Identifying population genetic structure (PGS) is crucial for breeding and conservation. Several clustering algorithms are available to identify the underlying PGS to be used with genetic data of maize genotypes. In this work, six methods to identify PGS from unlinked molecular marker data were compared using simulated and experimental data consisting of multilocus-biallelic genotypes. Datasets were delineated under different biological scenarios characterized by three levels of genetic divergence among populations (low, medium, and high FST) and two numbers of sub-populations (K=3 and K=5). The relative performance of hierarchical and non-hierarchical clustering, as well as model-based clustering (STRUCTURE) and clustering from neural networks (SOM-RP-Q). We use the clustering error rate of genotypes into discrete sub-populations as comparison criterion. In scenarios with great level of divergence among genotype groups all methods performed well. With moderate level of genetic divergence (FST=0.2), the algorithms SOM-RP-Q and STRUCTURE performed better than hierarchical and non-hierarchical clustering. In all simulated scenarios with low genetic divergence and in the experimental SNP maize panel (largely unlinked), SOM-RP-Q achieved the lowest clustering error rate. The SOM algorithm used here is more effective than other evaluated methods for sparse unlinked genetic data.

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Drought severely affects soybean productivity, challenging breeding/management strategies to increase crop resilience. Hormone-based biostimulants like brassinosteroids (BRs) modulate growth/defence trade-off, mitigating yield losses; yet, natural molecule's low stability challenges the development of cost-effective and long-lasting analogues. Here, we investigated for the first time the effects of BR functional analogue DI-31 in soybean physiology under drought by assessing changes in growth, photosynthesis, water relations, antioxidant metabolism, nodulation, and nitrogen homeostasis. Moreover, DI-31 application frequencies' effects on crop cycle and commercial cultivar yield stabilisation under drought were assessed. A single foliar application of DI-31 favoured plant drought tolerance, preventing reductions in canopy development and enhancing plant performance and water use since the early stages of stress. The analogue also increased the antioxidant response, favouring nitrogen homeostasis maintenance and attenuating the nodular senescence. Moreover, foliar applications of DI-31 every 21 days enhanced the absolute yield by ~ 9% and reduced drought-induced yield losses by ~ 7% in four commercial cultivars, increasing their drought tolerance efficiency by ~ 12%. These findings demonstrated the practical value of DI-31 as an environmentally friendly alternative for integrative soybean resilience management under drought.