Harnessing Big Data for Apple Breeding: Genomic Models to Meet Climate Challenges

In the face of climate change, apple breeding programs need innovative ways to select cultivars that can thrive under diverse conditions. A recent study demonstrates how integrating genomic data with environmental factors such as weather and soil can drastically improve the selection process. By using multi-environmental genomic prediction models, including deep learning, researchers have enhanced the accuracy of predictions for key apple traits. These advancements provide a promising tool for breeding apple varieties that are not only high-yielding but also adaptable to the fluctuating climate, offering a potential breakthrough in ensuring future food security.

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