Predicting capsicum leaf water stress using mid-infrared ATR-FTIR spectroscopy.

Area of Science:

• Plant Physiology
• Spectroscopy
• Agricultural Science

Background:

• Leaf water status is crucial for irrigation scheduling and early stress detection in crops.
• Traditional spectroscopic methods often rely on near-infrared features, limiting broader application.
• Mid-infrared (MIR) spectroscopy offers potential for detailed biochemical analysis of plant tissues.

Purpose of the Study:

• To develop practical prediction models for leaf water traits using MIR ATR-FTIR spectroscopy.
• To assess the efficacy of specific MIR spectral bands and ratios for estimating water content in capsicum leaves.
• To evaluate MIR spectroscopy as a rapid, low-preparation method for plant water stress assessment.

Main Methods:

• Capsicum leaves were subjected to a 10-day controlled dehydration period.
• Attenuated Total Reflectance Fourier-Transform Infrared (ATR-FTIR) spectra were collected (4000-450 cm⁻1) with minimal sample preparation.
• Leaf water traits, including fuel moisture content (FMC), equivalent water thickness (EWT), and specific leaf weight (SLW), were quantified.
• Prediction models were developed using single MIR bands and band ratios, with performance evaluated by R² and RMSE.

Main Results:

• Water-related MIR bands at 3370 cm⁻1 and 1641 cm⁻1 showed significant responses to dehydration.
• Simple band ratios provided stronger predictions than single bands for FMC, EWT, and SLW.
• The best band ratio models achieved R² values of 0.81 for FMC, 0.72 for EWT, and 0.62 for SLW.
• Predicted-versus-measured performance yielded R² values of 0.72 (FMC), 0.68 (EWT), and 0.52 (SLW).

Conclusions:

• MIR ATR-FTIR spectroscopy, combined with selected band ratios, offers a rapid, low-preparation approach for estimating capsicum leaf water traits.
• This method supports plant-based water stress assessment under controlled dehydration conditions.
• Further validation with larger datasets and standardized conditions is necessary for operational irrigation management applications.