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May 16, 2026Scientific ReportsOpen Access

Prediction of short‑term drought variation in tea plantations using a LASSO-COX-NOMOGRAM approach

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Authors

BWBaijuan WangWYWenxia YuanJZJihong Zhou

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Overview

Randomized trial demonstrates strong drought prediction in tea plantations, indicating potential for improved crop yield.

Key Points

  • The aim is to develop a predictive model for short-term drought in tea plantations using climatic data.
  • Developed a LASSO-Cox-nomogram model using multisource climatic data.
  • Conducted Limma differential analysis to examine climatic variables under varying drought severities.
  • Applied fivefold cross-validation and multivariate Cox analysis for model establishment.
  • Achieved AUC values of 0.776, 0.762, and 0.777 for varying soil moisture content changes in the training set.
  • Validation set AUC values were found to be 0.742, 0.799, and 0.710, showing robust predictive ability.
  • Demonstrated a temporal hold-out testing accuracy of 78.57%.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/6a0808ffa487c87a6a40b117https://doi.org/10.1038/s41598-026-52694-2
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