Assessment of Physicochemical Properties of Cashew Apple through Computer Vision – Original Images, Data, and R Script

Three files have been attached: (1) Raw input images, (2) Wet chemistry data of cashew apples, (3) R script used for analysis in the study.
(1) The presentation contains the original input images (6 varieties of cashew apple, 2 sample types [slice & whole], at 2 maturity stages [817 & 819]) and a glimpse of the preprocessing for generating input images for image-based metrics using the ImageJ plugin developed in this work. These were used for the proposed research paper “Assessment of Physicochemical Properties of Cashew Apple through Computer Vision.”
(2) An MS Excel data of the wet chemistry analysis for 15 parameters of 6 varieties of cashew apples at 2 maturity stages with 3 replications is given in this file. The mean values of these 15 parameters were used as dependent variables in the study.
(3) For achieving data analysis using the 144 image-based metrics generated from the plugin using the above images. An R program was developed to (i) determine the strength of association between the wet chemistry and image-based parameters and graphically visualize the correlation, (ii) evaluate the range and ranking of the parameters correlation, (iii) develop the top three linear prediction models of wet chemistry based on the image-based parameters, and (iv) perform prediction and validation with visualization, employing the top-ranked prediction model to unseen images. The R script also includes the necessary data set used for the analyses.

Files: Input-images-used-for-image-analysis.pdf, Wet chemistry data of cashew apples.xlsx, and CashewApple-All.R.