Search

Summary Bananas (Musa spp.) are considered the most important fruit crop in Kenya, grown mostly by smallholder farmers. However, in the past two decades production has declined and has largely been attributed to plant pathogens, including plant-parasitic nematodes. To assess the understanding and awareness that banana farmers have of nematodes, a survey was conducted. The incidence, abundance and distribution of nematodes in relation to altitude were determined for different banana types on 180 farms and the pathogenicity of Pratylenchus goodeyi, originating from three different altitudinal locations, was compared on two banana cultivars. Just 2.3% of farmers were aware of nematode damage and symptoms, none of whom applied any management measures. The highest abundance of nematodes was recorded at an altitude range of 1601-2000 m a.s.l., with Pratylenchus, Meloidogyne and Helicotylenchus being the predominant genera. Across all altitudinal locations, cooking banana had higher densities of nematodes than dessert bananas. In pots, P. goodeyi populations from Embu (1300 m a.s.l.) appeared more aggressive and with higher levels of multiplication than the population from Oyugis (1100 m a.s.l.). Cooking banana (‘Ng’ombe’) was more susceptible than dessert banana (‘Sukari Ndizi’). Nematode damage is more prominent in areas at higher altitude and on cooking banana cultivars. The findings provide key information in guiding informed and suitable management decision thresholds in relation to potential climate change.

In-depth understanding of metabolite-mediated plant-nematode interactions can guide us towards novel nematode management strategies. To improve our understanding of the effects of secondary metabolites on soil nematode communities, we grew Arabidopsis thaliana genetically altered in glucosinolate, camalexin, or flavonoid synthesis pathways, and analyzed their root-associated nematode communities using metabarcoding. To test for any modulating effects of the associated microbiota on the nematode responses, we characterized the bacterial and fungal communities. Finally, as a proxy of microbiome-modulating effects on nematode invasion, we isolated the root-associated microbiomes from the mutants and tested their effect on the ability of the plant parasitic nematode Meloidogyne incognita to penetrate tomato roots. Most mutants had altered relative abundances of several nematode taxa with stronger effects on the plant parasitic Meloidogyne hapla than on other root feeding taxa. This probably reflects that M. hapla invades and remains embedded within root tissues and is thus intimately associated with the host. When transferred to tomato, microbiomes from the flavonoid over-producing pap1-D enhanced M. incognita root-invasion, whereas microbiomes from flavonoid-deficient mutants reduced invasion. This suggests microbiome-mediated effect of flavonoids on Meloidogyne infectivity plausibly mediated by the alteration of the abundances of specific microbial taxa in the transferred microbiomes, although we could not conclusively pinpoint such causative microbial taxa.

Given the large yield losses attributed to plant-parasitic nematodes and the limited availability of sustainable control strategies, new plant-parasitic nematode control strategies are urgently needed. To defend themselves against nematode attack, plants possess sophisticated multi-layered immune systems. One element of plant immunity against nematodes is the production of small molecules with anti-nematode activity, either constitutively or after nematode infection. This review provides an overview of such metabolites that have been identified to date and groups them by chemical class (e.g., terpenoids, flavonoids, glucosinolates, etc.). Furthermore, this review discusses strategies that have been used to identify such metabolites and highlights the ways in which studying anti-nematode metabolites might be of use to agriculture and crop protection. Particular attention is given to emerging, high-throughput approaches for the identification of anti-nematode metabolites, in particular the use of untargeted metabolomics techniques based on nuclear magnetic resonance (NMR) and mass spectrometry (MS).