Abstract
Phenomics and chlorophyll fluorescence can help us to understand the various stresses a plant may undergo. In this research work, we observe the image-based morphological changes in the wheat canopy. These changes are monitored by capturing the maximum area of wheat canopy image that has maximum photosynthetic activity (chlorophyll fluorescence signals). The proposed algorithm presented here has three stages: (i) first, derivation of dynamic threshold value by curve fitting of data to eliminate the pixels of low-intensity value, (ii) second, extraction and segmentation of thresholded region by application of histogram-based K-means algorithm iteratively (this scheme of the algorithm is referred to as the curve fit K-means (CfitK-means) algorithm); and (iii) third, computation of 23 grey level cooccurrence matrix (GLCM) texture features (traits) from the wheat images has been done. These features help to do statistical analysis and infer agronomical insights. The analysis consists of correlation, factor, and agglomerative clustering to identify water stress indicators. A public repository of wheat canopy images was used that had normal and water stress response chlorophyll fluorescence images. The analysis of the feature dataset shows that all 23 features are proved fruitful in studying the changes in the shape and structure of wheat canopy due to water stress. The best segmentation algorithm was confirmed by doing exhaustive comparisons of seven segmentation algorithms. The comparisons showed that the best algorithm is CfitK-means as it has a maximum IoU score value of 95.75.
Highlights
Wheat is one of the essential staple food grains of the human race
These fluorescence wave signals are recorded with the help of imaging devices, where reemitted light can be realised as International Journal of Genomics a digital image, and mathematical analysis 4can be done for quantification of photosynthetic activity and water stress in a nondestructive manner [9, 10]
For qualitative comparison of the proposed methodology, the segmentation results on the input image using seven segmentation algorithms, namely, Global Static Thresholding (GST), Global Automatic Thresholding (GAT), K-means based on four mean values, Watershed, mean shift, convolution gradient filters, and curve fit‐based thresholding + K‐means algorithm named as CFitK-means have been shown
Summary
Wheat is one of the essential staple food grains of the human race. As per Indian statistics, 80 percent of water is consumed by just three major crops—rice, wheat, and sugarcane. The markerassisted selection (MAS) method [2] has brought much confidence in current researchers to overcome the challenges of pest attacks and other stresses such as drought [3] This technique primarily involves finding linkages between underline genes by identifying traits or modifying traits [4]. Empirical observations show that when the plant changes its photochemistry, it emits a chlorophyll fluorescence signal which falls under the range of 680 nm to 800 nm as a by-product of photosynthesis [8] These fluorescence wave signals are recorded with the help of imaging devices, where reemitted light can be realised as International Journal of Genomics a digital image, and mathematical analysis 4can be done for quantification of photosynthetic activity and water stress in a nondestructive manner [9, 10]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
