Eggsplorer: a rapid plant-insect resistance determination tool using an automated whitefly egg quantification algorithm

被引:4
作者
Devi, Micha Gracianna [1 ]
Rustia, Dan Jeric Arcega [2 ]
Braat, Lize [1 ]
Swinkels, Kas [1 ]
Espinosa, Federico Fornaguera [1 ]
van Marrewijk, Bart M. [2 ]
Hemming, Jochen [2 ]
Caarls, Lotte [1 ]
机构
[1] Wageningen Univ & Res, Plant Breeding, POB 384, NL-6700 AJ Wageningen, Netherlands
[2] Wageningen Univ & Res, Greenhouse Hort & Flower Bulbs, Wageningen Plant Res, NL-6708 PB Wageningen, Netherlands
基金
欧盟地平线“2020”;
关键词
Insect egg quantification; Rapid phenotyping; Whitefly; Deep learning; Plant insect resistance; Bioassay; BEMISIA-TABACI; HOMOPTERA; IDENTIFICATION; ALEYRODIDAE; HEMIPTERA;
D O I
10.1186/s13007-023-01027-9
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
BackgroundA well-known method for evaluating plant resistance to insects is by measuring insect reproduction or oviposition. Whiteflies are vectors of economically important viral diseases and are, therefore, widely studied. In a common experiment, whiteflies are placed on plants using clip-on-cages, where they can lay hundreds of eggs on susceptible plants in a few days. When quantifying whitefly eggs, most researchers perform manual eye measurements using a stereomicroscope. Compared to other insect eggs, whitefly eggs are many and very tiny, usually 0.2 mm in length and 0.08 mm in width; therefore, this process takes a lot of time and effort with and without prior expert knowledge. Plant insect resistance experiments require multiple replicates from different plant accessions; therefore, an automated and rapid method for quantifying insect eggs can save time and human resources.ResultsIn this work, a novel automated tool for fast quantification of whitefly eggs is presented to accelerate the determination of plant insect resistance and susceptibility. Leaf images with whitefly eggs were collected from a commercial microscope and a custom-built imaging system. A deep learning-based object detection model was trained using the collected images. The model was incorporated into an automated whitefly egg quantification algorithm, deployed in a web-based application called Eggsplorer. Upon evaluation on a testing dataset, the algorithm was able to achieve a counting accuracy as high as 0.94, r(2) of 0.99, and a counting error of +/- 3 eggs relative to the actual number of eggs counted by eye. The automatically collected counting results were used to determine the resistance and susceptibility of several plant accessions and were found to yield significantly comparable results as when using the manually collected counts for analysis.ConclusionThis is the first work that presents a comprehensive step-by-step method for fast determination of plant insect resistance and susceptibility with the assistance of an automated quantification tool.
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页数:14
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