Unverified paper record
Metabolite-derived spectral modelling can differentiate heat and drought stress under hot-dry environments
Remote Sensing of Environment · 1 Oct 2025
Abstract
Increasing combined heat and drought extremes due to climate change heighten the risk of crop failure, underscoring the need for improved stress diagnosis for effective management strategies. However, current plant physiology indicators struggle to differentiate crop stresses in hot-dry environments. This study proposes using specific leaf metabolites, detectable by leaf reflectance spectra, for more precise identification of heat and drought stress compared to traditional methods. We conducted two rounds of one-week drought treatments under heat stress on soybean seedlings. Throughout the experiment, we monitored stomatal conductance, reflectance spectra, and metabolites, including Abscisic Acid (ABA), Jasmonic Acid (JA), Salicylic Acid (SA), and proline (Pro), on a daily basis. Our findings revealed that ABA and JA exhibited differential sensitivities to drought and heat stress, respectively. In contrast, stomatal conductance was unable to differentiate between the two stressors. Using partial least-squares regression (PLSR), we determined that both ABA and JA could be detected via leaf spectroscopy with moderate predictive performance (R² = 0.53, relative RMSE = 14.28 %; R² = 0.53, relative RMSE = 14.96 %) and exhibited distinct sensitive spectral signatures. The metabolite-derived, stress-specific spectral models enable more precise and earlier diagnosis and differentiation of stress in a hot-dry environment than traditional physiological indicators (e.g., relying on stomatal conductance). This study provides an example of using metabolites as novel stress indicators, which could contribute to precision agriculture, offering the potential for accurate, stress-specific, and pre-physiological detection of crop health.
Plant phenotyping relevance
葉の反射スペクトルとPLSRにより、熱・ drought stressに関連する代謝物を推定し、植物ストレス状態を識別する手法の開発・検証が研究の中心である。
abstractThis study proposes using specific leaf metabolites, detectable by leaf reflectance spectra, for more precise identification of heat and drought stress compared to traditional methods.
abstractUsing partial least-squares regression (PLSR), we determined that both ABA and JA could be detected via leaf spectroscopy with moderate predictive performance
abstractThe metabolite-derived, stress-specific spectral models enable more precise and earlier diagnosis and differentiation of stress in a hot-dry environment than traditional physiological indicators
Code and data availability
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