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  "Title": "Fresh Weight Determination from Visual Image of the Plant",
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  "Authors@R": "c(person(\"Tanuj\", \"Misra \", role = c(\"aut\", \"cre\"),\nemail = \"tanujmisra102@gmail.com\"),\nperson(\"Alka\", \"Arora\", role = \"aut\", email = \"Alka.Arora@icar.gov.in\"),\nperson(\"Sudeep\", \"Marwaha\", role = \"aut\", email = \"Sudeep.Marwaha@icar.gov.in\"),\nperson(\"Shailendra\", \"Kumar\", role = \"aut\", email = \"shailendrabujhansi@gmail.com\"),\nperson(\"Mrinmoy\", \"Ray\", role = \"aut\", email = \"mrinmoy4848@gmail.com\"),\nperson(\"Sudhir\", \"Kumar\", role = \"aut\", email = \"sudhirnpf@gmail.com\"),\nperson(\"Sayanti Guha\", \"Majumder\", role = \"aut\", email = \"sayanti23gm@gmail.com\")\n)",
  "Maintainer": "Tanuj Misra <tanujmisra102@gmail.com>",
  "Description": "Fresh biomass determination is the key to evaluating crop\ngenotypes' response to diverse input and stress conditions and\nforms the basis for calculating net primary production.\nHowever, as conventional phenotyping approaches for measuring\nfresh biomass is time-consuming, laborious and destructive,\nimage-based phenotyping methods are being widely used now. In\nthe image-based approach, the fresh weight of the above-ground\npart of the plant depends on the projected area. For\ndetermining the projected area, the visual image of the plant\nis converted into the grayscale image by simply averaging the\nRed(R), Green (G) and Blue (B) pixel values. Grayscale image is\nthen converted into a binary image using Otsu’s thresholding\nmethod Otsu, N. (1979) <doi:10.1109/TSMC.1979.4310076> to\nseparate plant area from the background (image segmentation).\nThe segmentation process was accomplished by selecting the\npixels with values over the threshold value belonging to the\nplant region and other pixels to the background region. The\nresulting binary image consists of white and black pixels\nrepresenting the plant and background regions. Finally, the\nnumber of pixels inside the plant region was counted and\nconverted to square centimetres (cm2) using the reference\nobject (any object whose actual area is known previously) to\nget the projected area. After that, the projected area is used\nas input to the machine learning model (Linear Model,\nArtificial Neural Network, and Support Vector Regression) to\ndetermine the plant's fresh weight.",
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    "Date": "2026-05-08 07:12:23 UTC",
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  "Author": "Tanuj Misra [aut, cre], Alka Arora [aut], Sudeep Marwaha [aut],\nShailendra Kumar [aut], Mrinmoy Ray [aut], Sudhir Kumar [aut],\nSayanti Guha Majumder [aut]",
  "Repository": "https://cran.r-universe.dev",
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