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A Scientific Reports study applies interpretable machine learning to a large yield monitor dataset of 134 US maize and soybean crop-site-years. The models predict yield with R² above 0.87 and use Shapley values to rank the effects of weather, soil and terrain.
The authors aim to inform breeding and precision management.
The study improves understanding of which environmental factors limit yields, which may help future supply forecasting. It has no immediate effect on prices.
在过去 2,467 次天气事件之后,玉米 在 5 个交易日内中位数变动 +0.1%(51% 上涨;中间一半区间为 -1.5% 至 +1.7%),20 个交易日内为 +0.6%。
在过去 1,964 次天气事件之后,大豆 在 5 个交易日内中位数变动 +0.1%(51% 上涨;中间一半区间为 -1.7% 至 +1.8%),20 个交易日内为 +0.3%。
各商品基准价相对事件前最后收盘价的变动。历史数据汇总同类过往事件;仅描述已发生的情况,不代表未来走势。不构成投资建议。