## 1 Introduction  
Plants play a vital role in the life of human beings and animals. They are major sources of food, medicine, shelter, etc. Plant phenotyping is becoming essential with the increase in food demand globally. It deals with the quantitative measurement of the structural and functional properties of plants--that is, the process of determining plant traits such as chlorophyll content, water content, leaf surface area, and leaf count, and disease identification. The conventional methods involve the manual measurement of the key plant traits. These methods depend on the knowledge of plant breeding experts and farmers. The drawbacks of the conventional methods are that they are expensive, inaccurate, and time-consuming, and many of them are destructive in nature. To overcome these difficulties and limitations, modern researchers are using computer vision techniques [1] and deep learning models in plant phenotyping. Recently, global agriculture and modern research programs have faced difficulties in plant breeding [2]. Many plant phenotyping communities have been developed in different countries and are involved in solving problems in plant phenotyping. Many researchers have worked on various plant phenotyping methods to identify plant traits from plant images. [PERSON] and [PERSON] [3] developed an occluded object segmentation method for plant phenotyping. [PERSON] and [PERSON] [4; 5] developed various plant segmentation and leaf counting models for plant phenotyping. [PERSON] et al. [6] identified the growth signatures of rosette plants from time-lapse video. [PERSON] et al. [7] studied various methods to extract the tree leaves from natural plant images. [PERSON] et al. [8] developed a low-Cost chlorophyll fluorescence imaging to detect the stress in Catharanthus roseus plants. [PERSON] et al. [9] developed a spatio-temporal spectral framework for plant stress phenotyping. [PERSON] et al. [10] conducted a study in an environmental condition where only white root rot disease stress was applied to avocado roots and the other conditions favored plant growth. This study was conducted to provide information on physiological change that occurs during the initial stages of R. necatrix infection on avocado roots. It showed the effect of root rot disease on leaf chlorophyll content. Biotic and abiotic plant stresses act as important factors for crop yield. In order to protect the plants from these stresses and to prevent a reduction in crop yield, plant breeders depend on plant phenotyping methods and genetic tools to accurately identify plant traits. Korean ginseng ([PERSON]) is a famous herbal plant that is sensitive to biotic stress. It is a shade-loving plant and useful for strengthening human immunity. It is highly sensitive to heat stress [11; 12]. The roots of Korean ginseng have high pharmacological efficacy [13]. The size, appearance, and shape of the roots determine the quality and value of the roots. Generally, Ginseng plants are cultivated for several years, and the roots of the plants are harvested for sale between the fourth and sixth years. Ginseng roots are at risk of soil-borne diseases caused by nematodes, fungi, and bacteria in these long cultivation periods [14]. Among these fungi are the most common pathogens causing various diseases such as anthracose, alternaria blight, root rot, gray mold, botrytis blight, etc. [15; 16]. The fungus Cylindrocarbon destructans is one of the most harmful pathogens, causing root rot and rusty root disease. Root rot disease can significantly reduce ginseng production [17; 18; 19; 20]. Cylindrocarbon destructans also gives rise to thick-walled resting spores known as chlamdospores that can survive for more than 10 years in the soil. This can lead to the development of root rot disease at any point of time while the spores remain in the soil [21]. The root rot disease in grapevine plants cause symptoms in aboveground plant region [22; 23; 24]. These include stunted shoots, wilting leaves, low fruit production and dwarf leaves.