence factors were found in the interaction secretome of T. harzianum and P. fijiensis. Further characterization revealed a potential novel effector of T. harzianum. Full article

Radopholus similus, commonly known as the burrowing nematode, is one of the major pathogens affecting banana production. Currently, the control of this pathogen relies on chemicals, as no resistant varieties are available. However, new control methods, such the application of ensilage biostimulants (EBs) near the banana rhizosphere, have shown effectiveness. Nevertheless, the impact of this organic control method on soil nematodes and other microbial components remains unknown. This study evaluates the effects of EB application on the native nematofauna of banana. EBs altered the flow of carbon, nutrients, and energy in ways that influenced the abundance of fungivorous and bacterivorous taxa, while consistently reducing the number of plant-parasitic nematodes throughout the experimental period. Specifically, EB application in the soil increased the abundance of certain free-living nematodes, including Aphelenchus, Aphelenchoides, Cephalobidae, and Rhabditidae, while decreasing both the abundance and diversity of phytoparasitic nematodes. In contrast, Criconematidae, Hoplolaimidae, Meloidogyne, Tylenchidae, and R. similis were more abundant in the control and oxamyl-treated soils. EBs can play a crucial role in strategies aimed to improve soil resilience, fertility, and natural suppression, provided that more sustainable production practices are adopted. Full article

Banana Fusarium wilt (BFW, also known as Panama disease) is a highly infectious and destructive disease that threatens global banana production, requiring early recognition for timely prevention and control. Current monitoring methods primarily rely on continuous variable features—such as band reflectances (BRs) and vegetation indices (VIs)—collectively referred to as basic features (BFs)—which are prone to noise during the early stages of infection and struggle to capture subtle spectral variations, thus limiting the recognition accuracy. To address this limitation, this study proposes a discretized enhanced feature (EF) construction method, the automated kernel density segmentation-based feature construction algorithm (AutoKDFC). By analyzing the differences in the kernel density distributions between healthy and diseased samples, the AutoKDFC automatically determines the optimal segmentation threshold, converting continuous BFs into binary features with higher discriminative power for early-stage recognition. Using UAV-based multi-spectral imagery, BFW recognition models are developed and tested with the random forest (RF), support vector machine (SVM), and Gaussian naïve Bayes (GNB) algorithms. The results show that EFs exhibit significantly stronger correlations with BFW’s presence than original BFs. Feature importance analysis via RF further confirms that EFs contribute more to the model performance, with VI-derived features outperforming BR-based ones. The integration of EFs results in average performance gains of 0.88%, 2.61%, and 3.07% for RF, SVM, and GNB, respectively, with SVM achieving the best performance, averaging over 90%. Additionally, the generated BFW distribution map closely aligns with ground observations and captures spectral changes linked to disease progression, validating the method’s practical utility. Overall, the proposed AutoKDFC method demonstrates high effectiveness and generalizability for BFW recognition. Its core concept of “automatic feature enhancement” has strong potential for broader applications in crop disease monitoring and supports the development of intelligent early warning systems in plant health management. Full article

Bananas and plantains, belonging to the Musa genus, are important food crops that sustain the livelihoods of countless smallholder farmers globally. However, their production is hindered by various challenges, including abiotic and biotic stresses, climate change, and poor access to clean planting materials, which negatively impact their yields. Addressing these constraints is essential for improving production and ensuring food security. This study investigated the influence of triploid genome background and exogenous growth regulators on the regeneration of Musa cultivars [Gros Michel (AAA genome), Obino l’Ewai and Silk (AAB genome), and Poteau Naine (ABB genome)]. Shoot tip explants of the AAA, AAB, and ABB triploid genomes were cultured in Murashige and Skoog (MS) media supplemented with varying 6-benzylaminopurine (BAP) and indole-3-butyric acid (IBA), indole-3-acetic acid (IAA), or naphthaleneacetic acid (NAA) hormones. Shoot induction was successfully achieved within 21.50 ± 2.00 days, with AAA exhibiting the highest shoot induction frequencies ranging from 30.00 ± 1.57% to 100% and shoot numbers per explant ranging from 3.00 ± 0.50 to 8.80 ± 0.80, followed by the ABB genome ranging from 20.00 ± 3.45% to 100% and from 2.00 ± 0.55 to 5.60 ± 0.50 shoots, and the AAB genome ranging from 17.50 ± 5.01% to 100% and from 2.00 ± 0.04 to 6.60 ± 0.25 shoots, respectively, in media amended with 1.2 to 6.0 mg.L⁻¹ BAP and 0.1 mg.L⁻¹ IAA. The highest rooting rate of 100% was recorded in all three genomes in media containing 1.4 mg.L⁻¹ IBA and 0.5 mg.L⁻¹ IAA, with the AAA genome producing the maximum number of 14.8 roots per explant. The results indicate the positive influence of the AAA genome background on in vitro regeneration and its potential utilization for genomic editing transformation protocols Full article

Banana is an important cash and food crop worldwide. Recent outbreaks of banana diseases are threatening the global banana industry and smallholder livelihoods. Remote sensing data offer the potential to detect the presence of disease, but formal analysis is needed to compare inferred disease data with observed disease data. In this study, we present a novel remote-sensing-based framework that combines Landsat-8 imagery with meteorology-informed phenological models and machine learning to identify anomalies in banana crop health. Unlike prior studies, our approach integrates domain-specific crop phenology to enhance the specificity of anomaly detection. We used a pixel-level random forest (RF) model to predict 11 key vegetation indices (VIs) as a function of historical meteorological conditions, specifically daytime and nighttime temperature from MODIS and precipitation from NASA GES DISC. By training on periods of healthy crop growth, the RF model establishes expected VI values under disease-free conditions. Disease presence is then detected by quantifying the deviations between observed VIs from Landsat-8 imagery and these predicted healthy VI values. The model demonstrated robust predictive reliability in accounting for seasonal variations, with forecasting errors for all VIs remaining within 10% when applied to a disease-free control plantation. Applied to two documented outbreak cases, the results show strong spatial alignment between flagged anomalies and historical reports of banana bunchy top disease (BBTD) and Fusarium wilt Tropical Race 4 (TR4). Specifically, for BBTD in Australia, a strong correlation of 0.73 was observed between infection counts and the discrepancy between predicted and observed NDVI values at the pixel with the highest number of infections. Notably, VI declines preceded reported infection rises by approximately two months. For TR4 in Mozambique, the approach successfully tracked disease progression, revealing clear spatial spread patterns and correlations as high as 0.98 between VI anomalies and disease cases in some pixels. These findings support the potential of our method as a scalable early warning system for banana disease detection. Full article

The genetic diversity of banana plants (Musa spp.) can result in different phosphorus requirements, highlighting the importance of studies performed to optimize phosphate fertilization in order to improve the productivity and sustainability of banana plantations. This study assessed the effects of phosphate fertilization on the duration of the harvest season, bunch mass, soil fertility and foliar nutrition of BRS SCS Belluna banana plants. A replicated trial was performed in two consecutive harvests, with different phosphorus levels, i.e., 25, 50, 75, 100, 125 and 150% of the recommended level for the crop. Soil analyses included macro- and micronutrients, silicon, acidity, organic matter, cation exchange capacity and base saturation. Leaf tissue was analyzed for mineral content. Thermophosphate had different effects on soil fertility and leaf nutrients. Calcium and phosphorus in the soil increased linearly. In the leaf, a reduction in zinc content was mainly observed. The lower temperatures and accumulated rainfall that occurred during the second harvest season are related to a greater number of days between flowering and harvest and a lower bunch mass. These results could support fertilization programs aimed at ensuring the long-term sustainability of phosphorus nutrition in banana plantations. Full article

The sterol demethylation inhibitors (DMIs) are among the most widely used fungicides for controlling black Sigatoka (Mycosphaerella fijiensis) and yellow Sigatoka (Mycosphaerella musicola) in banana plantations in Brazil. Black Sigatoka is considered more important due to causing yield losses of up to 100% in commercial banana crops under predisposing conditions. In contrast, yellow Sigatoka is important due to its widespread occurrence in the country. This study aimed to determine the current sensitivity levels of Mf and Mm populations to DMI fungicides belonging to the chemical group of triazoles. Populations of both species were sampled from commercial banana plantations in Registro, Vale do Ribeira, São Paulo (SP), Ilha Solteira, Northwestern SP, and Janaúba, Northern Minas Gerais, and were further characterized phenotypically. Additionally, allelic variation in the CYP51 gene was analyzed in populations of these pathogens to identify and characterize major mutations and/or mechanisms potentially associated with resistance. Sensitivity to the triazoles propiconazole and tebuconazole was determined by calculating the 50% inhibitory concentration of mycelial growth (EC₅₀) based on dose–response curves ranging from 0 to 5 µg mL⁻¹. Variation in sensitivity to fungicides was evident with all nine Mf isolates showing moderate resistance levels to both propiconazole or tebuconazole, while 11 out of 42 Mm strains tested showed low to moderate levels of resistance to these triazoles. Mutations leading to CYP51 substitutions Y136F, Y461N/H, and Y463D in Mm and Y461D, G462D, and Y463D in Mf were associated with low or moderate levels of resistance to the triazoles. Interestingly, Y461H have not been reported before in Mm or Mf populations, and this alteration was found in combination with V106D and A446S. More complex CYP51 variants and CYP51 promoter inserts associated with upregulation of the target protein were not detected and can explain the absence of highly DMI-resistant strains in Brazil. Disease management programs that minimize reliance on fungicide sprays containing triazoles will be needed to slow down the further evolution and spread of novel CYP51 variants in Mf and Mm populations in Brazil. Full article

Foliar diseases caused by various fungi severely affect the yield and quality of banana crops. This study was conducted to clarify the biological characteristics of Bipolaris oryzae (teleomorph: Cochliobolus miyabeanus), a pathogen reported in 2023 as a new etiological agent of leaf spot in the banana variety ‘Pisang Mas’ (Musa acuminata, AA group) in Hainan Province, China, and to screen effective fungicides for its control. The results indicated that banana leaf extract agar (BLEA) and cornmeal agar (CMA) were the best media for the growth and sporulation of the pathogen, respectively. The pathogen grew best on a Czapek’s agar (CZA) medium with sucrose as a carbon source and yeast extract as a nitrogen source, while the optimal carbon and nitrogen sources for sporulation were lactose and beef extract, respectively. The pathogen could grow within a temperature range from 5 °C to 35 °C, and the optimal temperatures for growth and sporulation were 30 °C and 25 °C, respectively. Exposure to 50 °C for 10 min was lethal. Additionally, the pathogen could grow and sporulate within pH ranges of 4 to 10 and 4 to 9, respectively, and the optimal pH values for growth and sporulation were 5 and 8, respectively. The optimal photoperiods for growth and sporulation were 16 h light/8 h dark and 24 h light, respectively. Among the 12 tested fungicides, 500 g/L of iprodione SC showed the highest toxicity against B. oryzae, with an EC₅₀ value of 0.08 μg/mL, followed by 30% difenoconazole-azoxystrobin SC and 125 g/L of epoxiconazole SC, with EC₅₀ values of 0.13 μg·mL⁻¹ and 0.20 μg/mL, respectively. A fungicide containing 40% chlorothalonil SC had the poorest fungicidal activity, with an EC₅₀ value of 155.98 μg/mL. An artificial inoculation pot experiment showed that 125 g/L of epoxiconazole SC at 250 μg/mL, 500 g/L of iprodione SC at 1667 μg/mL, and 30% difenoconazole-azoxystrobin SC at 250 μg/mL provided a protective control efficacy of 100% against B. oryzae, while 125 g/L of epoxiconazole SC at 250 μg/mL and 500 g/L of iprodione SC at 1667 μg/mL provided a curative control efficacy of greater than 60%. This study clarified the optimal conditions for the mycelial growth and sporulation of B. oryzae isolated from banana and screened out fungicides with effective inhibitory activities. These results can provide guidance for field applications and the management of leaf spot caused by B. oryzae in banana. Full article

Fusarium oxysporum f. sp. cubense (Foc) causes Fusarium wilt, a devastating epidemic disease that has caused widespread damage to banana crops worldwide. We report the draft genomes of Foc race 1 (16117) and Foc tropical race 4 (Fusarium odoratissimum) (CNSD1) isolates from China, assembled using PacBio HiFi sequencing reads, with functional annotation performed. The strains group in distinct lineages within the Fusarium oxysporum species complex. This genetic resource will contribute towards understanding the pathogenicity and evolutionary dynamics of Foc populations in banana-growing regions around the world. Full article

Spent mushroom substrate (SMS), a waste product from mushroom cultivation, in addition to being rich in essential nutrients for crop growth, contains actively growing mushroom mycelia and metabolites that suppress some plant pathogens and pests. SMS thus has potential for fostering the suppressiveness of soil-borne pathogens of farms. This study determined the potential of using the spent Pleurotus ostreatus substrate (SPoS) to suppress the plant-parasitic nematode Radopholus similis in bananas. R. similis is the most economically important nematode in bananas worldwide. The effect of SPoS on R. similis was assessed through two in vivo (potted plants) experiments between May 2023 and June 2024. Five-month-old East African highland banana (genome AAA) plantlets that are highly susceptible to R. similis were used. In the first experiment, the plantlets were established in 3 L pots containing (i) pre-sterilized soil, (ii) pre-sterilized soil inoculated with nematodes, (iii) pre-sterilized soil mixed with 30% (v/v) SPoS, (iv) pre-sterilized soil mixed with 30% (v/v) SPoS followed by nematode inoculation, (v) SPoS without soil, and (vi) SPoS without soil inoculated with nematodes. The SPoS was already decomposed; thus, it may or may not have contained active mycelia. The nematodes were introduced two weeks after the SPoS application. In the second experiment, SPoS was introduced two weeks after nematode inoculation. The SPoS treatments without soil were not evaluated in the second experiment. Both experiments were monitored over a three-month period. Each screenhouse treatment contained four plants and was replicated thrice. In the first experiment, data were collected on changes in soil nutrient content, below- and aboveground biomass, root deaths, root necrosis due to nematode damage, and R. similis population in root tissues and soil. In the second experiment, data were collected on root deaths and the number of nematodes in root tissues and the soil. The SPoS improved crop biomass yield, reduced root damage, and colonization by R. similis. The potential of SPoS to improve the management of R. similis and banana production under field conditions needs to be determined. Full article

This paper explores the role of agroforestry in sequestering atmospheric carbon in the tropics and subtropics, specifically in the Madhupur Sal forest of Bangladesh. Agroforestry, combining trees with crops on agricultural lands, is recognized for its potential to act as a carbon sink and enhance productivity. The study assesses various agroforestry practices, including acacia–pineapple–turmeric–papaya, acacia–pineapple–ginger–banana, and sal–pineapple–aroid combinations. This study innovatively assessed both the carbon sequestration and economic viability of agroforestry in the Madhupur Sal forest, presenting a sustainable land-use model that balances environmental benefits and farm profitability. The research reveals improved farm productivity in these agroforestry systems, with different tree species sequestering varying amounts of carbon. Acacia species, ranging from 12 to 25 ft in height, sequestered an average of 23.35 lbs/year, while sal species (Shorea robusta), with trees 45 to 61 ft tall, sequestered 49.80 lbs/year on average. Factors such as tree height, diameter at breast height (DBH), number of leaves, and branches influence carbon sequestration. The paper suggests that the carbon sequestration (CS) potential of agroforestry results in greenhouse gas emission reduction in Bangladesh. By emphasizing the profitability of these practices alongside carbon sequestration, the study encourages the adoption of agroforestry as a sustainable and economically viable strategy. Full article

Banana is a commercially important crop widely cultivated in tropical and subtropical regions, but its cultivation in the canal command basins is challenged due to the development of waterlogged sodic soils. The present study aimed to induce sodicity tolerance through the integration of secondary metabolites in the plants during the tissue culture organogenesis phase. Secondary-metabolite-treated plants were assessed for their performance in the waterlogged sodic soil areas of Samesee block in Lucknow district of Uttar Pradesh, India. Metabolite-treated (MT) plants exhibited significantly better growth and yield compared to untreated control (UTC) plants. Key physiological enhancements in MT plants included increased activities of defense-related enzymes superoxide dismutase (SOD), phenylalanine ammonia lyase (PAL), peroxidase (POD), and proline along with a reduced Na⁺/K⁺ ratio. The metabolic profile of MT plants showed higher expression of antioxidants, phenolic compounds, and flavonoids. MT plants exhibited production of the metabolites such as trihydroxy methylene–di-oxyflavone, rush flavanone, rutin, anthocyanins, neodiosmin, arachidonic acid, and trigalloyl-HHDP-glucose, which belongs to the subclasses of flavonoids, anthocyanins, and sugar alcohols. Consequently, MT plants produced a significantly higher yield (20.85 kg per plant) compared to UTC plants (8.35 kg) and greater biomass. These results suggest that treatments using secondary metabolite extracted from salt-tolerant bacteria can be used as an effective strategy for enhancing sodicity tolerance in banana plants, contributing to sustainable production and economic viability in waterlogged sodic soil conditions. Full article

Lemongrass (Cymbopogon citratus) has potential for intercropping with banana (Musa spp.) plants, thus contributing to the sustainability of plantations. The study evaluated the growth and yield of ‘Prata Anã’ banana and seasonality, yield and essential oil properties of lemongrass grown in intercropping and the land equivalent ratio. A randomized block design in a split plot arrangement was used, evaluating two cropping systems (sole crop and intercropping) and three harvest seasons during the year for lemongrass and two harvest seasons for banana, separately. The banana can be intercropped with lemongrass without interfering with its growth and production. The biomass production and essential oil yield of lemongrass differed according to cropping system and seasonality. The chemical composition of the essential oil showed stability in the concentration of citral (mixture of neral and geranial), with an average of 94.43%. Seasonal variations were observed in the content of these compounds and other components of the essential oil, emphasizing the importance of the time of harvest in the overall value of the oil. The result demonstrates the viability of intercropping, which not only provides crop yields for both species and produces more per unit area than a sole crop but also optimizes the use of resources and promotes more sustainable farming practices. Full article

Leaf diseases, such as Black Sigatoka and Cordana, represent a growing threat to banana crops in Ecuador. These diseases spread rapidly, impacting both leaf and fruit quality. Early detection is crucial for effective control measures. Recently, deep learning has proven to be a powerful tool in agriculture, enabling more accurate analysis and identification of crop diseases. This study applied the CRISP-DM methodology, consisting of six phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. A dataset of 900 banana leaf images was collected—300 of Black Sigatoka, 300 of Cordana, and 300 of healthy leaves. Three pre-trained models (EfficientNetB0, ResNet50, and VGG19) were trained on this dataset. To improve performance, data augmentation techniques were applied using TensorFlow Keras’s ImageDataGenerator class, expanding the dataset to 9000 images. Due to the high computational demands of ResNet50 and VGG19, training was performed with EfficientNetB0. The models—EfficientNetB0, ResNet50, and VGG19—demonstrated the ability to identify leaf diseases in bananas, with accuracies of 88.33%, 88.90%, and 87.22%, respectively. The data augmentation increased the performance of EfficientNetB0 to 87.83%, but did not significantly improve its accuracy. These findings highlight the value of deep learning techniques for early disease detection in banana crops, enhancing diagnostic accuracy and efficiency. Full article

Banana is the second-highest fruit produced in the world and is a staple food for over 400 million people. Only 40% of the crop is utilised, leading to 114 million tonnes of banana waste annually. Banana peel constitutes about ~40% of the whole fruit, and it is considered a domestic and food industry waste. It is enriched with macronutrients, micronutrients and bioactive compounds, which can provide antioxidant, anti-microbial, antibiotic, pharmaceutical and nutraceutical properties. Banana peels also have higher nutrient value than banana pulp, and they are used in traditional medicines to treat diabetes, diarrhoea, inflammation, ulcers, burns and cough. Given its diverse bioactive properties, banana peel waste is now being explored within the framework of a circular economy to promote waste recycling and reduce environmental impact. This review highlights the nutritional and health properties of banana peel while providing opportunities for waste reduction. Potential applications of banana peels include anti-cancer and anti-fungal agents, biosorbents, natural emulsifiers, reducing agents, biofertilisers, food industry ingredients for bakery products, natural preservatives and food fortification. Exploring banana peel waste potential not only contributes to sustainable waste management but also enhances environmentally friendly innovation for the benefit of human health and the environment. Full article