Active optical sensor assessment of spider mite damage on greenhouse beans and cotton

Martin, Derrel L.; Latheef, M. A.

doi:10.1007/s10493-018-0213-7

Cited by 6 publications

(3 citation statements)

References 51 publications

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“…As some environmental factors including temperature, humidity and light directly affect the growth and development of T. urticae (Maeda et al., 2000; White & Liburd, 2005), the weather data were obtained from the meteorological station located at the research field. The weather data confirmed a tolerable range of the environmental conditions for T. urticae lifestyle during this study (Martin & Latheef, 2018; Maula & Khan, 2016).…”

Section: Discussionsupporting

confidence: 82%

“…TSSM mobile stages can gradually destroy chloroplast‐containing cells through feeding from mesophyll and parenchyma of plant leaf. This piercing‐sucking herbivore penetrates its stylet‐like chelicerae into the leaf tissues and drains cell content using its rostrum, leading to the reduction of photosynthetic capacity and consequently restricts plant growth and yield (Martin & Latheef, 2018; Tanigoshi et al., 2004). Akhtar et al.…”

Section: Introductionmentioning

confidence: 99%

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A field study on common bean (Phaseolus vulgaris) response to Tetranychus urticae herbivory

et al. 2021

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The bean farms in Iran are increasingly suffering from two‐spotted spider mite (TSSM) herbivory, which is intensified with the gradual increase in temperature and decrease in relative humidity coinciding with the flowering time in the common bean. Limited genetic variability for resistance to TSSM is a major bottleneck in the development of resistant common beans. Hence, this study aimed to evaluate the response of a diverse panel of 104 common bean genotypes to TSSM infestation during reproductive stages. The experiment was conducted in the form of an augmented randomized complete block design under TSSM‐infested and non‐infested conditions. The less susceptible genotypes had more grain yield, number of pods, plant height and leaf chlorophyll content, but also, they showed less reduction in these traits under TSSM herbivory condition relative to the more susceptible genotypes. The spider mite laid more eggs on the leaves of more susceptible beans creating a negative density dependence condition, while there was a greater nutritional contribution per adult mite on the leaves of less susceptible common beans. Variance components estimation highlighted grain yield, number of pods, plant height and 1,000‐grain weight of the common bean with the higher genotypic variances compared to environmental variances. The findings provide a phenotypic screening procedure of common bean to determine the main plant traits contributing to genetic TSSM resistance under field conditions. This study concludes that pole‐type genotypes of common bean would tolerate the mite feeding more than bush‐type genotypes during reproductive stages.

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Section: Discussionsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

A field study on common bean (Phaseolus vulgaris) response to Tetranychus urticae herbivory

et al. 2021

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“…In recent years, there has been a lot of interest in the high-throughput phenotyping (HTP), which allows the collection of data on multiple traits of interest at one time by using automated systems of data collection and analysis. Most HTP protocols are based on low-resolution imaging using visible, multispectral, hyperspectral or uorescence cameras, which allow the recording of traits both visible and invisible to the naked eye (Goggin et al, 2015;Herrmann et al, 2012Herrmann et al, , 2015Martin and Latheef, 2018;Nieuwenhuizen et al, 2019;Uygun et al, 2020;Fraulo et al, 2009;Crockett et. al., 2014;Gonzalez-Gonzalez et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Automated imaging coupled with AI-powered analysis accelerates the assessment of plant resistance to Tetranychus urticae

Złotkowska,

Wlazło,

Kiełkiewicz

et al. 2023

Preprint

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The two-spotted spider mite (TSSM), Tetranychus urticae, is one of the most destructive piercing-sucking herbivores, infesting more than 1,100 plant species. The TSSM has evolved a broad tolerance to different plant xenobiotics, influencing its flexibility to adapt to multiple host plants and pesticides. At the same time, the effective resistance loci in plants are still unknown. To find out more about plant-mite correlation, novel approaches are required allowing the efficient screening of large, genetically diverse populations of two interacting species. Here we propose an analytical pipeline based on high-resolution imaging of infested leaves and an artificial intelligence-based computer program, MITESPOTTER, for analysis of plant susceptibility. Our system precisely identifies and quantifies eggs, feces and damaged areas on phenotypically differentiated leaves. The new method was tested on 14 TSSM-infested Arabidopsis thaliana ecotypes derived from diverse world locations and showing remarkable differences in the listed symptoms. The proposed method also demonstrated the ecotype variation in the mite preference to the age of leaf and egg distribution on the ab/adaxial leaf surface. The presented analytical pipeline can be adapted to different pest and host species facilitating diverse experiments with a high number of specimens such as the screening of a large segregating population of plants leading to the identification of loci for efficient breeding of TSSM-resistant plants.

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Automated imaging coupled with AI-powered analysis accelerates the assessment of plant resistance to Tetranychus urticae

Złotkowska,

Wlazło,

Kiełkiewicz

et al. 2024

Sci Rep

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The two-spotted spider mite (TSSM), Tetranychus urticae, is among the most destructive piercing-sucking herbivores, infesting more than 1100 plant species, including numerous greenhouse and open-field crops of significant economic importance. Its prolific fecundity and short life cycle contribute to the development of resistance to pesticides. However, effective resistance loci in plants are still unknown. To advance research on plant-mite interactions and identify genes contributing to plant immunity against TSSM, efficient methods are required to screen large, genetically diverse populations. In this study, we propose an analytical pipeline utilizing high-resolution imaging of infested leaves and an artificial intelligence-based computer program, MITESPOTTER, for the precise analysis of plant susceptibility. Our system accurately identifies and quantifies eggs, feces and damaged areas on leaves without expert intervention. Evaluation of 14 TSSM-infested Arabidopsis thaliana ecotypes originating from diverse global locations revealed significant variations in symptom quantity and distribution across leaf surfaces. This analytical pipeline can be adapted to various pest and host species, facilitating diverse experiments with large specimen numbers, including screening mutagenized plant populations or phenotyping polymorphic plant populations for genetic association studies. We anticipate that such methods will expedite the identification of loci crucial for breeding TSSM-resistant plants.

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Active optical sensor assessment of spider mite damage on greenhouse beans and cotton

Cited by 6 publications

References 51 publications

A field study on common bean (Phaseolus vulgaris) response to Tetranychus urticae herbivory

A field study on common bean (Phaseolus vulgaris) response to Tetranychus urticae herbivory

Automated imaging coupled with AI-powered analysis accelerates the assessment of plant resistance to Tetranychus urticae

Automated imaging coupled with AI-powered analysis accelerates the assessment of plant resistance to Tetranychus urticae

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