Abstract
Close remote sensing approaches can be used for high throughput on-field phenotyping in the context of plant breeding and biological research. Data on canopy cover (CC) and canopy height (CH) and their temporal changes throughout the growing season can yield information about crop growth and performance. In the present study, sigmoid models were fitted to multi-temporal CC and CH data obtained using RGB imagery captured with a drone for a broad set of soybean genotypes. The Gompertz and Beta functions were used to fit CC and CH data, respectively. Overall, 90.4% fits for CC and 99.4% fits for CH reached an adjusted R2 > 0.70, demonstrating good performance of the models chosen. Using these growth curves, parameters including maximum absolute growth rate, early vigor, maximum height, and senescence were calculated for a collection of soybean genotypes. This information was also used to estimate seed yield and maturity (R8 stage) (adjusted R2 = 0.51 and 0.82). Combinations of parameter values were tested to identify genotypes with interesting traits. An integrative approach of fitting a curve to a multi-temporal dataset resulted in biologically interpretable parameters that were informative for relevant traits.
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Claims 5
Claim · model-written summary
Sigmoid fits to canopy cover reached adjusted R2 > 0.70 for 90.4% of soybean genotypes.
- Taxon
- soybean
Glycine maxe0 - Material
- soybean genotypese0
- Outcome
- adjusted R2e1
- Value
- 90.4%e1
- Qualifier
- fits for CCe1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sigmoid models were fitted to multi-temporal CC and CH data obtained using RGB imagery captured with a drone for a broad set of soybean genotypes”
e1“Overall, 90.4% fits for CC and 99.4% fits for CH reached an adjusted R2 > 0.70”
Claim · model-written summary
Sigmoid fits to canopy height reached adjusted R2 > 0.70 for 99.4% of soybean genotypes.
- Taxon
- soybeanGlycine maxe0
- Material
- soybean genotypese0
- Outcome
- adjusted R2e1
- Value
- 99.4%e1
- Qualifier
- fits for CHe1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sigmoid models were fitted to multi-temporal CC and CH data obtained using RGB imagery captured with a drone for a broad set of soybean genotypes”
e1“Overall, 90.4% fits for CC and 99.4% fits for CH reached an adjusted R2 > 0.70”
Claim · model-written summary
Growth-curve parameters estimated seed yield with adjusted R2 = 0.51.
- Taxon
- soybeanGlycine maxe0
- Outcome
- seed yielde2
- Value
- adjusted R2 = 0.51e2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sigmoid models were fitted to multi-temporal CC and CH data obtained using RGB imagery captured with a drone for a broad set of soybean genotypes”
e2“This information was also used to estimate seed yield and maturity (R8 stage) (adjusted R2 = 0.51 and 0.82)”
Claim · model-written summary
Growth-curve parameters estimated maturity (R8 stage) with adjusted R2 = 0.82.
- Taxon
- soybeanGlycine maxe0
- Outcome
- maturity (R8 stage)e2
- Value
- 0.82e2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sigmoid models were fitted to multi-temporal CC and CH data obtained using RGB imagery captured with a drone for a broad set of soybean genotypes”
e2“This information was also used to estimate seed yield and maturity (R8 stage) (adjusted R2 = 0.51 and 0.82)”
Claim · model-written summary
Fitting a curve to the multi-temporal dataset gave biologically interpretable parameters informative for relevant traits.
- Taxon
- soybeanGlycine maxe0
- Outcome
- biologically interpretable parameterse3
- Qualifier
- informative for relevant traitse3
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sigmoid models were fitted to multi-temporal CC and CH data obtained using RGB imagery captured with a drone for a broad set of soybean genotypes”
e3“An integrative approach of fitting a curve to a multi-temporal dataset resulted in biologically interpretable parameters that were informative for relevant traits”