High‐throughput phenotyping for breeding targets—Current status and future directions of strawberry trait automation

James, Katherine; Whitehouse, A. B.; Cielniak, Grzegorz

doi:10.1002/ppp3.10275

Cited by 11 publications

(8 citation statements)

References 54 publications

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“…However, the slight differences in correlation with manual techniques are more difficult to interpret. While it is possible that ShinyFruit is less accurate than other methods, James et al. (2022) points out that automated methods approach the problem of color quantification in a fundamentally different way than manual techniques.…”

Section: Discussionmentioning

confidence: 99%

ShinyFruit: interactive fruit phenotyping software and its application in blackberry

Chizk,

Lee,

Clark

et al. 2023

Front. Plant Sci.

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IntroductionHorticultural plant breeding programs often demand large volumes of phenotypic data to capture visual variation in quality of harvested products. Increasing the throughput potential of phenomic pipelines enables breeders to consider data-hungry molecular breeding strategies such as genome-wide association studies and genomic selection.MethodsWe present an R-based web application called ShinyFruit for image-based phenotyping of size, shape, and color-related qualities in fruits and vegetables. Here, we have demonstrated one potential application for ShinyFruit by comparing its estimates of fruit length, width, and red drupelet reversion (RDR) with ImageJ and analogous manual phenotyping techniques in a population of blackberry cultivars and breeding selections from the University of Arkansas System Division of Agriculture Fruit Breeding Program.ResultsShinyFruit results shared a strong positive correlation with manual measurements for blackberry length (r = 0.96) and ImageJ estimates of RDR (r = 0.96) and significant, albeit weaker, correlations with manual RDR estimation methods (r = 0.62 - 0.70). Neither phenotyping method detected genotypic differences in blackberry fruit width, suggesting that this trait is unlikely to be heritable in the population observed.DiscussionIt is likely that implementing a treatment to promote RDR expression in future studies might strengthen the documented correlation between phenotyping methods by maximizing genotypic variance. Even so, our analysis has suggested that ShinyFruit provides a viable, open-source solution to efficient phenotyping of size and color in blackberry fruit. The ability for users to adjust analysis settings should also extend its utility to a wide range of fruits and vegetables.

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Section: Discussionmentioning

confidence: 99%

ShinyFruit: interactive fruit phenotyping software and its application in blackberry

Chizk,

Lee,

Clark

et al. 2023

Front. Plant Sci.

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show abstract

“…Phenotyping represents a crucial step in the initial selection process of breeds [93], providing a quantitative measure of external agronomic traits. Imagebased phenotyping is one of the most employed techniques, allowing the 2D and 3D shape reconstruction across different spatial scales, from the whole plant to the specific considered trait.…”

Section: Modeling For Phenotypingmentioning

confidence: 99%

Soft robotics for farm to fork: applications in agriculture & farming

Armanini,

Junge,

Johnson

et al. 2024

Bioinspir. Biomim.

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Agricultural tasks and environments range from harsh field conditions with semi-structured produce or animals, through to post-processing tasks in food processing environment. From farm to fork, the development and application of soft robotics offers a plethora of potential uses. Robust yet compliant interactions between farm produce and machines and will enable new capabilities and optimize existing processes. There is also an opportunity to explore how modelling tools used in soft robotics can be applied to improve our representation and understanding of the soft and compliant structures common in agriculture. In this review we seek to highlight the potential for soft robotics technologies within the food system, and also the unique challenges that must be addressed when developing soft robotics systems for this problem domain. We conclude with an outlook on potential directions for meaningful and sustainable impact, and also how our outlook on both soft robotics and agriculture must evolve in order to achieve the required paradigm shift.

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“…High‐throughput (HT) phenotyping methods, or the automation of trait measurement, are now widely used in some crops, especially cereals, but are just beginning to take hold in fruit breeding. James et al (2022) explore both the current status and future directions for HT phenotyping in strawberry. In doing so, they provide a roadmap of potential traits, challenges, and opportunities for strawberry and thereby lay the foundation for future HT phenotyping research in other fruit crops.…”

Section: Breeding Fruitmentioning

confidence: 99%

“…Cockerton et al (2023) perform a genome-wide association study to explore the genomic basis of this trait: identifying three loci including a known major locus and two epistatic modifiers. This study emphasizes the opportunity for combining HT phenotyping, as outlined by James et al (2022), with genomic resources to guide fruit breeding and improvement.…”

Section: Breeding Fruitmentioning

confidence: 99%

Fruit in focus: A sampler platter of research

Migicovsky

Forrestel

Warschefsky

2023

Plants People Planet

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Few plants have captured the imagination and palettes of the world like those which bear edible fruits, providing novel insights into the relationships between plants and people. This special collection of reviews and research highlights the unique challenges and opportunities we face when studying, breeding, and working to conserve these species. The 18 articles included here examine fruiting plants across diverse scales and topics, from the genome to global sustainability, and from fruit morphology to species' geographic distributions, yet they showcase only a fraction of the immense evolutionary, phenotypic, and genomic diversity present in fruit‐bearing plants. Across the special collection, our hope is to not only offer highlights of fruit diversity and importance but also provide a taste of future research in this area. We hope you enjoy the fruits of our labor.

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High‐throughput phenotyping for breeding targets—Current status and future directions of strawberry trait automation

Cited by 11 publications

References 54 publications

ShinyFruit: interactive fruit phenotyping software and its application in blackberry

ShinyFruit: interactive fruit phenotyping software and its application in blackberry

Soft robotics for farm to fork: applications in agriculture & farming

Fruit in focus: A sampler platter of research

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