scholarly journals Superiority Verification of Deep Learning in the Identification of Medicinal Plants: Taking Paris polyphylla var. yunnanensis as an Example

2021 ◽  
Vol 12 ◽  
Author(s):  
JiaQi Yue ◽  
WanYi Li ◽  
YuanZhong Wang
Keyword(s):  
Deep Learning ◽  
Medicinal Plants ◽  
Medicinal Plant ◽  
Sample Size ◽  
Discrimination Performance ◽  
Modern Technology ◽  
New Drugs ◽  
Support Vector ◽  
Paris Polyphylla ◽  
Identification Techniques

Medicinal plants have a variety of values and are an important source of new drugs and their lead compounds. They have played an important role in the treatment of cancer, AIDS, COVID-19 and other major and unconquered diseases. However, there are problems such as uneven quality and adulteration. Therefore, it is of great significance to find comprehensive, efficient and modern technology for its identification and evaluation to ensure quality and efficacy. In this study, deep learning, which is superior to conventional identification techniques, was extended to the identification of the part and region of the medicinal plant Paris polyphylla var. yunnanensis from the perspective of spectroscopy. Two pattern recognition models, partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM), were established, and the overall discrimination performance of the three types of models was compared. In addition, we also compared the effects of different sample sizes on the discriminant performance of the models for the first time to explore whether the three models had sample size dependence. The results showed that the deep learning model had absolute superiority in the identification of medicinal plant. It was almost unaffected by factors such as data type and sample size. The overall identification ability was significantly better than the PLS-DA and SVM models. This study verified the superiority of the deep learning from examples, and provided a practical reference for related research on other medicinal plants.

scholarly journals Factors influencing the use of Deep Learning for Medicinal Plants Recognition

2021 ◽  
Vol 2089 (1) ◽  
pp. 012055
Author(s):  
J V Anchitaalagammai ◽  
J S Shantha Lakshmi Revathy ◽  
S Kavitha ◽  
S Murali
Keyword(s):  
Deep Learning ◽  
Medicinal Plants ◽  
Medicinal Plant ◽  
Success Rate ◽  
Plant Species ◽  
High Accuracy ◽  
Medicinal Plant Species ◽  
Identification System ◽  
Human Beings ◽  
Physical And Mental Health

Abstract Medicinal plants are very essential in maintaining the physical and mental health of human beings. For providing better treatment, Identification and classification of medicinal plants is essential. In this research paper, main objective is to create a medicinal plant identification system using Deep Learning concept. This system identifies and classifies the medicinal plant species with high accuracy. In this system, five different Indian medicinal plant species namely Pungai, Jamun (Naval), Jatropha curcas, kuppaimeni and Basil are used for identification and classification. The dataset contains 58,280 images, includes approximately 10,000 images for each species. The leaf texture, shape, color, physiological or morphological as the features set for leaf identification. The CNN architecture is used to train the collected dataset and develop the system with high accuracy. As result of this model, 96.67% success rate in finding the corresponding medicinal plant. This model is advisable to use as early detection tool for finding the medicinal plant because of its best success rate

scholarly journals MYLPHerb-1: A Dataset of Malaysian Local Perennial Herbs for the Study of Plant Images Classification under Uncontrolled Environment

2022 ◽  
Vol 30 (1) ◽  
pp. 413-431
Author(s):  
Kalananthni Pushpanathan ◽  
Marsyita Hanafi ◽  
Syamsiah Masohor ◽  
Wan Fazilah Fazlil Ilahi
Keyword(s):  
Deep Learning ◽  
Medicinal Plants ◽  
Medicinal Plant ◽  
High Performance ◽  
Learning Algorithms ◽  
Automatic Classification ◽  
Medicinal Value ◽  
New Findings ◽  
Perennial Herbs ◽  
Imaging Conditions

Research in the medicinal plants’ recognition field has received great attention due to the need of producing a reliable and accurate system that can recognise medicinal plants under various imaging conditions. Nevertheless, the standard medicinal plant datasets publicly available for research are very limited. This paper proposes a dataset consisting of 34200 images of twelve different high medicinal value local perennial herbs in Malaysia. The images were captured under various imaging conditions, such as different scales, illuminations, and angles. It will enable larger interclass and intraclass variability, creating abundant opportunities for new findings in leaf classification. The complexity of the dataset is investigated through automatic classification using several high-performance deep learning algorithms. The experiment results showed that the dataset creates more opportunities for advanced classification research due to the complexity of the images. The dataset can be accessed through https://www.mylpherbs.com/.

ETHNOVETERINARY MEDICINAL USES OF SOME MEDICINAL PLANTS ON PNEUMONIA BY THE GUJJAR AND PAHARI TRIBES OF POONCH DISTRICT OF JAMMU AND KASHMIR

2017 ◽  
Vol 23 (2) ◽  
Author(s):  
JAMIL AHMED KHAN ◽  
RAJINDER PAUL
Keyword(s):  
Health Care ◽  
Medicinal Plants ◽  
Medicinal Plant ◽  
Natural Resources ◽  
Indigenous People ◽  
Health Care Facilities ◽  
Jammu And Kashmir ◽  
Medicinal Uses ◽  
Modern Health Care ◽  
Care Facilities

Poonch district of Jammu and Kashmir is a reservoir of enormous natural resources including the wealth of medicinal plants. The present paper deals with 12 medicinal plant species belonging to 8 genera of angiosperms used on pneumonia in cattle such as cows, sheep, goats and buffaloes in different areas of Poonch district. Due to poverty and nonavailability of modern health care facilities, the indigenous people of the area partially or fully depend on surrounding medicinal plants to cure the different ailments of their cattles. Further research on modern scientific line is necessary to improve their efficacy, safety and validation of the traditional knowledge.

NAMING OF BASOTHO MEDICINAL PLANTS: SEMANTIC CONNECTION TO THEIR REMEDIES

2015 ◽  
Vol 25 (1) ◽  
Author(s):  
R Possa ◽  
P Khotso
Keyword(s):  
Medicinal Plants ◽  
Medicinal Plant ◽  
Indigenous Knowledge ◽  
Future Generation ◽  
Speech Community ◽  
Traditional Medicines ◽  
Traditional Medicinal Plants ◽  
The Future ◽  
Economic Sphere ◽  
Medical Plants

The indigenous knowledge of the Basotho makes it simple for this speech community to name their traditional medicinal plants in such a way that they are meaningful; this could also be viewed as an empowerment technique, especially in the economic sphere. Their medicinal plants names seem to be idiomatic and to express certain philosophies of the Basotho society. Creativity is observable in this kind of naming, and many names allude to the kind of remedy that is associated with the medicinal plant. It is therefore the interest of this paper to consider the names of medical plants among the Basotho whose names allude to the remedy they provide. The names of Sesotho medicinal plants and the reasoning of the Basotho in general behind the name and the use of each medicinal plant will be discussed in this article. This paper will further preserve and promote the use of Basotho traditional medicines for the future generation.

Preterm Birth, Inflammation and Infection: New Alternative Strategies for their Prevention

2019 ◽  
Vol 20 (5) ◽  
pp. 354-365 ◽  
Author(s):  
Víctor M. Muñoz-Pérez ◽  
Mario I. Ortiz ◽  
Raquel Cariño-Cortés ◽  
Eduardo Fernández-Martínez ◽  
Leticia Rocha-Zavaleta ◽  
...  
Keyword(s):  
Preterm Birth ◽  
Medicinal Plants ◽  
Low Income ◽  
Experimental Studies ◽  
Neonatal Outcomes ◽  
New Drugs ◽  
Alternative Strategies ◽  
Mortality And Morbidity ◽  
Therapeutic Benefits ◽  
Gynecology And Obstetrics

Background:Worldwide, the progress in reducing neonatal mortality has been very slow. The rate of preterm birth has increased over the last 20 years in low-income and middle-income countries. Its association with increased mortality and morbidity is based on experimental studies and neonatal outcomes from countries with socioeconomic differences, which have considered implementing alternative healthcare strategies to prevent and reduce preterm births.Methods:Currently, there is no widely effective strategy to prevent preterm birth. Pharmacological therapies are directed at inhibiting myometrial contractions to prolong parturition. Some drugs, medicinal plants and microorganisms possess myorelaxant, anti-inflammatory and immunomodulatory properties that have proved useful in preventing preterm birth associated with inflammation and infection.Results:This review focuses on the existing literature regarding the use of different drugs, medicinal plants, and microorganisms that show promising benefits for the prevention of preterm birth associated with inflammation and infection. New alternative strategies involving the use of PDE-4 inhibitors, medicinal plants and probiotics could have a great impact on improving prenatal and neonatal outcomes and give babies the best start in life, ensuring lifelong health benefits.Conclusion:Despite promising results from well-documented cases, only a small number of these alternative strategies have been studied in clinical trials. The development of new drugs and the use of medicinal plants and probiotics for the treatment and/or prevention of preterm birth is an area of growing interest due to their potential therapeutic benefits in the field of gynecology and obstetrics.

Phytotherapy for wound healing: The most important herbal plants in wound healing based on Iranian etnobotanical documents

2020 ◽  
Vol 20 ◽  
Author(s):  
Kamal Solati ◽  
Mehrdad Karimi ◽  
Mahmoud Rafieian-Kopaei ◽  
Naser Abbasi ◽  
Saber Abbaszadeh ◽  
...  
Keyword(s):  
Wound Healing ◽  
Medicinal Plants ◽  
Aloe Vera ◽  
Datura Stramonium ◽  
New Drugs ◽  
Mentha Pulegium ◽  
Accelerate Wound Healing ◽  
Healing Tissue ◽  
Herbal Plants ◽  
Echium Amoenum

: Wound healing is a process which starts with inflammatory response after damage occurrence. This process happens by restoring the wound surface coating tissue, migrating fibroblasts to form the needed collagen, forming a healing tissue and finally contortion and extraction of the wound. Today, various drugs are used to heal the wound. However, the used drugs to repair wounds have some defects and side effects. In spite of all attempts to accelerate wound healing definitely, no safe drug has been introduced for this purpose. Therefore, the necessity of identifying herbal plants in ethnopharmacology and ethnobotany documents with healing effect is felt essential. In this article we tried to review and present Iranian effective medicinal plants and herbal compounds used for wound healing. Searching was performed on databases including ISI Web of Science, PubMed, PubMed Central, Scopus, ISC, SID, Magiran and some other databases. The keywords used included wound healing, skin treatment, medicinal plants, ethnobotany, and phytotherapy. In this regard, 139 effective medicinal plants on wound healing were identified based on ethnopharmacology and ethnobotanical sources of Iran. Medicinal plants such as Salvia officinalis, Echium amoenum, Verbascum spp., G1ycyrrhiza glabra, Medicago sativa, Mentha pulegium, Datura stramonium L., Alhagi spp., Aloe vera, Hypericum perforatum, Pistacia atlantica and Prosopis cineraria were the most important and effective medicinal plants on wound healing in Iran. These native Iranian medicinal plants are full of antioxidants and biological compounds and might be used for wound healing and preparation of new drugs.

Virtual Screening Meets Deep Learning

2018 ◽  
Vol 15 (1) ◽  
pp. 6-28 ◽  
Author(s):  
Javier Pérez-Sianes ◽  
Horacio Pérez-Sánchez ◽  
Fernando Díaz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Virtual Screening ◽  
Great Increase ◽  
New Drugs ◽  
Learning Approach ◽  
Screening Strategies ◽  
Computer Aided ◽  
Recent Developments

Background: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence. Objective: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.

scholarly journals Identifying the Branch of Kiwifruit Based on Unmanned Aerial Vehicle (UAV) Images Using Deep Learning Method

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4442
Author(s):  
Zijie Niu ◽  
Juntao Deng ◽  
Xu Zhang ◽  
Jun Zhang ◽  
Shijia Pan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Unmanned Aerial Vehicle ◽  
Semantic Segmentation ◽  
Dynamic Monitoring ◽  
Support Vector ◽  
Distribution Maps ◽  
Time Operation ◽  
Aerial Vehicle ◽  
Uav Images ◽  
Segmentation Image

It is important to obtain accurate information about kiwifruit vines to monitoring their physiological states and undertake precise orchard operations. However, because vines are small and cling to trellises, and have branches laying on the ground, numerous challenges exist in the acquisition of accurate data for kiwifruit vines. In this paper, a kiwifruit canopy distribution prediction model is proposed on the basis of low-altitude unmanned aerial vehicle (UAV) images and deep learning techniques. First, the location of the kiwifruit plants and vine distribution are extracted from high-precision images collected by UAV. The canopy gradient distribution maps with different noise reduction and distribution effects are generated by modifying the threshold and sampling size using the resampling normalization method. The results showed that the accuracies of the vine segmentation using PSPnet, support vector machine, and random forest classification were 71.2%, 85.8%, and 75.26%, respectively. However, the segmentation image obtained using depth semantic segmentation had a higher signal-to-noise ratio and was closer to the real situation. The average intersection over union of the deep semantic segmentation was more than or equal to 80% in distribution maps, whereas, in traditional machine learning, the average intersection was between 20% and 60%. This indicates the proposed model can quickly extract the vine distribution and plant position, and is thus able to perform dynamic monitoring of orchards to provide real-time operation guidance.

scholarly journals Ethnomedicinal Plants Traditionally Used for the Treatment of Jaundice (Icterus) in Himachal Pradesh in Western Himalaya—A Review

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 232
Author(s):  
Disha Raghuvanshi ◽  
Rajni Dhalaria ◽  
Anjali Sharma ◽  
Dinesh Kumar ◽  
Harsh Kumar ◽  
...  
Keyword(s):  
Medicinal Plants ◽  
Plant Species ◽  
Ricinus Communis ◽  
Western Himalaya ◽  
Saccharum Officinarum ◽  
Himachal Pradesh ◽  
New Drugs ◽  
Tinospora Cordifolia ◽  
Ethnomedicinal Plants ◽  
Pharmacological Significance

Ethnomedicinal plants have a significant role in the lives of people of rural and tribal areas. Thousands of medicinal plant species are used to treat various diseases, including jaundice, and are considered an important therapeutic resource to minimize these diseases. Jaundice (icterus) is a chronic disease that occurs when the amount of bilirubin in the blood increases. This review describes different ethnomedicinal plants used for curing jaundice by tribal and rural people of Himachal Pradesh. The study reveals 87 ethnomedicinal plant species belonging to 51 different families, which are used for treating jaundice in Himachal Pradesh. These plants are arranged in a systematic way, which includes a description of their common name, botanical name, along with its family, plant parts used, region, and mode of use in tabulated form. Some of the plant extracts have already been explored for their phytochemical and pharmacological significance and proved their potential in the preparation of new medicines or drugs against the treatment of jaundice. This review is an attempt to highlight the indigenous knowledge of medicinal plants, which are specifically used for the treatment of jaundice. The data mentioned in the present review is compiled from various sources like existing literature, books, Google Scholar, and Scopus publications. Among all the observed plant species, most used medicinal plants for the treatment of jaundice include Justicia adhatoda, Emblica officinalis, Ricinus communis, Saccharum officinarum, Terminalia chebula, Berberis aristata, Cuscuta reflexa, and Tinospora cordifolia. Plants that are mostly utilized for the treatment of jaundice need to be scientifically validated by pharmacological analysis and should be subsequently used for the preparation of new drugs, which may prove far more beneficial than the existing one.

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