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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.


3D leaf area development dynamics within a 12 d period covering the 155–273 degree-days thermal time in pearl millet fine-mapping recombinants varying in parental allele at three marker loci within the terminal drought tolerance QTL region of linkage group 2 (Yadav et al., 2002) (AAA, recurrent; BBB, QTL donor parent). Each data point for the AAA is the mean (±SE) of 10 lines. Each data point for the BBB is the mean (±SE) of 5 lines.
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Figure 7: 3D leaf area development dynamics within a 12 d period covering the 155–273 degree-days thermal time in pearl millet fine-mapping recombinants varying in parental allele at three marker loci within the terminal drought tolerance QTL region of linkage group 2 (Yadav et al., 2002) (AAA, recurrent; BBB, QTL donor parent). Each data point for the AAA is the mean (±SE) of 10 lines. Each data point for the BBB is the mean (±SE) of 5 lines.

Mentions: The materials were planted in the LeasyScan platform on 19 September 2014, using a sector dimension of 65cm width and 40cm length. Each sector included two pots of 27cm diameter filled with 11kg Alfisol collected from the ICRISAT farm. Three to four seeds were planted in four hills. Seedlings were thinned to one per hill 8 d after sowing and eventually to two seedlings per pot at 12 d after sowing. Therefore, each sector contained four pearl millet plants, giving a sowing density of approximately 16 plants m-2, typical of field populations. Four replicated sectors were used for each entry. The scanning started after the last thinning and the data are presented for the period 1–11 October. The calendar time was converted into thermal units taking a base temperature of 10ºC and optimal temperatures of 25–35ºC. Figure 7 compares the leaf canopy development pattern of 10 lines carrying the recurrent parent allele A at the first three loci within the QTL region (AAA) and of 5 lines carrying the QTL donor parent allele B at the first three loci within the QTL region (BBB). Here, recombinant containing the AAA allele had a more vigorous leaf area development than the BBB allele. Clearly, the leaf area development pattern of the two groups of lines differed and these differences could be pinpointed by the scan measurements. Measuring these differences destructively and manually would have implied major efforts. It should be noticed that the largest leaf area differences, i.e. at 249 degree-days after sowing, were no more than 13% indicating the capacity of the scanning technique to pinpoint small differences for fine genetic analysis. These leaf area differences may look small, but would have very large implications under water restricted conditions, as seen earlier (Kholová et al., 2014). Possible immediate application is the mapping of the growth rate coefficients, and this can be applied to very large sets of entries. Of course, growth is a response to environmental conditions (e.g. Welcker et al., 2011) and therefore repeated experiments with the same material over time under different evaporative demand would also allow us to compare the growth rate response coefficients to environmental 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)

3D leaf area development dynamics within a 12 d period covering the 155–273 degree-days thermal time in pearl millet fine-mapping recombinants varying in parental allele at three marker loci within the terminal drought tolerance QTL region of linkage group 2 (Yadav et al., 2002) (AAA, recurrent; BBB, QTL donor parent). Each data point for the AAA is the mean (±SE) of 10 lines. Each data point for the BBB is the mean (±SE) of 5 lines.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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

Figure 7: 3D leaf area development dynamics within a 12 d period covering the 155–273 degree-days thermal time in pearl millet fine-mapping recombinants varying in parental allele at three marker loci within the terminal drought tolerance QTL region of linkage group 2 (Yadav et al., 2002) (AAA, recurrent; BBB, QTL donor parent). Each data point for the AAA is the mean (±SE) of 10 lines. Each data point for the BBB is the mean (±SE) of 5 lines.
Mentions: The materials were planted in the LeasyScan platform on 19 September 2014, using a sector dimension of 65cm width and 40cm length. Each sector included two pots of 27cm diameter filled with 11kg Alfisol collected from the ICRISAT farm. Three to four seeds were planted in four hills. Seedlings were thinned to one per hill 8 d after sowing and eventually to two seedlings per pot at 12 d after sowing. Therefore, each sector contained four pearl millet plants, giving a sowing density of approximately 16 plants m-2, typical of field populations. Four replicated sectors were used for each entry. The scanning started after the last thinning and the data are presented for the period 1–11 October. The calendar time was converted into thermal units taking a base temperature of 10ºC and optimal temperatures of 25–35ºC. Figure 7 compares the leaf canopy development pattern of 10 lines carrying the recurrent parent allele A at the first three loci within the QTL region (AAA) and of 5 lines carrying the QTL donor parent allele B at the first three loci within the QTL region (BBB). Here, recombinant containing the AAA allele had a more vigorous leaf area development than the BBB allele. Clearly, the leaf area development pattern of the two groups of lines differed and these differences could be pinpointed by the scan measurements. Measuring these differences destructively and manually would have implied major efforts. It should be noticed that the largest leaf area differences, i.e. at 249 degree-days after sowing, were no more than 13% indicating the capacity of the scanning technique to pinpoint small differences for fine genetic analysis. These leaf area differences may look small, but would have very large implications under water restricted conditions, as seen earlier (Kholová et al., 2014). Possible immediate application is the mapping of the growth rate coefficients, and this can be applied to very large sets of entries. Of course, growth is a response to environmental conditions (e.g. Welcker et al., 2011) and therefore repeated experiments with the same material over time under different evaporative demand would also allow us to compare the growth rate response coefficients to environmental 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.