Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jun 16:12:662498.
doi: 10.3389/fpls.2021.662498. eCollection 2021.

Digital Phenotyping to Delineate Salinity Response in Safflower Genotypes

Affiliations

Digital Phenotyping to Delineate Salinity Response in Safflower Genotypes

Emily Thoday-Kennedy et al. Front Plant Sci. .

Abstract

Salinity is a major contributing factor to the degradation of arable land, and reductions in crop growth and yield. To overcome these limitations, the breeding of crop varieties with improved salt tolerance is needed. This requires effective and high-throughput phenotyping to optimize germplasm enhancement. Safflower (Carthamus tinctorius L.), is an underappreciated but highly versatile oilseed crop, capable of growing in saline and arid environments. To develop an effective and rapid phenotyping protocol to differentiate salt responses in safflower genotypes, experiments were conducted in the automated imaging facility at Plant Phenomics Victoria, Horsham, focussing on digital phenotyping at early vegetative growth. The initial experiment, at 0, 125, 250, and 350 mM sodium chloride (NaCl), showed that 250 mM NaCl was optimum to differentiate salt sensitive and tolerant genotypes. Phenotyping of a diverse set of 200 safflower genotypes using the developed protocol defined four classes of salt tolerance or sensitivity, based on biomass and ion accumulation. Salt tolerance in safflower was dependent on the exclusion of Na+ from shoot tissue and the maintenance of K+ uptake. Salinity response identified in glasshouse experiments showed some consistency with the performance of representatively selected genotypes tested under sodic field conditions. Overall, our results suggest that digital phenotyping can be an effective high-throughput approach in identifying candidate genotypes for salt tolerance in safflower.

Keywords: RGB imaging; digital biomass; high-throughput phenotyping; salinity; salt tolerance.

PubMed Disclaimer

Conflict of interest statement

DH was employed by the company GO Resources Pty Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Performance of safflower genotypes under four salt (NaCl) concentrations from first experiment. (A) Raw and processed images of representative safflower plants at 36 days after sowing from the four salt treatments. (B) Growth curves showing the average performance, as estimated shoot biomass, of safflower genotypes across the growing period under four salt treatments. Data shown as mean with standard deviation. n = 96.
FIGURE 2
FIGURE 2
Measured and estimated shoot biomass in safflower genotypes at four salt (NaCl) concentrations from first experiment. (A) Correlation between estimated shoot biomass and fresh biomass and (B) dry biomass harvested at 36 days after sowing. (C) Estimated shoot biomass accumulation for all genotypes at the four salt concentrations. (D) Fresh biomass at the four salt concentrations for the four safflower genotypes and average of all genotypes. Data represents mean and standard deviation. n = 96. Different letter (a,b,c) indicate a significant difference (P < 0.05) for fresh biomass at different salt level.
FIGURE 3
FIGURE 3
Ion contents in third and fourth leaves of four safflower genotypes under four salt (NaCl) treatments from first experiment. (A) Sodium content, (B) potassium content, and (C) K+/Na+ ratio in third and fourth leaves of four safflower genotypes at 36 days after sowing.
FIGURE 4
FIGURE 4
Changes in shoot biomass between control and salt (NaCl) treatments for 200 diverse safflower genotypes. (A) Correlation between estimated biomass and dry biomass salt tolerance index. (B) Boxplots showing spread of estimated shoot biomass data for safflower genotypes classified as salt tolerant (blue) or salt sensitive (yellow) based on dry biomass salt tolerance index. Boxplot plots represent minimum, maximum and mean values as well as interquartile range and outliers. (C) Estimated shoot biomass under control (0 mM) and salt (250 mM) treatments for 200 diverse safflower genotypes. Black – all genotypes; blue – salt tolerant genotypes n = 65; and yellow – salt sensitive genotypes n = 135.
FIGURE 5
FIGURE 5
Changes in sodium and potassium leaf content between control and salt (NaCl) treatments for 200 diverse safflower genotypes. (A) Sodium content of safflower genotypes under control (0 mM) or salt (250 mM) treatments; sodium content of the third and fourth leaves in the upper panel and sodium content of the first and second youngest expanded leaves in the lower panel. (B) Potassium content of safflower genotypes under control (0 mM) or salt (250 mM) treatments; potassium content of the third and fourth leaves in the upper panel and potassium content of the first and second youngest expanded leaves in the lower panel. Black – all genotypes; blue – salt tolerant genotypes; and yellow – salt sensitive genotypes.
FIGURE 6
FIGURE 6
Average sodium and potassium content in leaves for salt tolerant and salt sensitive safflower genotypes under control and salt (NaCl) treatments. Sodium content of significantly salt tolerant, salt tolerant, salt sensitive and significantly salt sensitive genotypes for (A) third and fourth leaves and (C) first and second youngest expanded leaves under control (0 mM; green) and salt (250 mM, pink) treatments. Potassium content of strongly salt tolerant, salt tolerant, salt sensitive, and strongly salt sensitive genotypes for (B) third and fourth leaves and (D) first and second youngest expanded leaves under control (0 mM; green) and salt (250 mM, pink) treatments.
FIGURE 7
FIGURE 7
Performance of the four classes of safflower genotypes under control and salt (NaCl) treatments. Processed images and dry biomass salt tolerance index (STI) of genotypes under control (0 mM) and salt (250 mM) treatments, representing the four classes of genotypes; strongly salt sensitive (STI < 0.5), salt sensitive (STI 0.5–0.8), salt tolerant (0.8–1.1), and strongly salt tolerant (>1.1).

Similar articles

Cited by

References

    1. Ahmad M., Shahzad A., Iqbal M., Asif M., Hirani A. H. (2013). Morphological and molecular genetic variation in wheat for salinity tolerance at germination and early seedling stage. Aust. J. Crop Sci. 7 66–74.
    1. Anjani K., Yadav P. (2017). High yielding-high oleic non-genetically modified Indian safflower cultivars. Indust. Crops Prod. 104 7–12. 10.1016/j.indcrop.2017.04.011 - DOI
    1. Araus J. L., Cairns J. E. (2014). Field high-throughput phenotyping: the new crop breeding frontier. Trends Plant Sci. 19 52–61. - PubMed
    1. Asgarpanah J., Kazemivash N. (2013). Phytochemistry, pharmacology and medicinal properties of Carthamus tinctorius L. Chin. J. Integr. Med. 19 153–159. 10.1007/s11655-013-1354-5 - DOI - PubMed
    1. Atieno J., Li Y., Langridge P., Dowling K., Brien C., Berger B., et al. (2017). Exploring genetic variation for salinity tolerance in chickpea using image-based phenotyping. Sci. Rep. 7:1309. - PMC - PubMed

LinkOut - more resources