A low-cost aeroponic phenotyping system for storage root development: unravelling the below-ground secrets of cassava (Manihot esculenta)

被引:18
|
作者
Gomez Selvaraj, Michael [1 ]
Elker Montoya-P, Maria [1 ]
Atanbori, John [2 ]
French, Andrew P. [2 ,3 ]
Pridmore, Tony [2 ]
机构
[1] Int Ctr Trop Agr CIAT, Cali 6713, Colombia
[2] Univ Nottingham, Sch Comp Sci, Jubilee Campus,Wollaton Rd, Nottingham NG8 1BB, England
[3] Univ Nottingham, Sch Biosci, Sutton Bonington Campus, Loughborough LE12 5RD, Leics, England
基金
英国生物技术与生命科学研究理事会;
关键词
Aeroponics; Auxin; Cassava; Dripponics; Semi-aeroponic; Root bulking; Storage root; Tuber crops; NITROGEN; ARCHITECTURE; TOLERANCE; IMAGE; TRAITS; GROWTH; YIELD;
D O I
10.1186/s13007-019-0517-6
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background Root and tuber crops are becoming more important for their high source of carbohydrates, next to cereals. Despite their commercial impact, there are significant knowledge gaps about the environmental and inherent regulation of storage root (SR) differentiation, due in part to the innate problems of studying storage roots and the lack of a suitable model system for monitoring storage root growth. The research presented here aimed to develop a reliable, low-cost effective system that enables the study of the factors influencing cassava storage root initiation and development. Results We explored simple, low-cost systems for the study of storage root biology. An aeroponics system described here is ideal for real-time monitoring of storage root development (SRD), and this was further validated using hormone studies. Our aeroponics-based auxin studies revealed that storage root initiation and development are adaptive responses, which are significantly enhanced by the exogenous auxin supply. Field and histological experiments were also conducted to confirm the auxin effect found in the aeroponics system. We also developed a simple digital imaging platform to quantify storage root growth and development traits. Correlation analysis confirmed that image-based estimation can be a surrogate for manual root phenotyping for several key traits. Conclusions The aeroponic system developed from this study is an effective tool for examining the root architecture of cassava during early SRD. The aeroponic system also provided novel insights into storage root formation by activating the auxin-dependent proliferation of secondary xylem parenchyma cells to induce the initial root thickening and bulking. The developed system can be of direct benefit to molecular biologists, breeders, and physiologists, allowing them to screen germplasm for root traits that correlate with improved economic traits.
引用
收藏
页数:13
相关论文
共 8 条
  • [1] A low-cost aeroponic phenotyping system for storage root development: unravelling the below-ground secrets of cassava (Manihot esculenta)
    Michael Gomez Selvaraj
    Maria Elker Montoya-P
    John Atanbori
    Andrew P. French
    Tony Pridmore
    Plant Methods, 15
  • [2] Development of Combination Rapid Propagation Techniques for Diverse Cassava (Manihot esculenta Crantz) Cultivars in an Aeroponic System
    Moun, Sovannara
    Kaewrahun, Supawadee
    Janket, Anon
    INTERNATIONAL JOURNAL OF AGRONOMY, 2024, 2024
  • [3] Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)
    Michael Gomez Selvaraj
    Manuel Valderrama
    Diego Guzman
    Milton Valencia
    Henry Ruiz
    Animesh Acharjee
    Plant Methods, 16
  • [4] Genotypic Variation in Responses of Cassava (Manihot esculenta Crantz) to Drought and Rewatering: Root System Development
    Subere, Juvy Oliva Q.
    Bolatete, Dioscoro
    Bergantin, Reynaldo
    Pardales, Andreu
    Belmonte, Jedi Jim
    Mariscal, Algerico
    Sebidos, Rodrigo
    Yamauchi, Akira
    PLANT PRODUCTION SCIENCE, 2009, 12 (04) : 462 - 474
  • [5] Cassava (Manihot esculenta Krantz) genome harbors KNOX genes differentially expressed during storage root development
    Guo, D.
    Li, H. L.
    Tang, X.
    Peng, S. Q.
    GENETICS AND MOLECULAR RESEARCH, 2014, 13 (04): : 10714 - 10726
  • [6] Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculentaCrantz)
    Selvaraj, Michael Gomez
    Valderrama, Manuel
    Guzman, Diego
    Valencia, Milton
    Ruiz, Henry
    Acharjee, Animesh
    PLANT METHODS, 2020, 16 (01)
  • [7] Leaf proteomic analysis in cassava (Manihot esculenta, Crantz) during plant development, from planting of stem cutting to storage root formation
    Mitprasat, Mashamon
    Roytrakul, Sittiruk
    Jiemsup, Surasak
    Boonseng, Opas
    Yokthongwattana, Kittisak
    PLANTA, 2011, 233 (06) : 1209 - 1221
  • [8] Leaf proteomic analysis in cassava (Manihot esculenta, Crantz) during plant development, from planting of stem cutting to storage root formation
    Mashamon Mitprasat
    Sittiruk Roytrakul
    Surasak Jiemsup
    Opas Boonseng
    Kittisak Yokthongwattana
    Planta, 2011, 233 : 1209 - 1221