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Assessment of the responses of cassava (Manihot esculenta) breeder’s germplasm to cassava mosaic virus (CMD) infection in Kenya

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Research Paper 01/04/2015
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Assessment of the responses of cassava (Manihot esculenta) breeder’s germplasm to cassava mosaic virus (CMD) infection in Kenya

Geoffrey Sing’ombe, E. Ateka, D. Miano, S. Githiri, Theresia Munga, Samuel Mwaura
Int. J. Agron. Agri. Res.6( 4), 120-129, April 2015.
Certificate: IJAAR 2015 [Generate Certificate]
Key: CassavaCMDELISAPCRSeverity

Abstract

Cassava is an important cash crop in tropical lands and in Kenya is grown for income and food covering 77,502 ha with an output of 841,196 tons. Most cassava breeding programmes use symptom expression for selection and detection of viruses. Molecular and/or serological techniques to accurately diagnose viruses are required. Information on the responses of varieties to virus infection helps in assessing rate of crop degeneration over time. This study evaluated seven cassava breeders germplasm (08/363, F10-30-R2, Nl, Tajirika, E-Mariakani), a local susceptible (Kibanda meno) and improved (Shibe) to cassava mosaic disease (CMD) under high disease pressure conditions. The populations of whitefly vector, Bemisia tabaci (Gennadis), severity and incidence of CMD were recorded during the growth period. Infection was determined through symptom severity, disease incidence, ELISA and PCR assays. The mean numbers of whiteflies was higher in the dry season (3 MAP) compared to the wet season (6 MAP) of crop growth. The CMD disease incidence was highest in Kibanda meno (>70%) and lowest in Shibe and Tajirika. The mean CMD severities in the tested genotypes was highest in Kibanda meno (>1.5) and lowest in Shibe and Tajirika. PCR proved a more sensitive disease diagnostic tool as compared to ELISA in the detection of cassava mosaic virus. However both ELISA and PCR detected CMD in asymptomatic cassava samples. The study confirms that the absence of CMD infection cannot be assumed by only looking for the absence of visual symptoms on the leaves underscoring the need for multiple detection tools.

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