Literature DB >> 32480841

A semi-automatic system for high throughput phenotyping wheat cultivars in-field conditions: description and first results.

Alexis Comar1, Philippe Burger2, Benoit de Solan1, Fr D Ric Baret3, Fabrice Daumard2, Jean-Fran Ois Hanocq3.   

Abstract

A semi-automatic system was developed to monitor micro-plots of wheat cultivars in field conditions for phenotyping. The system is based on a hyperspectral radiometer and 2 RGB cameras observing the canopy from ~1.5m distance to the top of the canopy. The system allows measurement from both nadir and oblique views inclined at 57.5° zenith angle perpendicularly to the row direction. The system is fixed to a horizontal beam supported by a tractor that moves along the micro-plots. About 100 micro-plots per hour were sampled by the system, the data being automatically collected and registered thanks to a centimetre precision geo-location. The green fraction (GF, the fraction of green area per unit ground area as seen from a given direction) was derived from the images with an automatic segmentation process and the reflectance spectra recorded by the radiometers were transformed into vegetation indices (VI) such as MCARI2 and MTCI. Results showed that MCARI2 is a good proxy of the GF, the MTCI as observed from 57° inclination is expected to be mainly sensitive to leaf chlorophyll pigments. The frequent measurements achieved allowed a good description of the dynamics of each micro-plot along the growth cycle. It is characterised by two periods: the first period corresponding to the vegetative stages exhibits a small rate of change of VI with time; followed by the senescence period characterised by a high rate of change. The dynamics were simply described by a bilinear model with its parameters providing high throughput metrics (HTM). A variance analysis achieved over these HTMs showed that several HTMs were highly heritable, particularly those corresponding to MCARI2 as observed from nadir, and those corresponding to the first period. Potentials of such semi-automatic measurement system are discussed for in field phenotyping applications.

Year:  2012        PMID: 32480841     DOI: 10.1071/FP12065

Source DB:  PubMed          Journal:  Funct Plant Biol        ISSN: 1445-4416            Impact factor:   3.101


  4 in total

1.  A Semi-Automated Method to Extract Green and Non-Photosynthetic Vegetation Cover from RGB Images in Mixed Grasslands.

Authors:  Dandan Xu; Yihan Pu; Xulin Guo
Journal:  Sensors (Basel)       Date:  2020-12-01       Impact factor: 3.576

Review 2.  A Review of High-Throughput Field Phenotyping Systems: Focusing on Ground Robots.

Authors:  Rui Xu; Changying Li
Journal:  Plant Phenomics       Date:  2022-06-16

Review 3.  The field phenotyping platform's next darling: Dicotyledons.

Authors:  Xiuni Li; Xiangyao Xu; Menggen Chen; Mei Xu; Wenyan Wang; Chunyan Liu; Liang Yu; Weiguo Liu; Wenyu Yang
Journal:  Front Plant Sci       Date:  2022-08-24       Impact factor: 6.627

Review 4.  Breeding for Economically and Environmentally Sustainable Wheat Varieties: An Integrated Approach from Genomics to Selection.

Authors:  Etienne Paux; Stéphane Lafarge; François Balfourier; Jérémy Derory; Gilles Charmet; Michael Alaux; Geoffrey Perchet; Marion Bondoux; Frédéric Baret; Romain Barillot; Catherine Ravel; Pierre Sourdille; Jacques Le Gouis
Journal:  Biology (Basel)       Date:  2022-01-17
  4 in total

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