Identification of the pathogen associated with Sigatoka disease of banana in South Africa

Surridge, A. K. J.; Viljoen, A.; Crous, Pedro W.; Wehner, F. C.

doi:10.1071/ap02058

Cited by 20 publications

(8 citation statements)

References 7 publications

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“…cubense, banana Xanthomonas wilt caused by bacteria Xanthomonas campestris pv . musacearum , black Sigatoka caused by Mycosphaerella fijiensis and viral diseases caused by Banana streak virus (BSV) and Banana bunchy top virus (BBTV; Jones 2000; Surridge etal. 2003 ; Tripathi etal.…”

Section: Introductionmentioning

confidence: 99%

Dominant Allele Phylogeny and Constitutive Subgenome Haplotype Inference in Bananas Using Mitochondrial and Nuclear Markers

Muiruri

Britt

Amugune

et al. 2017

Genome Biology and Evolution

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Cultivated bananas (Musa spp.) have undergone domestication patterns involving crosses of wild progenitors followed by long periods of clonal propagation. Majority of cultivated bananas are polyploids with different constitutive subgenomes and knowledge on phylogenies to their progenitors at the species and subspecies levels is essential. Here, the mitochondrial (NAD1) and nuclear (CENH3) markers were used to phylogenetically position cultivated banana genotypes to diploid progenitors. The CENH3 nuclear marker was used to identify a minimum representative haplotype number in polyploids and diploid bananas based on single nucleotide polymorphisms. The mitochondrial marker NAD1 was observed to be ideal in differentiating bananas of different genomic constitutions based on size of amplicons as well as sequence. The genotypes phylogenetically segregated based on the dominant genome; AAB genotypes grouped with AA and AAA, and the ABB together with BB. Both markers differentiated banana sections, but could not differentiate subspecies within the A genomic group. On the basis of CENH3 marker, a total of 13 haplotypes (five in both diploid and triploid, three in diploids, and rest unique to triploids) were identified from the genotypes tested. The presence of haplotypes, which were common in diploids and triploids, stipulate possibility of a shared ancestry in the genotypes involved in this study. Furthermore, the presence of multiple haplotypes in some diploid bananas indicates their being heterozygous. The haplotypes identified in this study are of importance because they can be used to check the level of homozygozity in breeding lines as well as to track segregation in progenies.

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Section: Introductionmentioning

confidence: 99%

Dominant Allele Phylogeny and Constitutive Subgenome Haplotype Inference in Bananas Using Mitochondrial and Nuclear Markers

Muiruri

Britt

Amugune

et al. 2017

Genome Biology and Evolution

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“…Mycosphaerella musicola Symptoms similar to black Sigatoka except the early streaks are seen more on the upper surface of the leaves which are yellow-green, narrower and shorter Surridge et al (2003), Perera and Kelaniyangoda (2013) Anthracnose Colletotrichum musae Development of dark, sunken spots or lesions on affected leaves and fruit, fruit turns black and shrivels Khan et al (2001); Zakaria et al (2009) Septoria leaf spot (1998) there are very few known cultivars which show resistance to TR4, and those are diploid wild bananas unsuitable for consumption. Same is the case with other banana diseases such as banana bunchy top disease, Sigatoka disease and weevil infestation.…”

Section: Mycosphaerella Fijiensismentioning

confidence: 99%

RNAi-mediated protection against banana diseases and pests

Ghag

Ganapathi

2019

3 Biotech

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Pests and pathogens restrict the production potential of many crop plants. The losses incurred due to pests and diseases are huge threatening food security. Management strategies include use of chemical pesticides which can be detrimental to human health and environment and other physical and biological methods which have serious limitations. An alternative would be to utilize the advanced technology such as RNA interference (RNAi) to engineer disease resistance in crop plants. The phenomenon of RNAi is very well studied in organisms across genera and found to be conserved. Taking advantage of this, dsRNAs have been delivered into pests and pathogens and showed significant growth inhibition. Banana is susceptible to various groups of pathogens which results in poor yield. The proof-of-principle studies using RNAi technology have already been demonstrated in banana to develop resistance to two important groups of pathogens. Transgenic banana plants expressing small interfering RNA targeting BBTV and Fusarium pathogen have shown high level of resistance. In this review, we summarize and discuss the studies utilizing RNAi as a strategy to develop resistance to major banana diseases and encourage further research in exploiting RNAi-based resistance in other crop plants.

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“…In highly developed stages, these streaks expand to form necrotic lesions with yellow halo and light grey centers (Stover, 1972). These necrotic lesions produce complete drying of the leaves and defoliation, direct to delayed flowering, reduction in the number of hands and fingers, premature ripening and peel splitting of the fruits (Surridge et al, 2003).…”

Section: Yellow Sigatokamentioning

confidence: 99%

Iot Based Banana Leaf Disease Identification System

2022

IRJMETS

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The fundamental and very important role in the Indian economy is played by agriculture of the country. In India, more than 70% of the rural people depend on agriculture. Agriculture contributes approximately 20% to the total GDP and 58% of the Indian population is employed through agriculture. Apart from climatic conditions, the pathogens cause the plant diseases .Due to the diseases occurred in plants the productivity and quality of the harvest get reduced. It is not possible for the human eyes to detect the infected parts of plants at the early stage. Hence In this work, the temperature sensor and color sensor interfaced with IOT systems are used to detect the infected parts of plants at early stage. 37% of the fruit production in India is contributed by Banana. Sigatoka, Black leaf streak and Bunchy top are some of the diseases caused in banana plants. In this work, the Internet of things (IOT)based system is used to detect the leaf diseases occurrence in banana plants.

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Identification of the pathogen associated with Sigatoka disease of banana in South Africa

Cited by 20 publications

References 7 publications

Dominant Allele Phylogeny and Constitutive Subgenome Haplotype Inference in Bananas Using Mitochondrial and Nuclear Markers

Dominant Allele Phylogeny and Constitutive Subgenome Haplotype Inference in Bananas Using Mitochondrial and Nuclear Markers

RNAi-mediated protection against banana diseases and pests

Iot Based Banana Leaf Disease Identification System

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