PocketPlant3D: Analysing canopy structure using a smartphone

Confalonieri, Roberto; Paleari, Livia; Foi, Marco; Movedi, Ermes; Vesely, Fosco M.; Thoelke, William; Agape, Cristina; Borlini, Giulia; Ferri, Irene; Massara, Federico; Motta, Roberto; Ravasi, Riccardo A.; Tartarini, Sofia; Zoppolato, Camilla; Baia, Luca M.; Brumana, Andrea; Colombo, Davide; Curatolo, Antonio; Fauda, Valerio; Gaia, Denise; Gerosa, A.; Ghilardi, Antonio; Grassi, Enrico; Magarini, Andrea; Novelli, Francesco; Garcia, Fatima B. Perez; Graziosi, Andrea Rota; Salvan, Michele Giuseppe; Tadiello, Tommaso; Rossini, Laura

doi:10.1016/j.biosystemseng.2017.09.014

Cited by 29 publications

(25 citation statements)

References 53 publications

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“…This requires cell wall loosening for cell expansion on the adaxial side of the leaf (López‐Bucio et al ; Eklöf and Brumer ). This increased tendency of leaf bending with ageing is also well‐known and has been observed and discussed in other species (Duan et al ; Confalonieri et al ).…”

Section: Barley Shoot Morphology and Developmentsupporting

confidence: 75%

“…Manual measurement of leaf angle has a major drawback because it is labour‐ and time‐consuming or even destructive, for example manual direct measure of LAD using inclinometers in contact with the leaf surface (Campbell and Norman ). In addition, traditional methods (e.g., inclinometer or protractor) overestimate the angle due to the tendency of the leaves to curve, which affects the light interception in a 3D distribution of leaves in the canopy (Tadrist et al ; Confalonieri et al ).…”

Section: Genetics Of Barley Shoot Architecturementioning

confidence: 99%

“…To date, few such instruments have been developed and proposed as reliable measurement tools for extracting multiple parameters on canopy structure (Escribano‐Rocafort et al ; Confalonieri et al ). One example is PocketPlant3D, a newly developed cell phone‐based phenotyping instrument that can extract both LI (the first value at the proximal parts between the stem and the leaf, Figure A) and LIA (Figure F) (Confalonieri et al ). In addition, the app provides indirect measurements of several important canopy parameters, such as parameters of ellipsoidal distribution and BI.…”

Section: Genetics Of Barley Shoot Architecturementioning

confidence: 99%

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Genetics of barley tiller and leaf development

Shaaf

Bretani

Biswas

et al. 2019

JIPB

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In cereals, tillering and leaf development are key factors in the concept of crop ideotype, introduced in the 1960s to enhance crop yield, via manipulation of plant architecture. In the present review, we discuss advances in genetic analysis of barley shoot architecture, focusing on tillering, leaf size and angle. We also discuss novel phenotyping techniques, such as 2D and 3D imaging, that have been introduced in the era of phenomics, facilitating reliable trait measurement. We discuss the identification of genes and pathways that are involved in barley tillering and leaf development, highlighting key hormones involved in the control of plant architecture in barley and rice. Knowledge on genetic control of traits related to plant architecture provides useful resources for designing ideotypes for enhanced barley yield and performance.

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Section: Barley Shoot Morphology and Developmentsupporting

confidence: 75%

Section: Genetics Of Barley Shoot Architecturementioning

confidence: 99%

Section: Genetics Of Barley Shoot Architecturementioning

confidence: 99%

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Genetics of barley tiller and leaf development

Shaaf

Bretani

Biswas

et al. 2019

JIPB

Self Cite

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“…The most frequently used phenotyping index, such as leaf length, leaf area, and fruit volume, could be obtained in phenotyping platforms simply (Klukas et al, 2014;Zhang et al, 2017). The smartphone app platform was developed for field phenotyping by taking pictures and image analysis at organ level (Confalonieri et al, 2017). It is very convenient to acquire leaf angles and leaf length using the app in a 2D view.…”

Section: Three-dimensional Phenotyping At the Organ Levelmentioning

confidence: 99%

Crop Phenomics: Current Status and Perspectives

et al. 2019

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Reliable, automatic, multifunctional, and high-throughput phenotypic technologies are increasingly considered important tools for rapid advancement of genetic gain in breeding programs. With the rapid development in high-throughput phenotyping technologies, research in this area is entering a new era called 'phenomics.' The crop phenotyping community not only needs to build a multi-domain, multi-level, and multi-scale crop phenotyping big database, but also to research technical systems for phenotypic traits identification and develop bioinformatics technologies for information extraction from the overwhelming amounts of omics data. Here, we provide an overview of crop phenomics research, focusing on two parts, from phenotypic data collection through various sensors to phenomics analysis. Finally, we discussed the challenges and prospective of crop phenomics in order to provide suggestions to develop new methods of mining genes associated with important agronomic traits, and propose new intelligent solutions for precision breeding.

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“…This is an emerging and rapidly evolving area, so we only provide a few examples to illustrate the possibilities. PocketPlant3D measures maize canopy structure (Confalonieri et al, 2017); the smartphone is moved parallel with the leaf lamina from base to tip, and all the leaves can be scanned to obtain the whole leaf architecture. A machine learning-based app can diagnose Cercospora leaf spot and other sugar beet leaf diseases better than experts (Hallau et al, 2018).…”

Section: Pocket Phenotyping: the Flexible Futurementioning

confidence: 99%

Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives

et al. 2020

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Since whole-genome sequencing of many crops has been achieved, crop functional genomics studies have stepped into the big-data and high-throughput era. However, acquisition of large-scale phenotypic data has become one of the major bottlenecks hindering crop breeding and functional genomics studies. Nevertheless, recent technological advances provide us potential solutions to relieve this bottleneck and to explore advanced methods for large-scale phenotyping data acquisition and processing in the coming years. In this article, we review the major progress on high-throughput phenotyping in controlled environments and field conditions as well as its use for post-harvest yield and quality assessment in the past decades. We then discuss the latest multi-omics research combining high-throughput phenotyping with genetic studies. Finally, we propose some conceptual challenges and provide our perspectives on how to bridge the phenotype-genotype gap. It is no doubt that accurate high-throughput phenotyping will accelerate plant genetic improvements and promote the next green revolution in crop breeding.

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PocketPlant3D: Analysing canopy structure using a smartphone

Cited by 29 publications

References 53 publications

Genetics of barley tiller and leaf development

Genetics of barley tiller and leaf development

Crop Phenomics: Current Status and Perspectives

Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives

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