ArticleBiology2020
A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant.
Article in Biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Recent advances in generation of doubled haploid plants for genetic improvement in solanaceous vegetable crops.Planta · 2026Review
- Doubled Haploid Production inPlants (Basel, Switzerland) · 2025Article
- Deep learning-based high-throughput detection of in vitro germination to assess pollen viability from microscopic images.Journal of experimental botany · 2023Article
- PollenDetect: An Open-Source Pollen Viability Status Recognition System Based on Deep Learning Neural Networks.International journal of molecular sciences · 2022Article
- Doubled Haploids in Eggplant.Biology · 2021Review
- Deep learning-based high-throughput phenotyping can drive future discoveries in plant reproductive biology.Plant reproduction · 2021Article
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Authors and funding
7 authors.
Funding
Abstract
The development of double haploids (DHs) is a straightforward path for obtaining pure lines but has multiple bottlenecks. Among them is the determination of the optimal stage of pollen induction for androgenesis. In this work, we developed Microscan, a deep learning-based system for the detection and recognition of the stages of pollen development. In a first experiment, the algorithm was developed adapting the RetinaNet predictive model using microspores of different eggplant accessions as samples. A mean average precision of 86.30% was obtained. In a second experiment, the anther range to be cultivated in vitro was determined in three eggplant genotypes by applying the Microscan system. Subsequently, they were cultivated following two different androgenesis protocols (Cb and E6). The response was only observed in the anther size range predicted by Microscan, obtaining the best results with the E6 protocol. The plants obtained were characterized by flow cytometry and with the Single Primer Enrichment Technology high-throughput genotyping platform, obtaining a high rate of confirmed haploid and double haploid plants. Microscan has been revealed as a tool for the high-throughput efficient analysis of microspore samples, as it has been exemplified in eggplant by providing an increase in the yield of DHs production.
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Registered trials
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