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Sci Rep


Title:Electroantennogram and machine learning reveal a volatile blend mediating avoidance behavior by Tuta absoluta females to a wild tomato plant
Author(s):Miano RN; Ayelo PM; Musau R; Hassanali A; Mohamed SA;
Address:"International Centre of Insect Physiology and Ecology (icipe), P.O Box 30772-00100, Nairobi, Kenya. rmiano@icipe.org. Department of Chemistry, Kenyatta University, P.O Box 43844-00100, Nairobi, Kenya. rmiano@icipe.org. International Centre of Insect Physiology and Ecology (icipe), P.O Box 30772-00100, Nairobi, Kenya. Department of Chemistry, Kenyatta University, P.O Box 43844-00100, Nairobi, Kenya. International Centre of Insect Physiology and Ecology (icipe), P.O Box 30772-00100, Nairobi, Kenya. sfaris@icipe.org"
Journal Title:Sci Rep
Year:2022
Volume:20220527
Issue:1
Page Number:8965 -
DOI: 10.1038/s41598-022-13125-0
ISSN/ISBN:2045-2322 (Electronic) 2045-2322 (Linking)
Abstract:"Tomato cultivation is threatened by the infestation of the nocturnal invasive tomato pinworm, Tuta absoluta. This study was based on field observations that a wild tomato plant, Solanum lycopersicum var. cerasiforme, grown in the Mount Kenya region, Kenya, is less attacked by T. absoluta, unlike the cultivated tomato plants like S. lycopersicum (var. Rambo F1). We hypothesized that the wild tomato plant may be actively avoided by gravid T. absoluta females because of the emission of repellent allelochemical constituents. Therefore, we compared infestation levels by the pest in field monocrops and intercrops of the two tomato genotypes, characterized the headspace volatiles, then determined the compounds detectable by the insect through gas chromatography-linked electroantennography (GC-EAG), and finally performed bioassays using a blend of four EAG-active compounds unique to the wild tomato. We found significant reductions in infestation levels in the monocrop of the wild tomato, and intercrops of wild and cultivated tomato plants compared to the monocrop of the cultivated tomato plant. Quantitative and qualitative differences were noted between volatiles of the wild and cultivated tomato plants, and between day and night volatile collections. The most discriminating compounds between the volatile treatments varied with the variable selection or machine learning methods used. In GC-EAG recordings, 16 compounds including hexanal, (Z)-3-hexenol, alpha-pinene, beta-myrcene, alpha-phellandrene, beta-phellandrene, (E)-beta-ocimene, terpinolene, limonene oxide, camphor, citronellal, methyl salicylate, (E)-beta-caryophyllene, and others tentatively identified as 3,7,7-Trimethyl-1,3,5-cycloheptatriene, germacrene D and cis-carvenone oxide were detected by antennae of T. absoluta females. Among these EAG-active compounds, (Z)-3-hexenol, alpha-pinene, alpha-phellandrene, limonene oxide, camphor, citronellal, (E)-beta-caryophyllene and beta-phellandrene are in the top 5 discriminating compounds highlighted by the machine learning methods. A blend of (Z)-3-hexenol, camphor, citronellal and limonene oxide detected only in the wild tomato showed dose-dependent repellence to T. absoluta females in wind tunnel. This study provides some groundwork for exploiting the allelochemicals of the wild tomato in the development of novel integrated pest management approaches against T. absoluta"
Keywords:Animals Avoidance Learning Camphor Female *Lepidoptera *Solanum lycopersicum/chemistry Machine Learning Pheromones Plants *Solanum *Volatile Organic Compounds/chemistry;
Notes:"MedlineMiano, Raphael Njurai Ayelo, Pascal Mahukpe Musau, Richard Hassanali, Ahmed Mohamed, Samira A eng Research Support, Non-U.S. Gov't England 2022/05/28 Sci Rep. 2022 May 27; 12(1):8965. doi: 10.1038/s41598-022-13125-0"

 
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