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

Abstract

Leaf water status is a key indicator for irrigation scheduling and early stress detection, but many spectroscopic prediction studies have mainly relied on near-infrared features. Here, practical prediction models were developed using mid-infrared (MIR) ATR-FTIR spectra of capsicum (Capsicum annuum L.) leaves collected under glasshouse conditions during a 10-day gradual dehydration period, alongside an irrigated control. Spectra (4000-450 cm⁻1) were measured with minimal sample preparation, and leaf water traits were quantified using fuel moisture content (FMC), equivalent water thickness (EWT), and specific leaf weight (SLW). Water-related MIR bands at 3370 and 1641 cm⁻1 showed the most consistent response to dehydration, and simple band ratios generally provided stronger predictions than single bands. The best ratios were A1641/A2159 for FMC (R2 = 0.81; RMSE = 12.80) and A3370/A2849 for EWT (R2 = 0.72; RMSE = 0.0034) and SLW (R2 = 0.62; RMSE = 6.95 × 10⁻4), while predicted-versus-measured performance yielded R2 values of 0.72 for FMC, 0.68 for EWT, and 0.52 for SLW. These results indicate that MIR ATR-FTIR spectroscopy, when coupled with selected band ratios, can provide a rapid, low-preparation laboratory-based approach for estimating capsicum leaf water traits under controlled dehydration, supporting plant-based water stress assessment under controlled conditions and providing a basis for further irrigation-related sensing studies. However, the models are preliminary and require validation with larger independent datasets and tightly standardised measurement conditions before operational use in irrigation management.

Plant phenotyping relevance

MIR ATR-FTIRスペクトルと選択バンド比を用いて、葉の水分形質を推定するセンシング・予測手法の開発と性能評価が中心である。

Code and data availability

The paper reports capsicum leaf water-stress phenotyping (FMC, EWT, SLW) with ATR-FTIR spectra and regression models, but provides no public repository, code, or dataset URL. The spectral/trait datasets are stated to be available only from the corresponding author on request.

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