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Article

Development and Application of Image-Based High-Throughput Phenotyping Methodology for Salt Tolerance in Lentils

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Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
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Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia
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Agriculture Victoria, Grains Innovation Park, Horsham, VIC 3400, Australia
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Agriculture Victoria, Hamilton Centre, Hamilton, VIC 3300, Australia
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School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3086, Australia
*
Authors to whom correspondence should be addressed.
Agronomy 2020, 10(12), 1992; https://doi.org/10.3390/agronomy10121992
Received: 2 November 2020 / Revised: 8 December 2020 / Accepted: 15 December 2020 / Published: 18 December 2020
(This article belongs to the Special Issue Salinities—Framing Knowledge into Multiple Agricultural Contexts)
Soil salinity is a major abiotic stress in Australian lentil-producing areas. It is therefore imperative to identify genetic variation for salt tolerance in order to develop lentil varieties suitable for saline soils. Conventional screening methods include the manual assessment of stress symptoms, which can be very laborious, time-consuming, and error-prone. Recent advances in image-based high-throughput phenotyping (HTP) technologies have provided unparalleled opportunities to screen plants for a range of stresses, such as salt toxicity. The current study describes the development and application of an HTP method for salt toxicity screening in lentils. In a pilot study, six lentil genotypes were evaluated to determine the optimal salt level and the growth stage for distinguishing lentil genotypes using red–green–blue (RGB) images on a LemnaTec Scanalyzer 3D phenomics platform. The optimized protocol was then applied to screen 276 accessions that were also assessed earlier in a conventional phenotypic screen. Detailed phenotypic trait assessments, including plant growth and green/non-green color pixels, were made and correlated to the conventional screen (r = 0.55; p < 0.0001). These findings demonstrated the improved efficacy of an image-based phenotyping approach that is high-throughput, efficient, and better suited to modern breeding programs. View Full-Text
Keywords: lentils; Lens culinaris; salt tolerance; phenotyping; LemnaTec; RGB image analysis lentils; Lens culinaris; salt tolerance; phenotyping; LemnaTec; RGB image analysis
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MDPI and ACS Style

Dissanayake, R.; Kahrood, H.V.; Dimech, A.M.; Noy, D.M.; Rosewarne, G.M.; Smith, K.F.; Cogan, N.O.I.; Kaur, S. Development and Application of Image-Based High-Throughput Phenotyping Methodology for Salt Tolerance in Lentils. Agronomy 2020, 10, 1992. https://doi.org/10.3390/agronomy10121992

AMA Style

Dissanayake R, Kahrood HV, Dimech AM, Noy DM, Rosewarne GM, Smith KF, Cogan NOI, Kaur S. Development and Application of Image-Based High-Throughput Phenotyping Methodology for Salt Tolerance in Lentils. Agronomy. 2020; 10(12):1992. https://doi.org/10.3390/agronomy10121992

Chicago/Turabian Style

Dissanayake, Ruwani, Hossein V. Kahrood, Adam M. Dimech, Dianne M. Noy, Garry M. Rosewarne, Kevin F. Smith, Noel O.I. Cogan, and Sukhjiwan Kaur. 2020. "Development and Application of Image-Based High-Throughput Phenotyping Methodology for Salt Tolerance in Lentils" Agronomy 10, no. 12: 1992. https://doi.org/10.3390/agronomy10121992

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