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

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.

Authors

Institutions

Publication Details

Journal
BMC Plant Biology
Published
2026-06-29
DOI
https://doi.org/10.1186/s12870-026-09383-z
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Talal Al-Shukaili, Yaseen Al-Mulla, Seham Al-Mahrouqi
BMC Plant Biology
Spectroscopy and Chemometric Analyses
article

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

Talal Al-Shukaili, Yaseen Al-Mulla, Seham Al-Mahrouqi
article en

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.

BMC Plant Biology
Sultan Qaboos University (OM)
Sultan Qaboos University
Clean water and sanitation
Openalex Percentile: Top 11%
Spectroscopy and Chemometric Analyses
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.