• Smart Media Journal
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• v.13 no.7
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• pp.36-44
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• 2024

Identifying plant species and diseases is crucial for maintaining biodiversity and achieving optimal crop yields, making it a topic of significant practical importance. Recent studies have extended plant disease recognition from traditional closed-set scenarios to open-set environments, where the goal is to reject samples that do not belong to known categories. However, in open-world tasks, it is essential not only to define unknown samples as "unknown" but also to classify them further. This task assumes that images and labels of known categories are available and that samples of unknown categories can be accessed. The model classifies unknown samples by learning the prior knowledge of known categories. To the best of our knowledge, there is no existing research on this topic in plant-related recognition tasks. To address this gap, this paper utilizes knowledge distillation to model the category space relationships between known and unknown categories. Specifically, we identify similarities between different species or diseases. By leveraging a fine-tuned model on known categories, we generate pseudo-labels for unknown categories. Additionally, we enhance the baseline method's performance by using a larger pre-trained model, dino-v2. We evaluate the effectiveness of our method on the large plant specimen dataset Herbarium 19 and the disease dataset Plant Village. Notably, our method outperforms the baseline by 1% to 20% in terms of accuracy for novel category classification. We believe this study will contribute to the community.

• The Plant Pathology Journal
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• v.36 no.4
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• pp.346-354
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• 2020

Pectobacterium, which causes soft rot disease, is divided into 18 species based on the current classification. A total of 225 Pectobacterium strains were isolated from 10 main cultivation regions of potato (Solanum tuberosum), napa cabbage (Brassica rapa subsp. pekinensis), and radish (Raphanus sativus) in South Korea; 202 isolates (90%) were from potato, 18 from napa cabbage, and five from radish. Strains were identified using the Biolog test and phylogenetic analysis. The pathogenicity and swimming motility were tested at four different temperatures. Pectolytic activity and plant cell-wall degrading enzyme (PCWDE) activity were evaluated for six species (P. carotovorum subsp. carotovorum, Pcc; P. odoriferum, Pod; P. brasiliense, Pbr; P. versatile, Pve; P. polaris, Ppo; P. parmentieri, Ppa). Pod, Pcc, Pbr, and Pve were the most prevalent species. Although P. atrosepticum is a widespread pathogen in other countries, it was not found here. This is the first report of Ppo, Ppa, and Pve in South Korea. Pectobacterium species showed stronger activity at 28℃ and 32℃ than at 24℃, and showed weak activity at 37℃. Pectolytic activity decreased with increasing temperature. Activity of pectate lyase was not significantly affected by temperature. Activity of protease, cellulase, and polygalacturonase decreased with increasing temperature. The inability of isolated Pectobacterium to soften host tissues at 37℃ may be a consequence of decreased motility and PCWDE activity. These data suggest that future increases in temperature as a result of climate change may affect the population dynamics of Pectobacterium.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.959-968
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• 2019

In the agricultural industry, wireless sensor network technology has being applied by utilizing various sensors and embedded systems. In particular, a lot of researches are being conducted to diagnose diseases of crops early by using sensor network. There are some difficulties on traditional research how to diagnose crop diseases is not practical for agriculture. This paper proposes the algorithm which enables to investigate and analyze the crop leaf image taken by image camera and detect the infected area within the image. We applied the enhanced k-means clustering method to the images captured at horticulture facility and categorized the areas in the image. Then we used the edge detection and edge tracking scheme to decide whether the extracted areas are located in inside of leaf or not. The performance was evaluated using the images capturing tomato leaves. The results of performance evaluation shows that the proposed algorithm outperforms the traditional algorithms in terms of classification capability.

• The Plant Pathology Journal
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• v.39 no.4
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• pp.409-416
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• 2023

Bacterial leaf blight of carrots caused by Xanthomonas hortorum pv. carotae (Xhc) is an important worldwide seed-borne disease. In 2012 and 2013, symptoms similar to bacterial leaf blight were found in carrot farms in Jeju Island, Korea. The phenotypic characteristics of the Korean isolation strains were similar to the type strain of Xhc. Pathogenicity showed symptoms on the 14th day after inoculation on carrot plants. Identification by genetic method was multi-position sequencing of the isolated strain JJ2001 was performed using four genes (danK, gyrB, fyuA, and rpoD). The isolated strain was confirmed to be most similar to Xhc M081. Furthermore, in order to analyze the genetic characteristics of the isolated strain, whole genome analysis was performed through the next-generation sequencing method. The draft genome size of JJ2001 is 5,443,372 bp, which contains 63.57% of G + C and has 4,547 open reading frames. Specifically, the classification of pathovar can be confirmed to be similar to that of the host lineage. Plant pathogenic factors and determinants of the majority of the secretion system are conserved in strain JJ2001. This genetic information enables detailed comparative analysis in the pathovar stage of pathogenic bacteria. Furthermore, these findings provide basic data for the distribution and diagnosis of Xanthomonas hortorum pv. carotae, a major plant pathogen that infects carrots in Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.1
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• pp.23-28
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• 2002

Sets of weather variables for estimation of LWD were evaluated using CART(Classification And Regression Tree) models. Input variables were sets of hourly observations of air temperature at 0.3-m and 1.5-m height, relative humidity(RH), and wind speed that were obtained from May to September in 1997, 1998, and 1999 at 15 weather stations in iowa, Illinois, and Nebraska, USA. A model that included air temperature at 0.3-m height, RH, and wind speed showed the lowest misidentification rate for wetness. The model estimated presence or absence of wetness more accurately (85.5%) than the CART/SLD model (84.7%) proposed by Gleason et al. (1994). This slight improvement, however, was insufficient to justify the use of our model, which requires additional measurements, in preference to the CART/SLD model. This study demonstrated that the use of measurements of temperature, humidity, and wind from automated stations was sufficient to make LWD estimations of reasonable accuracy when the CART/SLD model was used. Therefore, implementation of crop disease-warning systems may be facilitated by application of the CART/SLD model that inputs readily obtainable weather observations.

• Research in Plant Disease
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• v.23 no.3
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• pp.249-255
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• 2017

The rice blast fungus is a representative model phytopathogenic fungus in which Gene-for-Gene interaction with host rice is applicable. After 1980, eight differential varieties have been constructed and classified to analyze the race of rice blast isolates in Korea. However, since there is limited information about the genetic background of rice blast resistance genes within the Korean differentials, scientific analysis on the emergence of new race or resistance break down was difficult. Recently, a differential system has been developed using monogenic resistance lines to understand the interactions of pathogen race and rice resistance genes. In this study, a total of 50 isolates were selected from four different races isolated in Korea, and they were inoculated into monogenic lines. As a result, the isolates in the same race classified by the Korean differential system reacted differently in single monogenic lines. This suggests that the isolates categorized as the same race group contains different avirulence genes and furthermore, it is presumed that the Korean differential system is difficult to provide useful information for breeding program. For this reason, introduction of differential system using monogenic resistance lines is required in addition to the current system.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• The Plant Pathology Journal
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• v.39 no.2
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• pp.171-180
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• 2023

Spring black stem and leaf spot, caused by Phoma medicaginis, is an issue in annual Medicago species. Therefore, in this study, we analyzed the response to P. medicaginis infection in a collection of 46 lines of three annual Medicago species (M. truncatula, M. ciliaris, and M. polymorpha) showing different geographic distribution in Tunisia. The reaction in the host to the disease is explained by the effects based on plant species, lines nested within species, treatment, the interaction of species × treatment, and the interaction of lines nested within species × treatment. Medicago ciliaris was the least affected for aerial growth under infection. Furthermore, the largest variation within species was found for M. truncatula under both conditions. Principal component analysis and hierarchical classification showed that M. ciliaris lines formed a separate group under control treatment and P. medicaginis infection and they are the most vigorous in growth. These results indicate that M. ciliaris is the least susceptible in response to P. medicaginis infection among the three Medicago species investigated here, which can be used as a good candidate in crop rotation to reduce disease pressure in the field and as a source of P. medicaginis resistance for the improvement of forage legumes.

• Journal of the Ergonomics Society of Korea
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• v.30 no.4
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• pp.451-458
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• 2011

Objective: This study is to develop a design and evaluation guide to the ergonomic design of the farm working convenient equipments in order for the elderly to use them easily and safely. Background: The aging population has already increased in farm villages. But due to the usage of the farm working equipments that did not reflect the characteristics and functional changes of aging, accidents and patients with disease are increasing. Method: The study investigated the functional changes and physical, cognitive, and sensuous characteristics of the aged. By determining the criteria for classification of the convenient equipments by crop, and by finding out the items necessary for the ergonomic design, a guide to this study is proposed. Results: It is obvious that the physical, cognitive and sensuous functions change as the aging process continues. Therefore, for the design and evaluation of Control Panel, Control Lever, Frame Size, Shape, and Equipment Weight that are the necessary items for the ergonomic approach for the farm working equipments, such characteristics have to be reflected. Conclusion: Through this study, a guide to the design and evaluation of convenient equipments for the farm works that reflected the aging characteristics and functional changes has been proposed. Application: The result of this study is to expect not only designers but also related specialists to make the best use of it.

• The Korean Journal of Mycology
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• v.45 no.2
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• pp.132-138
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• 2017

To obtain useful data on root rot in Korean ginseng, we performed phylogenetic analysis and pathogenicity test for Cylindrocarpon destructans isolated from peony. Cylindrocarpon destructans isolates from peony were proven to cause ginseng root rot. The isolate KACC44663 was identified as Ilyonectria robusta under the new classification system, which belongs to the I. radicicola species complex. This is the first report of the pathogenic isolate, which was isolated from another host plant, but not ginseng, that can cause root rot disease on ginseng in Korea.