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<p>Drought stress is a major constraint on sugarcane productivity, necessitating efficient and scalable phenotyping methods for precision agriculture. Previous studies have established general relationships between spectral reflectance and plant stress, but the cultivar-specific coupling between leaf spectral reflectance and photosynthetic physiology under drought remains poorly characterized. This study investigated the spectro-physiological responses of four sugarcane cultivars with contrasting drought tolerance (GT42, GT44, ROC22, ROC16) following 30&#xa0;days of water withholding. Drought stress significantly inhibited photosynthetic function in a cultivar-dependent manner. The sensitive cultivar (ROC16) exhibited the most severe impairment (56.85–83.30% reduction in SPAD, Pn, Tr, and Gs), while tolerant cultivars (GT42, GT44) maintained better physiological homeostasis. These physiological differences were mirrored in the spectral domain. All cultivars showed a blue shift in the red-edge position and decreased red-edge slope under drought, with changes most pronounced in ROC16. Correlation analysis revealed robust spectro-physiology linkages: the red-edge chlorophyll index (CIred edge) was strongly correlated with net photosynthetic rate (Pn, r = 0.867), the photochemical reflectance index (PRI) with chlorophyll content (SPAD, r = 0.825), and the normalized difference vegetation index (NDVI) with stomatal conductance (Gs, r = 0.857). We conclude that sugarcane’s spectral and physiological responses to drought are inherently cultivar-dependent. The indices SI1, PRI, and NDVI are identified as optimal, specific proxies for monitoring photosynthetic function, pigment status, and stomatal behavior, respectively. These findings provide a critical technical basis for cultivar-specific drought phenotyping and hold significant potential for advancing precision irrigation and smart sugarcane agriculture.</p>

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Coupling of Leaf Spectral Reflectance with Photosynthetic Physiology in Sugarcane Under Drought Stress

  • 期刊论文

  • 发表日期：

    2026年4月22日

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  • Haiwei Chu,
  • Liyi Chen,
  • Meiyan Wu,
  • Shijian Han,
  • Zhenli He,
  • Yangrui Li,
  • Suli Li,
  • Zhigang Li

摘要

Drought stress is a major constraint on sugarcane productivity, necessitating efficient and scalable phenotyping methods for precision agriculture. Previous studies have established general relationships between spectral reflectance and plant stress, but the cultivar-specific coupling between leaf spectral reflectance and photosynthetic physiology under drought remains poorly characterized. This study investigated the spectro-physiological responses of four sugarcane cultivars with contrasting drought tolerance (GT42, GT44, ROC22, ROC16) following 30 days of water withholding. Drought stress significantly inhibited photosynthetic function in a cultivar-dependent manner. The sensitive cultivar (ROC16) exhibited the most severe impairment (56.85–83.30% reduction in SPAD, Pn, Tr, and Gs), while tolerant cultivars (GT42, GT44) maintained better physiological homeostasis. These physiological differences were mirrored in the spectral domain. All cultivars showed a blue shift in the red-edge position and decreased red-edge slope under drought, with changes most pronounced in ROC16. Correlation analysis revealed robust spectro-physiology linkages: the red-edge chlorophyll index (CIred edge) was strongly correlated with net photosynthetic rate (Pn, r = 0.867), the photochemical reflectance index (PRI) with chlorophyll content (SPAD, r = 0.825), and the normalized difference vegetation index (NDVI) with stomatal conductance (Gs, r = 0.857). We conclude that sugarcane’s spectral and physiological responses to drought are inherently cultivar-dependent. The indices SI1, PRI, and NDVI are identified as optimal, specific proxies for monitoring photosynthetic function, pigment status, and stomatal behavior, respectively. These findings provide a critical technical basis for cultivar-specific drought phenotyping and hold significant potential for advancing precision irrigation and smart sugarcane agriculture.