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LeasyScan: a novel concept combining 3D imaging and lysimetry for high-throughput phenotyping of traits controlling plant water budget.

Vadez V, Kholová J, Hummel G, Zhokhavets U, Gupta SK, Hash CT - J. Exp. Bot. (2015)

Bottom Line: Close agreement between scanned and observed leaf area data of individual plants in different crops was found (R(2) between 0.86 and 0.94).Similar agreement was found when comparing scanned and observed area of plants cultivated at densities reflecting field conditions (R(2) between 0.80 and 0.96).This new platform has the potential to phenotype for traits controlling plant water use at a high rate and precision, of critical importance for drought adaptation, and creates an opportunity to harness their genetics for the breeding of improved varieties.

View Article: PubMed Central - PubMed

Affiliation: ICRISAT-Crop Physiology Laboratory, Greater Hyderabad, Patancheru 502324, Telangana, India v.vadez@cgiar.org.

No MeSH data available.


Data display of the analytical scales and transpiration data extracted from sector weights in an experiment where two genotypes of pearl millet were treated with NaCl on 18 October 2014 evening. (A) Typical trace of load cell weights, averaged across six sectors per treatment and genotype (untreated controls, red and black weight trajectory of genotype 1 and 2; salt treatment, green and purple weight trajectory of genotype 1 and 2). Before treatment the plants were kept under fully irrigated conditions. (B) Transpiration data before and after NaCl treatment in two genotypes of pearl millet (PRLT and H77). Data are the mean of six replicated sectors per genotype and treatment. (This figure is available in colour at JXB online.)
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Figure 6: Data display of the analytical scales and transpiration data extracted from sector weights in an experiment where two genotypes of pearl millet were treated with NaCl on 18 October 2014 evening. (A) Typical trace of load cell weights, averaged across six sectors per treatment and genotype (untreated controls, red and black weight trajectory of genotype 1 and 2; salt treatment, green and purple weight trajectory of genotype 1 and 2). Before treatment the plants were kept under fully irrigated conditions. (B) Transpiration data before and after NaCl treatment in two genotypes of pearl millet (PRLT and H77). Data are the mean of six replicated sectors per genotype and treatment. (This figure is available in colour at JXB online.)

Mentions: A basic idea in the development of the LeasyScan platform was to combine the measurements of leaf development parameters (which can be encapsulated in ‘volumetric growth’) with a continuous assessment of plant transpiration (or ‘massic growth’ considering transpiration as a proxy for photosynthesis), to obtain a continuous measurement of canopy conductance, based on earlier work (e.g. Kholová et al., 2010; Zaman-Allah et al., 2011), and a shift from earlier destructive measurements (Kholová et al., 2012). Figure 6A demonstrates a typical trace of the evolution of the pot weight over time, before and after NaCl treatment, which further altered plant transpiration (visualized in HortControl). In this experiment, two pearl millet genotypes were cultivated in 27cm pots containing 12kg of Alfisol. Once plants were 10 days’ old, the pots were covered by a polythene sheet and a 2cm layer of low density polyethylene beads to prevent soil evaporation, so that pot weight differences would provide direct measurements of plant transpiration. There was a scanner setting of 65cm width and 60cm length. Each sector had two pots, and each pot two plants, giving a sowing density of 10 plants per square metre and each replication unit was 0.40 m2, with six replicated sectors for each genotype and treatment combination. The scales (Rugged Scale 50, Phenospex, Heerlen, Netherlands) have a capacity of 50kg, with 0.02% accuracy. The accuracy of these temperature-corrected scales (−10°C to +40°C range) was tested under artificial rapid increase in temperature (14°C h-1, i.e. much above our experimental conditions) and showed that the error remained within the stipulated 0.02% error range. The scales provided a reading with a 0.02% precision every second and these were integrated over one hour, giving readings with a precision of 0.1g. The treatment consisted of the application of 1 l of a 250mM NaCl solution, and the control received 1 l of non-salted water (Fig. 6). This was only a qualitative assessment and a proof-of-concept to assess how fast and accurate the system was able to detect changes in transpiration rates. In addition, these traces were important in the design of the type of interfacing scripts needed to extract meaningful transpiration information from numerous weight data. In any case, upon NaCl treatment the decrease in weight (the day following the treatment) was lower (Fig. 6A) and transpiration decreased more in the NaCl-treated plants of both genotypes than in the control plants (Fig. 6B). Similar results were obtained for two genotypes of sorghum, cultivated and treated in the same way (data not shown). Data filters are under development to segregate out weight changes due to watering or drainage. Therefore, the platform allows continuous and simultaneous measurements of plant development and transpiration within a time frame of an hour in an undisturbed manner and in the planting densities that reflect field conditions.


LeasyScan: a novel concept combining 3D imaging and lysimetry for high-throughput phenotyping of traits controlling plant water budget.

Vadez V, Kholová J, Hummel G, Zhokhavets U, Gupta SK, Hash CT - J. Exp. Bot. (2015)

Data display of the analytical scales and transpiration data extracted from sector weights in an experiment where two genotypes of pearl millet were treated with NaCl on 18 October 2014 evening. (A) Typical trace of load cell weights, averaged across six sectors per treatment and genotype (untreated controls, red and black weight trajectory of genotype 1 and 2; salt treatment, green and purple weight trajectory of genotype 1 and 2). Before treatment the plants were kept under fully irrigated conditions. (B) Transpiration data before and after NaCl treatment in two genotypes of pearl millet (PRLT and H77). Data are the mean of six replicated sectors per genotype and treatment. (This figure is available in colour at JXB online.)
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4585418&req=5

Figure 6: Data display of the analytical scales and transpiration data extracted from sector weights in an experiment where two genotypes of pearl millet were treated with NaCl on 18 October 2014 evening. (A) Typical trace of load cell weights, averaged across six sectors per treatment and genotype (untreated controls, red and black weight trajectory of genotype 1 and 2; salt treatment, green and purple weight trajectory of genotype 1 and 2). Before treatment the plants were kept under fully irrigated conditions. (B) Transpiration data before and after NaCl treatment in two genotypes of pearl millet (PRLT and H77). Data are the mean of six replicated sectors per genotype and treatment. (This figure is available in colour at JXB online.)
Mentions: A basic idea in the development of the LeasyScan platform was to combine the measurements of leaf development parameters (which can be encapsulated in ‘volumetric growth’) with a continuous assessment of plant transpiration (or ‘massic growth’ considering transpiration as a proxy for photosynthesis), to obtain a continuous measurement of canopy conductance, based on earlier work (e.g. Kholová et al., 2010; Zaman-Allah et al., 2011), and a shift from earlier destructive measurements (Kholová et al., 2012). Figure 6A demonstrates a typical trace of the evolution of the pot weight over time, before and after NaCl treatment, which further altered plant transpiration (visualized in HortControl). In this experiment, two pearl millet genotypes were cultivated in 27cm pots containing 12kg of Alfisol. Once plants were 10 days’ old, the pots were covered by a polythene sheet and a 2cm layer of low density polyethylene beads to prevent soil evaporation, so that pot weight differences would provide direct measurements of plant transpiration. There was a scanner setting of 65cm width and 60cm length. Each sector had two pots, and each pot two plants, giving a sowing density of 10 plants per square metre and each replication unit was 0.40 m2, with six replicated sectors for each genotype and treatment combination. The scales (Rugged Scale 50, Phenospex, Heerlen, Netherlands) have a capacity of 50kg, with 0.02% accuracy. The accuracy of these temperature-corrected scales (−10°C to +40°C range) was tested under artificial rapid increase in temperature (14°C h-1, i.e. much above our experimental conditions) and showed that the error remained within the stipulated 0.02% error range. The scales provided a reading with a 0.02% precision every second and these were integrated over one hour, giving readings with a precision of 0.1g. The treatment consisted of the application of 1 l of a 250mM NaCl solution, and the control received 1 l of non-salted water (Fig. 6). This was only a qualitative assessment and a proof-of-concept to assess how fast and accurate the system was able to detect changes in transpiration rates. In addition, these traces were important in the design of the type of interfacing scripts needed to extract meaningful transpiration information from numerous weight data. In any case, upon NaCl treatment the decrease in weight (the day following the treatment) was lower (Fig. 6A) and transpiration decreased more in the NaCl-treated plants of both genotypes than in the control plants (Fig. 6B). Similar results were obtained for two genotypes of sorghum, cultivated and treated in the same way (data not shown). Data filters are under development to segregate out weight changes due to watering or drainage. Therefore, the platform allows continuous and simultaneous measurements of plant development and transpiration within a time frame of an hour in an undisturbed manner and in the planting densities that reflect field conditions.

Bottom Line: Close agreement between scanned and observed leaf area data of individual plants in different crops was found (R(2) between 0.86 and 0.94).Similar agreement was found when comparing scanned and observed area of plants cultivated at densities reflecting field conditions (R(2) between 0.80 and 0.96).This new platform has the potential to phenotype for traits controlling plant water use at a high rate and precision, of critical importance for drought adaptation, and creates an opportunity to harness their genetics for the breeding of improved varieties.

View Article: PubMed Central - PubMed

Affiliation: ICRISAT-Crop Physiology Laboratory, Greater Hyderabad, Patancheru 502324, Telangana, India v.vadez@cgiar.org.

No MeSH data available.