Drought in sub-Saharan Africa is a huge problem that impacts how maize grows and reduces the harvest. Dealing with drought is complex because many different genes are involved. That's why scientists tried something new.

      Researchers took 236 different types of corn and tested them in multiple environments. By using seven different GWAS models, they wanted to understand the genetic secrets behind maize's performance.  Genes under optimum and drought stress were analyzed. To simplify the data, the best linear unbiased estimator (BLUEs) calculation was used. The team also looked at predictions using a model called RR-BLUP.

     Drought doesn't just hurt yield; it also messes with the timing of when the maize flowers. When flowers delay or alter, the plant's life cycle gets out of whack. This is why predicting how maize will grow under drought conditions is so tricky.

      To make the analysis comprehensive, the study looked at various models.  mrlm (Multivariate Residual Maximum Likelihood), FASTMRMLM, FASTmREMM A, and more provided new perspectives, along with FASTMRMLM.

      The approach can help researchers and farmers predict and solve the dry season issues for maize. The ultimate goal is to improve maize harvests during drought and optimal conditions.

      The prediction models used mathematical equations to make sense of the vast amounts of genetic data. Genomic prediction models provided insights across different locations and conditions. These models tested under drought and optimal conditions showed valuable insights.   RR-BLUP allowed researchers to make sensible guesses about how the maize would perform in different environments.

     The study included maize lines from Africa and the Americas.

     The study expanded the comprehension of drought-resilient maize traits, but there is still a lot to learn.   Combining this data with more field testing could lead to breakthroughs.

How Are Scientists Solving Drought Issues with Maize?

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