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PhenoRoots: An inexpensive non-invasive phenotyping system to assess the variability of the root system architecture

Muniz Martins Saulo, de Brito Giovani Greigh, da Conceição Gonçalves Washington, Mendes Diniz Tripode Bruna, Lartaud Marc, Duarte João Batista, De Lelis Morello Camilo, Giband Marc. 2020. PhenoRoots: An inexpensive non-invasive phenotyping system to assess the variability of the root system architecture. Scientia Agrícola, 77 (5):e20180420, 8 p.

Article de revue ; Article de recherche ; Article de revue à facteur d'impact Revue en libre accès total
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Quartile : Q2, Sujet : AGRICULTURE, MULTIDISCIPLINARY

Résumé : The root system architecture (RSA) of plants and its functioning play a fundamental role in a number of plant growth mechanisms including water and nutrient uptake. Optimization of the RSA is important for stable and increased plant productivity under adverse conditions. Despite its great importance, studying the RSA is notoriously laborious because of the difficulty of accessing the rooting system of plants. We developed a root phenotyping platform, PhenoRoots, which allows for the non-invasive study of plant RSA. The system was built using inexpensive material and was designed to provide medium throughput. Substrate or soil-filled rhizotrons are used to grow plantlets, whose roots are directly visible through a glass plate. An experiment conducted on a panel of twenty Upland cotton (Gossypium hirsutum L.) varieties demonstrated the usefulness of the platform in assessing RSA traits. A number of traits, destructive and non-destructive, related to the RSA were measured and statistically analyzed. The non-destructive traits based on image analysis of roots were more accurate and showed high correlation with the time-consuming destructive measurements. The platform allowed for capturing the phenotypic and genetic variability found in the panel of cotton varieties, and to define three contrasting RSA patterns. PhenoRoots provides an inexpensive alternative to the medium throughput analysis of RSA traits in plants.

Mots-clés Agrovoc : Gossypium hirsutum, système racinaire, analyse d'image, phénotype

Mots-clés libres : Rhizotron, Root traits, Image analysis, Medium-throughput, Cotton

Classification Agris : F50 - Anatomie et morphologie des plantes
U30 - Méthodes de recherche

Champ stratégique Cirad : CTS 2 (2019-) - Transitions agroécologiques

Auteurs et affiliations

  • Muniz Martins Saulo, CIRAD-BIOS-UMR AGAP (FRA)
  • de Brito Giovani Greigh, EMBRAPA (BRA)
  • da Conceição Gonçalves Washington, EMBRAPA (BRA)
  • Mendes Diniz Tripode Bruna, EMBRAPA (BRA)
  • Lartaud Marc, CIRAD-BIOS-UMR AGAP (FRA)
  • Duarte João Batista, UFG (BRA)
  • De Lelis Morello Camilo, EMBRAPA (BRA)
  • Giband Marc, CIRAD-BIOS-UMR AGAP (FRA) ORCID: 0000-0002-5553-5614 - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/594725/)

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