Sequences enhancing cassava mosaic disease symptoms occur in the cassava genome and are associated with South African cassava mosaic virus infection

Study of Endogenous Viruses in the Strawberry Plants

Endogenous viral elements (EVEs) have been reported to exist widely in the genomes of eukaryotic organisms, and they are closely associated with the growth, development, genetics, adaptation, and evolution of their hosts. In this study, two methods-homologous sequence search and genome alignment-were used to explore the endogenous viral sequences in the genomes of Fragaria species. Results revealed abundant endogenous pararetroviruses (EPRVs) in the genomes of Fragaria species, including 786 sequences belonging to five known taxa such as Caulimovirus and other unclassified taxa. Differences were observed in the detected EPRVs between the two methods, with the homologous sequence search having a greater number of EPRVs. On the contrary, genome alignment identified various types and sources of virus-like sequences. Furthermore, through genome alignment, a 267-bp sequence with 95% similarity to the gene encoding the aphid-transmitted protein of Strawberry vein banding virus (Caulimovirus venafragariae) was discovered in the F. chiloensis genome, which was likely a recent insertion. In addition, the statistical analysis of the genome alignment results indicated a remarkably higher abundance of virus-like sequences in the genomes of polyploid strawberries compared with diploid ones. Moreover, the differences in virus-like sequences were observed between the genomes of Fragaria species and those of their close relatives. This study enriched the diversity of viruses that infect strawberries, and laid a theoretical foundation for further research on the origin of endogenous viruses in the strawberry genome, host-virus interactions, adaptation, evolution, and their functions.

Detecting cassava mosaic disease using a deep residual convolutional neural network with distinct block processing

For people in developing countries, cassava is a major source of calories and carbohydrates. However, Cassava Mosaic Disease (CMD) has become a major cause of concern among farmers in sub-Saharan Africa countries, which rely on cassava for both business and local consumption. The article proposes a novel deep residual convolution neural network (DRNN) for CMD detection in cassava leaf images. With the aid of distinct block processing, we can counterbalance the imbalanced image dataset of the cassava diseases and increase the number of images available for training and testing. Moreover, we adjust low contrast using Gamma correction and decorrelation stretching to enhance the color separation of an image with significant band-to-band correlation. Experimental results demonstrate that using a balanced dataset of images increases the accuracy of classification. The proposed DRNN model outperforms the plain convolutional neural network (PCNN) by a significant margin of 9.25% on the Cassava Disease Dataset from Kaggle.

Cassava mosaic disease: a review of a threat to cassava production in Zambia

Cassava (Manihot esculenta Crantz) is one of the most important root staple crops in Zambia. An estimated 30% of Zambians, over 4 million people, consume cassava as part of their daily diet. Cassava is mostly grown by subsistence farmers on fields of less than 1 ha. Cultivation of cassava is hampered by several biotic constraints, of which cassava mosaic disease (CMD) is currently the most important factor limiting cassava production in Zambia. CMD occurs in all the cassava-growing provinces and accounts for 50% to 70% of yield losses countrywide. Strategies to counter CMD were initiated in the early 1990s and included the release of CMD-resistant cassava cultivars. However, efforts to control CMD are limited because few growers plant these cultivars. More recently, to address the CMD problem, regular disease monitoring and diagnostic capabilities have been strengthened, and there is increased support for screening breeders materials. CMD is a rising threat to cassava production in Zambia. This review of CMD research on disease surveillance, CMD spread, yield losses, awareness campaigns and control options in Zambia over the past 25 years informs future control efforts and management strategies.

Cassava Mosaic and Brown Streak Diseases: Current Perspectives and Beyond

Cassava is the fourth largest source of calories in the world but is subject to economically important yield losses due to viral diseases, including cassava brown streak disease and cassava mosaic disease. Cassava mosaic disease occurs in sub-Saharan Africa and the Asian subcontinent and is associated with nine begomovirus species, whereas cassava brown streak disease has to date been reported only in sub-Saharan Africa and is caused by two distinct ipomovirus species. We present an overview of key milestones and their significance in the understanding and characterization of these two major diseases as well as their associated viruses and whitefly vector. New biotechnologies offer a wide range of opportunities to reduce virus-associated yield losses in cassava for farmers and can additionally enable the exploitation of this valuable crop for industrial purposes. This review explores established and new technologies for genetic manipulation to achieve desired traits such as virus resistance.