Variation in shoot architecture traits and their relationship to canopy coverage and light interception in soybean (Glycine max)

BACKGROUND

In soybeans, faster canopy coverage (CC) is a highly desirable trait but a fully covered canopy is unfavorable to light interception at lower levels in the canopy with most of the incident radiation intercepted at the top of the canopy. Shoot architecture that influences CC is well studied in crops such as maize and wheat, and altering architectural traits has resulted in enhanced yield. However, in soybeans the study of shoot architecture has not been as extensive.

RESULTS

This study revealed significant differences in CC among the selected soybean accessions. The rate of CC was found to decrease at the beginning of the reproductive stage (R1) followed by an increase during the R2-R3 stages. Most of the accessions in the study achieved maximum rate of CC between R2-R3 stages. We measured Light interception (LI), defined here as the ratio of Photosynthetically Active Radiation (PAR) transmitted through the canopy to the incoming PAR or the radiation above the canopy. LI was found to be significantly correlated with CC parameters, highlighting the relationship between canopy structure and light interception. The study also explored the impact of plant shape on LI and CO2 assimilation. Plant shape was characterized into distinct quantifiable parameters and by modeling the impact of plant shape on LI and CO2 assimilation, we found that plants with broad and flat shapes at the top maybe more photosynthetically efficient at low light levels, while conical shapes were likely more advantageous when light was abundant. Shoot architecture of plants in this study was described in terms of whole plant, branching and leaf-related traits. There was significant variation for the shoot architecture traits between different accessions, displaying high reliability. We found that that several shoot architecture traits such as plant height, and leaf and internode-related traits strongly influenced CC and LI.

CONCLUSION

In conclusion, this study provides insight into the relationship between soybean shoot architecture, canopy coverage, and light interception. It demonstrates that novel shoot architecture traits we have defined here are genetically variable, impact CC and LI and contribute to our understanding of soybean morphology. Correlations between different architecture traits, CC and LI suggest that it is possible to optimize soybean growth without compromising on light transmission within the soybean canopy. In addition, the study underscores the utility of integrating low-cost 2D phenotyping as a practical and cost-effective alternative to more time-intensive 3D or high-tech low-throughput methods. This approach offers a feasible means of studying basic shoot architecture traits at the field level, facilitating a broader and efficient assessment of plant morphology.

Periphyton biomass and life-form responses to a gradient of discharge in contrasting light and nutrients scenarios in experimental lowland streams

Climate-induced changes in precipitation and land-use intensification affect the discharge of streams worldwide, which, together with eutrophication and loss of riparian canopy, can affect periphyton biomass and composition, and therefore, ultimately the stream functioning. We investigated the responses of periphyton biomass and life-forms (i.e., high profile, low profile and motile) to these changes applying an experimental approach by modulating nutrients (nutrient diffusion substrates enriched with 0.5 M NH₄NO₃ + 0.031 M KH₂PO₄ and without nutrient enrichment) and light availability (50% shade and full light) along a gradient in discharge ranging from 0.46 to 3.89 L/s (0.7 to 6.5 cm/s) in twelve large-sized (12- m long) outdoor flumes resembling lowland streams. We also analysed the potential effects of other environmental variables including macroinvertebrates on the responses of periphyton to discharge, nutrients, and light. Light and nutrient availability drastically affected periphyton biomass and composition responses to discharge. Periphyton biomass decreased with increasing discharge when shaded but this did not happen when exposed to full light. Under full light conditions, nutrient enrichment mediated an increase in the periphyton biomass with increasing discharge, possibly reflecting an increased metabolism, but this did not happen under non-enriched conditions. Enrichment further affected the compositional responses of periphyton to discharge, with an increase in the biomass of motile, fast-growing, small-sized flagellated at low discharge conditions, and mitigating a loss of high profile periphyton under higher discharges. Light did not affect periphyton composition, and the abundance or feeding-group composition of the macroinvertebrates did not affect biomass or composition of the periphyton either. Our results suggest that nutrient enrichment and light play an important synergistic role in the responses of the periphyton biomass and composition to discharge and emphasize the relevance of riparian canopy conservation and eutrophication control to avoid periphyton growth under increased discharge scenarios in small lowland streams.

A model for phenotyping crop fractional vegetation cover using imagery from unmanned aerial vehicles

Fractional vegetation cover (FVC) is the key trait of interest for characterizing crop growth status in crop breeding and precision management. Accurate quantification of FVC among different breeding lines, cultivars, and growth environments is challenging, especially because of the large spatiotemporal variability in complex field conditions. This study presents an ensemble modeling strategy for phenotyping crop FVC from unmanned aerial vehicle (UAV)-based multispectral images by coupling the PROSAIL model with a gap probability model (PROSAIL-GP). Seven field experiments for four main crops were conducted, and canopy images were acquired using a UAV platform equipped with RGB and multispectral cameras. The PROSAIL-GP model successfully retrieved FVC in oilseed rape (Brassica napus L.) with coefficient of determination, root mean square error (RMSE), and relative RMSE (rRMSE) of 0.79, 0.09, and 18%, respectively. The robustness of the proposed method was further examined in rice (Oryza sativa L.), wheat (Triticum aestivum L.), and cotton (Gossypium hirsutum L.), and a high accuracy of FVC retrieval was obtained, with rRMSEs of 12%, 6%, and 6%, respectively. Our findings suggest that the proposed method can efficiently retrieve crop FVC from UAV images at a high spatiotemporal domain, which should be a promising tool for precision crop breeding.

Improving the efficiency of soybean breeding with high-throughput canopy phenotyping

BACKGROUND

In the early stages of plant breeding programs high-quality phenotypes are still a constraint to improve genetic gain. New field-based high-throughput phenotyping (HTP) platforms have the capacity to rapidly assess thousands of plots in a field with high spatial and temporal resolution, with the potential to measure secondary traits correlated to yield throughout the growing season. These secondary traits may be key to select more time and most efficiently soybean lines with high yield potential. Soybean average canopy coverage (ACC), measured by unmanned aerial systems (UAS), is highly heritable, with a high genetic correlation with yield. The objective of this study was to compare the direct selection for yield with indirect selection using ACC and using ACC as a covariate in the yield prediction model (Yield|ACC) in early stages of soybean breeding. In 2015 and 2016 we grew progeny rows (PR) and collected yield and days to maturity (R8) in a typical way and canopy coverage using a UAS carrying an RGB camera. The best soybean lines were then selected with three parameters, Yield, ACC and Yield|ACC, and advanced to preliminary yield trials (PYT).

RESULTS

We found that for the PYT in 2016, after adjusting yield for R8, there was no significant difference among the mean performances of the lines selected based on ACC and Yield. In the PYT in 2017 we found that the highest yield mean was from the lines directly selected for yield, but it may be due to environmental constraints in the canopy growth. Our results indicated that PR selection using Yield|ACC selected the most top-ranking lines in advanced yield trials.

CONCLUSIONS

Our findings emphasize the value of aerial HTP platforms for early stages of plant breeding. Though ACC selection did not result in the best performance lines in the second year of selections, our results indicate that ACC has a role in the effective selection of high-yielding soybean lines.