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Updated: Jun 8, 2025

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A rapid method for assessing seed drought resistance using integrated ID-BOA-SVM.

Qiaohan Wu1, Xiaoyu Zhao1, Biqing Zhou1

  • 1Heilongjiang Bayi Agricultural University, China. xy_zhao77@163.com.

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Summary

Near-infrared spectroscopy (NIR) offers a rapid method for assessing seed drought resistance by analyzing key molecular factors. This approach aids in understanding drought resistance mechanisms and optimizing crop breeding strategies.

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Area of Science:

  • Agricultural Science
  • Spectroscopy
  • Biotechnology

Background:

  • Drought poses a significant threat to global food security, necessitating efficient methods for identifying drought-resistant crops.
  • Traditional methods for assessing seed drought resistance are often time-consuming and labor-intensive.
  • Near-infrared (NIR) spectroscopy presents a promising non-destructive technique for rapid chemical and physical analysis.

Purpose of the Study:

  • To evaluate the efficacy of NIR spectroscopy for high-throughput screening of maize seed drought resistance.
  • To identify key molecular indicators of drought response in seeds using NIR spectral data.
  • To develop and validate advanced machine learning models for accurate classification of drought resistance.

Main Methods:

  • NIR spectroscopy was employed to analyze maize seeds, focusing on water, sugars, amino acids, and gene-related factors.
  • Competitive Adaptive Reweighted Sampling (CARS) identified significant NIR spectral bands associated with drought resistance.
  • An Improved Discrete Bayesian Optimization Support Vector Machine (ID-BOA-SVM) and a stacking ensemble model (RF, ID-BOA-SVM, LR, GBDT) were developed for classification.

Main Results:

  • The developed stacking model achieved high classification performance: 94.28% accuracy, 94% precision, 94.61% recall, and 94.23% F1-score.
  • The models demonstrated robustness against dataset variability and interference, indicating reliable performance.
  • Specific NIR spectral signatures linked to drought resistance markers were successfully identified.

Conclusions:

  • NIR spectroscopy is a viable and efficient tool for large-scale primary screening of seed drought resistance.
  • The findings support the integration of NIR data into genetic and physiological studies of drought-resistant varieties.
  • This research facilitates a deeper understanding of drought resistance mechanisms and aids in optimizing crop breeding strategies for enhanced resilience.