Automated estimation of stomatal number and aperture in haskap (Lonicera caerulea L.)

Meng, Xiangji; Nakano, Arisa; Hoshino, Yoichiro

doi:10.1007/s00425-023-04231-y

Cited by 2 publications

(1 citation statement)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, DNA sequencing can help breeders distinguish suitable parents faster, more efficiently and more accurately, thus improving the genetic superiority of hybrids and supporting plant phylogenetic relationships (Srivastav et al, 2023;Žilinskaitė et al, 2022). New techniques have also been applied in germplasm resource evaluation, like Mask Regional Convolutional Neural Network, a deep learning model, to analyse the stomata of blue honeysuckle accurately (Meng et al, 2023).…”

Section: Breeding Methods and Supporting Techniquesmentioning

confidence: 99%

Breeding trends on blue honeysuckle (Lonicera caerulea L.)

Guo,

Qiao,

Sorokin

et al. 2024

Plant Breeding

View full text Add to dashboard Cite

Blue honeysuckle, also named as haskap or honeyberry, an emerging fruit worldwide, with the species being Lonicera L., originating from the north hemisphere, exhibits high genetic heterogeneity and abundant genetic variation in fruit and leaf traits. However, there are few papers on the research progress of blue honeysuckle breeding and cultivars. The International Union for the Protection of New Varieties of Plants (UPOV) is an effective plant variety protection system, and blue honeysuckle cultivars from different countries and regions are registered in the UPOV database. In this review, we summarized the origin, domestication and germplasm collection, breeding categories and supporting techniques of blue honeysuckle, and the information on registered blue honeysuckle cultivars was analysed based on the UPOV database. Finally, the paper put forward the challenges of blue honeysuckle in development, breeding direction and perspectives to promote the development of blue honeysuckle.

show abstract

Section: Breeding Methods and Supporting Techniquesmentioning

confidence: 99%

Breeding trends on blue honeysuckle (Lonicera caerulea L.)

Guo,

Qiao,

Sorokin

et al. 2024

Plant Breeding

View full text Add to dashboard Cite

show abstract

Application of deep learning for the analysis of stomata: a review of current methods and future directions

Gibbs,

Burgess

2024

Journal of Experimental Botany

View full text Add to dashboard Cite

Plant physiology and metabolism relies on the function of stomata, structures on the surface of above ground organs, which facilitate the exchange of gases with the atmosphere. The morphology of the guard cells and corresponding pore which make up the stomata, as well as the density (number per unit area) are critical in determining overall gas exchange capacity. These characteristics can be quantified visually from images captured using microscopes, traditionally relying on time-consuming manual analysis. However, deep learning (DL) models provide a promising route to increase the throughput and accuracy of plant phenotyping tasks, including stomatal analysis. Here we review the published literature on the application of DL for stomatal analysis. We discuss the variation in pipelines used; from data acquisition, pre-processing, DL architecture and output evaluation to post processing. We introduce the most common network structures, the plant species that have been studied, and the measurements that have been performed. Through this review, we hope to promote the use of DL methods for plant phenotyping tasks and highlight future requirements to optimise uptake; predominantly focusing on the sharing of datasets and generalisation of models as well as the caveats associated with utilising image data to infer physiological function.

show abstract

Automated estimation of stomatal number and aperture in haskap (Lonicera caerulea L.)

Cited by 2 publications

References 32 publications

Breeding trends on blue honeysuckle (Lonicera caerulea L.)

Breeding trends on blue honeysuckle (Lonicera caerulea L.)

Application of deep learning for the analysis of stomata: a review of current methods and future directions

Contact Info

Product

Resources

About