Articles
Vegetation indices to monitor water and chlorophyll content of tomato leaves
Article number
1445_34
Pages
243 – 248
Language
English
Abstract
Plant monitoring is not only an issue in the case of plants grown indoors but also affects the crops cultivated in the field more and more.
In conjunction with the development of precision agriculture, numerous vegetation indices came to light.
The problem of which vegetation index (VI) to apply to a given task can be confusing.
Thus, an experiment was carried out to reveal which VI is the best alternative to monitor the water and chlorophyll content of tomato leaves.
Four levels of water supply treatment were applied to the H1015 processing tomato cultivar in the experimental field of the Institute of Horticultural Science at Gödöllő, Hungary in 2023. The relative water content (RWC) and chlorophyll content (CC) were measured three times during the growing season specifically in the phase of flowering, and fruit development and in the beginning of the ripening phase.
The chlorophyll content of leaves was determined by HPLC. Simultaneously with the laboratory measurements, the non-destructive hyperspectral reflectance spectrum (VIS/NIR) was collected from the different treatments in the field.
Overall, 228 VIs were involved in the study and the correlation between RWC and CC with the VIs was evaluated.
Depending on the nature of VI, both strong positive and strong negative correlations were discovered in the case of RWC and CC, with many VIs.
The highest correlation with RWC was r=0.95 in the case of SR678/750 (Simple ratio 678/750). The strongest correlation coefficient was negative (r=-0.87) registered between total CC and the FR index (Simple Ratio 690/735 Fluorescence ratio). When the correlations were investigated separately to chlorophyll-a and chlorophyll-b, the results were very similar to when the total chlorophyll was involved.
The study revealed that some simple ratio index can be used well in the monitoring of RWC and CC in tomato leaves in the field.
However, more data must be collected from different growing seasons, genotypes and locations to build a larger database and draw more reliable conclusions.
In conjunction with the development of precision agriculture, numerous vegetation indices came to light.
The problem of which vegetation index (VI) to apply to a given task can be confusing.
Thus, an experiment was carried out to reveal which VI is the best alternative to monitor the water and chlorophyll content of tomato leaves.
Four levels of water supply treatment were applied to the H1015 processing tomato cultivar in the experimental field of the Institute of Horticultural Science at Gödöllő, Hungary in 2023. The relative water content (RWC) and chlorophyll content (CC) were measured three times during the growing season specifically in the phase of flowering, and fruit development and in the beginning of the ripening phase.
The chlorophyll content of leaves was determined by HPLC. Simultaneously with the laboratory measurements, the non-destructive hyperspectral reflectance spectrum (VIS/NIR) was collected from the different treatments in the field.
Overall, 228 VIs were involved in the study and the correlation between RWC and CC with the VIs was evaluated.
Depending on the nature of VI, both strong positive and strong negative correlations were discovered in the case of RWC and CC, with many VIs.
The highest correlation with RWC was r=0.95 in the case of SR678/750 (Simple ratio 678/750). The strongest correlation coefficient was negative (r=-0.87) registered between total CC and the FR index (Simple Ratio 690/735 Fluorescence ratio). When the correlations were investigated separately to chlorophyll-a and chlorophyll-b, the results were very similar to when the total chlorophyll was involved.
The study revealed that some simple ratio index can be used well in the monitoring of RWC and CC in tomato leaves in the field.
However, more data must be collected from different growing seasons, genotypes and locations to build a larger database and draw more reliable conclusions.
Authors
S. Takács, R. Ilahy, G. Palotás, J. Asbót-Posgay, Z. Pék, H.G. Daood, L. Helyes
Keywords
leaf monitoring, water stress, plant monitoring, reflectance, spectrum
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