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Early detection of black Sigatoka in banana leaves using hyperspectral images

ABSTRACT: Premise Black Sigatoka is one of the most severe banana (Musa spp.) diseases worldwide, but no methods for the rapid early detection of this disease have been reported. This paper assesses the use of hyperspectral images for the development of a partial?least?squares penalized?logistic?regression (PLS–PLR) model and a hyperspectral biplot (HS biplot) as a visual tool for detecting the early stages of black Sigatoka disease. Methods Young (three?month?old) banana plants were inoculated with a conidia suspension of the black Sigatoka fungus (Pseudocercospora fijiensis). Selected infected and control plants were evaluated using a hyperspectral imaging system at wavelengths in the range of 386–1019 nm. PLS–PLR models were run on the hyperspectral data set. The prediction power was assessed using leave?one?out cross?validation as well as external validation. Results The PLS–PLR model was able to predict the presence of the disease with a 98% accuracy. The wavelengths with the highest contribution to the classification ranged from 577 to 651 nm and from 700 to 1019 nm. Discussion PLS–PLR and HS biplot effectively estimated the presence of black Sigatoka disease at the early stages and can be used to graphically represent the relationship between groups of leaves and both visible and near?infrared wavelengths.

SUBMITTER: Ugarte Fajardo J

PROVIDER: S-EPMC7507400 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Project description:The haploid fungus Pseudocercospora fijiensis causes black Sigatoka in banana and is chiefly controlled by extensive fungicide applications, threatening occupational health and the environment. The 14α-Demethylase Inhibitors (DMIs) are important disease control fungicides, but they lose sensitivity in a rather gradual fashion, suggesting an underlying polygenic genetic mechanism. In spite of this, evidence found thus far suggests that P. fijiensis cyp51 gene mutations are the main responsible factor for sensitivity loss in the field. To better understand the mechanisms involved in DMI resistance, in this study we constructed a genetic map using DArTseq markers on two F1 populations generated by crossing two different DMI resistant strains with a sensitive strain. Analysis of the inheritance of DMI resistance in the F1 populations revealed two major and discrete DMI-sensitivity groups. This is an indicative of a single major responsible gene. Using the DMI-sensitivity scorings of both F1 populations and the generation of genetic linkage maps, the sensitivity causal factor was located in a single genetic region. Full agreement was found for genetic markers in either population, underlining the robustness of the approach. The two maps indicated a similar genetic region where the Pfcyp51 gene is found. Sequence analyses of the Pfcyp51 gene of the F1 populations also revealed a matching bimodal distribution with the DMI resistant. Amino acid substitutions in P. fijiensis CYP51 enzyme of the resistant progeny were previously correlated with the loss of DMI sensitivity. In addition, the resistant progeny inherited a Pfcyp51 gene promoter insertion, composed of a repeat element with a palindromic core, also previously correlated with increased gene expression. This genetic approach confirms that Pfcyp51 is the single explanatory gene for reduced sensitivity to DMI fungicides in the analysed P. fijiensis strains. Our study is the first genetic analysis to map the underlying genetic factors for reduced DMI efficacy.

Project description:Banana (Musa spp.) is an important crop worldwide, but black Sigatoka disease caused by the fungus Pseudocercospora fijiensis threatens fruit production. In this work, we examined the potential of the endophytes of banana plants Enterobacter cloacae and Klebsiella pneumoniae, as antagonists of P. fijiensis and support plant growth in nutrient limited soils by N-transfer. The two bacterial isolates were identified by MALDI-TOF mass spectrometry and corroborated by 16S rRNA sequence analysis. Both bacteria were positive for beneficial traits such as N-fixation, indole acetic acid production, phosphate solubilization, negative for 1-aminocyclopropane 1-carboxylic acid deaminase and were antagonistic to P. fijiensis. To measure the effects on plant growth, the two plant bacteria and an E. coli strain (as non-endophyte), were inoculated weekly for 60 days as active cells (AC) and heat-killed cells (HKC) into plant microcosms without nutrients and compared to a water only treatment, and a mineral nutrients solution (MMN) treatment. Bacterial treatments increased growth parameters and prevented accelerated senescence, which was observed for water and mineral nutrients solution (MMN) treatments used as controls. Plants died after the first 20 days of being irrigated with water; irrigation with MMN enabled plants to develop some new leaves, but plants lost weight (-30%) during the same period. Plants treated with bacteria showed good growth, but E. cloacae AC treated plants had significantly greater biomass than the E. cloacae HKC. After 60 days, plants inoculated with E. cloacae AC showed intracellular bacteria within root cells, suggesting that a stable symbiosis was established. To evaluate the transference of organic N from bacteria into the plants, the 3 bacteria were grown with 15NH4Cl or Na15NO3 as the nitrogen source. The 15N transferred from bacteria to plant tissues was measured by pheophytin isotopomer abundance. The relative abundance of the isotopomers m/z 872.57, 873.57, 874.57, 875.57, 876.57 unequivocally demonstrated that plants acquired 15N atoms directly from bacterial cells, using them as a source of N, to support plant growth in restricted nutrient soils. E. cloacae might be a new alternative to promote growth and health of banana crops.

Project description:Black Sigatoka or black leaf streak disease, caused by the Dothideomycete fungus Pseudocercospora fijiensis (previously: Mycosphaerella fijiensis), is the most significant foliar disease of banana worldwide. Due to the lack of effective host resistance, management of this disease requires frequent fungicide applications, which greatly increase the economic and environmental costs to produce banana. Weekly applications in most banana plantations lead to rapid evolution of fungicide-resistant strains within populations causing disease-control failures throughout the world. Given its extremely high economic importance, two strains of P. fijiensis were sequenced and assembled with the aid of a new genetic linkage map. The 74-Mb genome of P. fijiensis is massively expanded by LTR retrotransposons, making it the largest genome within the Dothideomycetes. Melting-curve assays suggest that the genomes of two closely related members of the Sigatoka disease complex, P. eumusae and P. musae, also are expanded. Electrophoretic karyotyping and analyses of molecular markers in P. fijiensis field populations showed chromosome-length polymorphisms and high genetic diversity. Genetic differentiation was also detected using neutral markers, suggesting strong selection with limited gene flow at the studied geographic scale. Frequencies of fungicide resistance in fungicide-treated plantations were much higher than those in untreated wild-type P. fijiensis populations. A homologue of the Cladosporium fulvum Avr4 effector, PfAvr4, was identified in the P. fijiensis genome. Infiltration of the purified PfAVR4 protein into leaves of the resistant banana variety Calcutta 4 resulted in a hypersensitive-like response. This result suggests that Calcutta 4 could carry an unknown resistance gene recognizing PfAVR4. Besides adding to our understanding of the overall Dothideomycete genome structures, the P. fijiensis genome will aid in developing fungicide treatment schedules to combat this pathogen and in improving the efficiency of banana breeding programs.

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Early detection of black Sigatoka in banana leaves using hyperspectral images

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