Klasifikasi Penyakit Padi berdasarkan Citra Daun Menggunakan Model Terlatih Resnet101

Rice is a staple food source for most countries in the world, including Indonesia. The problem of rice disease is a problem that is quite crucial and is experienced by many farmers. Approximately 200,000 - 300,000 tons per year the amount of rice attacked by pests in Indonesia. Considerable losses are caused by late-diagnosed rice plant diseases that reach a severe stage and cause crop failure. The limited number of Agricultural Extension Officers (PPL) and the Lack of information about disease and proper treatment are some of the causes of delays in handling rice diseases. Therefore, with the development of information technology and computers, it is possible to identify diseases by utilizing Artificial Intelligence, one of which is by using recognition methods based on image processing and pattern recognition technology. The purpose of this research is to create a Machine Learning model by applying the model architecture from Resnet101 combined with the model architecture from the author. The model proposed in this study produces an accuracy of 98.68%.

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Paddy Leaf Disease Detection and Recognition using Image Processing

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2021.36810 ◽

2021 ◽

Vol 9 (VII) ◽

pp. 2262-2267

Author(s):

Arfa Fathima

Keyword(s):

Image Processing ◽

Rice Plant ◽

Bacterial Blight ◽

Processing System ◽

Plant Diseases ◽

Future Research ◽

Crop Failure ◽

Background Removal ◽

Bacterial Blight Disease ◽

Blight Disease

Rice crops have been recognized as one of the most powerful energy sources for resource production over the last few decades. Rice plant diseases are regarded as a major cause of crop failure, economic and communal loss in the agricultural field's future development. Since the last ten years, researchers have been keenly interested in the diagnosis of plant disease approaches to image processing techniques. The primary goal of this research is to create an image processing system capable of identifying and classifying bacterial blight disease. A set of infected rice plant images from a rice field are captured using a digital camera and empirically evaluated using background removal and segmentation techniques. Image segmentation, feature extraction, feature selection, and classification are used to compare them. This paper also makes recommendations for future research on the diagnosis of bacterial blight disease.

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Awareness on Sustainability Perspective among Consumers’ of Tea

Restaurant Business ◽

10.26643/rb.v118i7.7670 ◽

2019 ◽

Vol 118 (7) ◽

pp. 111-116

Author(s):

Dr. M. Ayisha Millath ◽

Dr. K. Malik Ali

Keyword(s):

Sample Size ◽

Positive Relationship ◽

Health Benefits ◽

High Price ◽

Educational Qualification ◽

Lack Of Information ◽

The World ◽

Correlation Result ◽

Day By Day

Tea is an imperative beverage elsewhere in the world. The need and demand for tea are increasing day by day. Tea Association of USA expects continued growth in tea sales due to awareness on its health benefits. There are more than 3000 kinds of tea varieties are there but only four varieties are widely used. The authors investigated the opinion on sustainability perspectives and problems faced by them while they intend to buy. Willing Participants are included in survey with the sample size of 237. The correlation result revealed that there is a positive relationship between educational qualification and sustainability perspectives of tea products among consumers. . It is also found that lack of information and high price were the major problems faced by tea consumers while intend to buy sustainable tea. So the tea manufacturers and processors must throw light on these issues to improve its preference among consumers.

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Pivoting the Plant Immune System from Dissection to Deployment

Science ◽

10.1126/science.1236011 ◽

2013 ◽

Vol 341 (6147) ◽

pp. 746-751 ◽

Cited By ~ 571

Author(s):

Jeffery L. Dangl ◽

Diana M. Horvath ◽

Brian J. Staskawicz

Keyword(s):

Immune System ◽

Conceptual Understanding ◽

Germ Plasm ◽

Plant Diseases ◽

Sequencing Technology ◽

Plant Immune System ◽

Rich Diversity ◽

The World ◽

The Rich ◽

Molecular Components

Diverse and rapidly evolving pathogens cause plant diseases and epidemics that threaten crop yield and food security around the world. Research over the last 25 years has led to an increasingly clear conceptual understanding of the molecular components of the plant immune system. Combined with ever-cheaper DNA-sequencing technology and the rich diversity of germ plasm manipulated for over a century by plant breeders, we now have the means to begin development of durable (long-lasting) disease resistance beyond the limits imposed by conventional breeding and in a manner that will replace costly and unsustainable chemical controls.

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Dieback of apricot plantations caused by 'Ca. Phytoplasma prunorum' in Borsod-Abaúj-Zemplén county (Northern-Hungary)

Acta Agraria Debreceniensis ◽

10.34101/actaagrar/39/2735 ◽

2010 ◽

pp. 34-41

Author(s):

Gábor Tarcali ◽

Emese Kiss ◽

György J. Kövics ◽

Sándor Süle ◽

László Irinyi ◽

...

Keyword(s):

Sour Cherry ◽

Fruit Trees ◽

Fruit Production ◽

Plant Diseases ◽

Stone Fruit ◽

Stone Fruits ◽

The North ◽

Long Run ◽

The World ◽

Fruit Plantations

Plant diseases caused by phytoplasmas have increasing importance in all over the world for fruit growers. Lately, phytoplasma diseases occur on many fruit varieties and responsible for serious losses both in quality and quantity of fruit production. In the long-run these diseases cause destruction of fruit trees. The apricot phytoplasma disease (Ca. Phytoplasma prunorum) was first reported in Europe in 1924 from France. In 1992 the disease has also been identified in Hungary. On the base of growers' signals serious damages of "Candidatus Phytoplasma prunorum" Seemüller and Schneider, 2004 (formerly: European stone fruit yellows phytoplasma) could be observed in different stone fruit plantations in the famous apricot-growing area nearby Gönc town, Northern-Hungary. Field examinations have been begun in 2009 in several stone fruit plantations in Borsod-Abaúj-Zemplén County mainly in Gönc region which is one of the most important apricot growing regions in Hungary, named “Gönc Apricot Growing Area”. Our goals were to diagnose the occurrence of Ca. Phytoplasma prunorum on stone fruits (especially on apricot) in the North-Hungarian growing areas by visual diagnostics and confirm data by laboratory PCR-based examinations. All the 28 collected samples were tested in laboratory trials and at 13 samples from apricot, peach, sour cherry and wild plum were confirmed the presence of phytoplasma (ESFY). On the base of observations it seems evident that the notable losses caused by "Ca. Phytoplasma prunorum" is a new plant health problem to manage for fruit growers, especially apricot producers in Hungary.

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Communication Sentiment Analyzer using Machine Learning with Naive Bayes Bernoullinb

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.a1610.109119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 5976-5979

Keyword(s):

Machine Learning ◽

Social Media ◽

Major Part ◽

Naive Bayes ◽

Naïve Bayes ◽

User Preferences ◽

Social Media Data ◽

Machine Learning Model ◽

The World ◽

Media Data

In this never-ending social media era it is estimated that over 5 billion people use smartphones. Out of these, there are over 1.5 billion active users in the world. In which we all are a major part and before opening our messages we all are curious about what message we have received. No doubt, we all always hope for a good message to be received. So Sentiment analysis on social media data has been seen by many as an effective tool to monitor user preferences and inclination. Finally, we propose a scalable machine learning model to analyze the polarity of a communicative text using Naive Bayes’ Bernoulli classifier. This paper works on only two polarities that is whether the sentence is positive or negative. Bernoulli classifier is used in this paper because it is best suited for binary inputs which in turn enhances the accuracy of up to 97%.

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Localising Humanitarianism, Peace Making, and Diplomacy: The Challenges Facing Muslim INGOs

Journal of Peacebuilding & Development ◽

10.1177/1542316620925802 ◽

2020 ◽

Vol 15 (2) ◽

pp. 178-191

Author(s):

Amjad Mohamed-Saleem

Keyword(s):

Paradigm Shift ◽

Modus Operandi ◽

Lack Of Information ◽

The World ◽

International Donor

Since the World Humanitarian Summit in 2016, the concept of localisation has dominated the narrative of international donor engagement. Traditionally, this is something that Muslim charities have supposedly been doing. Yet Muslim charities are conspicuous by their absence in the global debate despite the fact that over the last 20 years, there has been an explosion in the number of International Islamic Development organisations or charities. The localisation debate highlights a weakness for the Muslim charities in terms of operations on the ground. Muslim International Non Governmental Organisations (INGOs) appear to be struggling to articulate a modus operandi for operation. As a consequence, Muslim charities respond in a schizophrenic manner brought about by a lack of information on how Muslim organisations work in the field of charity and also an internal understanding of how Muslim charities should operate. This article discusses the need for a paradigm shift for Muslim INGOs within the localisation debate in terms of how they operate, identify, and work with local partners.

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