首页|Leveraging Soil Mapping and Machine Learning to Improve Spatial Adjustments in Plant Breeding Trials
Leveraging Soil Mapping and Machine Learning to Improve Spatial Adjustments in Plant Breeding Trials
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from biorxiv.org:“Spatial adjustments are used to improve the estimate of plot seed yield across crops and geographies.Moving mean and P-Spline are examples of spatial adjustment methods used in plant breeding trials todeal with field heterogeneity. Within trial spatial variability primarily comes from soil feature gradients,such as nutrients, but study of the importance of various soil factors including nutrients is lacking.
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