A multimodal image sensor system for identifying water stress ingrapevines
2012
Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth.
In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to
balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal
sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water
stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G,
and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the
different water stress levels. This research aims at solving the aforementioned problems. The core technology of this
multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to
improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which
could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired
images, color features based on color space and reflectance features based on image process method were calculated.
The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are
needed to validate the conclusion.
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