Distribution, abundance and natural enemies of the invasive tomato leafminer, Tuta absoluta (Meyrick) in Kenya

Abstract

Tuta absoluta (Meyrick) has become a serious menace to sustainable production of tomato in Kenya. A survey was conducted between April 2015 and June 2016 to determine its distribution, abundance, infestation, and damage levels on tomato, and associated natural enemies. Trap counts of T. absoluta moths were recorded in all surveyed 29 counties, which indicated its nationwide distribution irrespective of altitude. Tuta absoluta was present in both open fields and greenhouses. The highest moth/trap/day was 115.38 ± 15.90. Highest leaf infestation was 92.22% and the highest number of mines and larvae per leaf were 3.71 ± 0.28 and 2.16 ± 0.45, respectively. Trap captures in terms of moth/trap/day were linearly and positively related to leaf infestations in open fields (R2 = 0.81) and greenhouses (R2 = 0.61). Highest fruits’ infestation and damage were 60.00 and 59.61%, respectively, while the highest number of mines per fruit was 7.50 ± 0.50. Nesidiocoris tenuis (Reuter) and Macrolophus pygmaeus (Rambur) were identified as predators of T. absoluta larvae. Nine species of larval parasitoids were recovered from infested foliage, with a combined parasitism of 7.26 ± 0.65%. Hockeria species was the most dominant (31.25%) and accounted for 12.88 ± 1.47% parasitism. Two species of larval parasitoids, Hockeria and Necremnus were obtained from sentinel plants with an average parasitism of 1.13 ± 0.25. The overall abundance and parasitism rates of recovered natural enemies were low to effectively control the field populations of T. absoluta. These findings form the basis of researching and developing effective and sustainable management strategies for the pest.

Identification, Microhabitat, and Ecological Niche Prediction of Two Promising Native Parasitoids of Tuta absoluta in Kenya

“…Stenomesius sp. has also been reported on T. absoluta in Algeria [ 26 ], while S. rufescens was previously identified in Kenya on the same host [ 65 ]. Stenomesius sp.…”

“…Three species of the genus Stenomesius have been reported in the Afrotropical region, namely Stenomesius elegantulus (Risbec) (Hymenoptera: Eulophidae) in Cameroon and Senegal and S. japonicus in the Afrotropical, Palaearctic, Indo-Malaya, and Australian regions [ 63 , 64 ] while S tenomesius rufescens (Retzius) (Hymenoptera: Eulophidae) was described for the first time in Africa, in Egypt [ 64 ], and this species is supposed to be distributed Nearctic and Palaearctic regions. However, the species has been identified in Kenya [ 65 ]. Stenomesius elegantulus differs from S. japonicus mainly by its relatively shorter scutellum abruptly black compared to yellow axillae [ 52 ].…”

“…nr japonicus . This is not the first report of these species on the African continent [ 30 , 69 ], but it is the first report of the two species in Kenya, although Kinyanjui et al [ 65 ] reported the presence of a Bracon sp. and S. rufescens .…”

A Fuzzy-Based Model to Predict the Spatio-Temporal Performance of the Dolichogenidea gelechiidivoris Natural Enemy against Tuta absoluta under Climate Change

“…absoluta was confirmed using the MaxEnt ecological niche model. The georeferenced records used in the study were obtained from Kinyanjui et al [ 35 ] and the 19 bioclimatic variables were sourced from the WorldClim platform (accessed on 20 January 2022) at an approximate 1 km 2 spatial resolution [ 36 , 37 ]. The net reproductive rate (R 0 ) was obtained from Aigbedion-Atalor et al [ 38 ] and used as an indicator for parasitoid performance.…”

“…MaxEnt software version 3.4.1 [ 42 ] was used to predict the habitat suitability of the parasitoid host, T. absoluta, for the classified LULCs in the study area. The georeferenced records of T. absoluta were obtained from Kinyanjui et al [ 35 ] and the 19 bioclimatic variables were sourced from the WorldClim platform (accessed on 20 January 2022) [ 36 , 37 ], in addition to the classified LULCs used as variables. Prior to running MaxEnt, the variables were clipped to Kenya country boundaries and converted to American Standard Code for Information Interchange (ASCII) format using the ‘raster’ package [ 43 ] in R statistical software [ 32 ].…”