Visible and Near-Infrared Spectroscopy for Investigation of Water and Nitrogen Stress in Tomato Plants
The main objective of this study was to evaluate the possibilities of visible-near-infrared spectroscopy for investigating water and nitrogen stress in tomato plants. Two varieties of tomato plants (Red Bounty and Manusa) were grown in a greenhouse. Plants were divided into three groups: control, reduced nitrogen fertilization, and reduced watering. Spectral measurements of tomato leaves were made on-site. A USB4000 spectrometer for 450–1100 nm and a handheld AlbaNIR for the 900–1650 nm region were used for the spectra acquisition. Twenty-four vegetative indices were calculated using the reflectance characteristics of plants. Soft Independent Modeling of Class Analogy (SIMCA) models were developed for classification. Additionally, aquagrams were calculated. Results show differences between the spectra of leaves from control and stressed plants for both tomato varieties. Aquagrams clearly show the differences in water structures in the three groups of plants. The performance of developed SIMCA models for discriminating plants according to growing conditions was very high. The total accuracy was between 86.89% and 97.09%. Several vegetation indices successfully differentiate control and stressed plants for both tomato varieties. The results show successful differentiation of the control and stressed tomato plants based on spectral characteristics of the plants’ leaves in the visible and near-infrared region.
Authors
- Petya Veleva (ORCID: https://orcid.org/0000-0001-7813-6387)
- Dimitar Yorgov
- Stefka Atanassova (ORCID: https://orcid.org/0000-0003-1797-9879)
- Antoniya Petrova (ORCID: https://orcid.org/0009-0004-4616-6150)
- Roksana Mineva
Institutions
- Trakia University (BG)
Publication Details
- Journal
- AgriEngineering
- Published
- 2025-05-14
- DOI
- https://doi.org/10.3390/agriengineering7050155
- Citations
- 5
- Primary Topic
- Spectroscopy and Chemometric Analyses
- Type
- article
- Field-Weighted Citation Impact
- 3.76
Funders
- Bulgarian National Science Fund