ArticlePlant methods2022
High-throughput phenotyping allows the selection of soybean genotypes for earliness and high grain yield.
Article in Plant methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Photosynthesis-informed breeding to enhance Soybean (Glycine max) yield potential: a framework integrating high-throughput phenomics, genomic prediction and G×E×M.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Advancing radiation-induced mutant screening through high-throughput technology: a preliminary evaluation of mutant screening in Arabidopsis thaliana.Plant methods · 2025Article
- Transfer learning for improving generalizability in predicting soybean maturity date using UAV imagery.Frontiers in plant science · 2025Article
- High throughput phenotyping in soybean breeding using RGB image vegetation indices based on drone.Scientific reports · 2024Article
- Review on blueberry drought tolerance from the perspective of cultivar improvement.Frontiers in plant science · 2024Review
- Remote sensing for field pea yield estimation: A study of multi-scale data fusion approaches in phenomics.Frontiers in plant science · 2023Article
- Multi-Omics Techniques for Soybean Molecular Breeding.International journal of molecular sciences · 2022Review
- Height to first pod: A review of genetic and breeding approaches to improve combine harvesting in legume crops.Frontiers in plant science · 2022Review
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8 authors.
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Abstract
backgroundPrecision agriculture techniques are widely used to optimize fertilizer and soil applications. Furthermore, these techniques could also be combined with new statistical tools to assist in phenotyping in breeding programs. In this study, the research hypothesis was that soybean cultivars show phenotypic differences concerning wavelength and vegetation index measurements.
resultsIn this research, we associate variables obtained via high-throughput phenotyping with the grain yield and cycle of soybean genotypes. The experiment was carried out during the 2018/2019 and 2019/2020 crop seasons, under a randomized block design with four replications. The evaluated soybean genotypes included 7067, 7110, 7739, 8372, Bonus, Desafio, Maracai, Foco, Pop, and Soyouro. The phenotypic traits evaluated were: first pod height (FPH), plant height (PH), number of branches (NB), stem diameter (SD), days to maturity (DM), and grain yield (YIE). The spectral variables evaluated were wavelengths and vegetation indices (NDVI, SAVI, GNDVI, NDRE, SCCCI, EVI, and MSAVI). The genotypes Maracai and Foco showed the highest grain yields throughout the crop seasons, in addition to belonging to the groups with the highest means for all VIs. YIE was positively correlated with the NDVI and certain wavelengths (735 and 790 nm), indicating that genotypes with higher values for these spectral variables are more productive. By path analyses, GNDVI and NDRE had the highest direct effects on the dependent variable DM, while NDVI had a higher direct effect on YIE.
conclusionsOur findings revealed that early and productive genotypes can be selected based on vegetation indices and wavelengths. Soybean genotypes with a high grain yield have higher means for NDVI and certain wavelengths (735 and 790 nm). Early genotypes have higher means for NDRE and GNDVI. These results reinforce the importance of high-throughput phenotyping as an essential tool in soybean breeding programs.
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