Results 71 to 80 of about 658 (166)

Advancements in smart agriculture: A systematic literature review on state‐of‐the‐art plant disease detection with computer vision

IET Computer Vision, Volume 19, Issue 1, January/December 2025.
Plant diseases are known to cause negative impacts and financial losses which are usually found on plant leaves and detection using traditional methods is a labor‐intensive process. Smart agriculture applications based on computer vision are being developed to detect and control of plant diseases.
Esra Yilmaz, Sevim Ceylan Bocekci, Cengiz Safak, Kazim Yildiz   +3 more
wiley   +1 more source

Rice Tungro Disease (RTD) Incidence in Assam, India

, 1992
This article 'Rice Tungro Disease (RTD) Incidence in Assam, India' appeared in the International Rice Research Newsletter series, created by the International Rice Research Institute (IRRI). The primary objective of this publication was to expedite communication among scientists concerned with the development of improved technology for rice and for ...
Saikia, A. K., Bhagabati, K. N., Rathaiah, Y., Choudhury, H. D.   +3 more
openaire   +2 more sources

Stochastic delay biocybernetic modeling and control of tungro virus transmission in rice systems

Alexandria Engineering Journal
Rice is among the main staple foods to the world population and management of its common diseases is a key way of enhancing crop production and food security.
Ali Raza, Marek Lampart, Nimra Khalid, Eugenio M. Rocha, Faridah Alruwaili, Emad Fadhal   +5 more
doaj   +1 more source

Timing Rice Planting to Control Tungro (RTV) Disease

, 1989
This article 'Timing Rice Planting to Control Tungro (RTV) Disease' appeared in the International Rice Research Newsletter series, created by the International Rice Research Institute (IRRI). The primary objective of this publication was to expedite communication among scientists concerned with the development of improved technology for rice and for ...
Sama, S., Hasanuddin, A., Cabunagan, R. C., Hibino, H.   +3 more
openaire   +2 more sources

CORH 3 - A Short Duration Non aromatic rice hybrid [PDF]

Electronic Journal of Plant Breeding, 2009
The new early maturing rice hybrid CORH 3 is a combination of TNAU CMS 2A and CB 87R. This hybrid matures in 115days. The hybrid was found to produce on an average 7.2 tonnes per hectare which was more than 12% higher than thehybrid checks, ADTRH 1 and ...
Suresh S, Rabindran R, Rajeswari S, Mohana Sundaram K, Robin S, Manonmani S, Thiyagarajan K, Subbalakshmi L, Raveendran T S   +8 more
doaj  

Comparing CNN Models for Rice Disease Detection: ResNet50, VGG16, and MobileNetV3-Small

Journal of Information Systems and Informatics
The Oryza sativa (rice) plant is an important staple food source, especially in the Asian region. Rice production is often disrupted by diseases such as Brown Spot, Leaf Scald, Rice Blast, Rice Tungro, and Sheath Blight, which can reduce yield and crop ...
Muhammad Taufik Roseno, Serly Oktarina, Yuwinti Nearti, Hadi Syaputra, Nirmala Jayanti   +4 more
doaj   +1 more source

First report of a putative new badnavirus in association with wisteria mosaic disease in Italy

New Disease Reports, Volume 51, Issue 1, January/March 2025.
M. Morelli, G. D'Attoma, P. Saldarelli, A. Minafra   +3 more
wiley   +1 more source

Lightweight Federated Transfer Learning for Plant Leaf Disease Detection and Classification across Multiclient Cross-Silo Datasets [PDF]

BIO Web of Conferences
Plant leaves and crops play a crucial role as a primary food source globally, making significant contributions to dietary iron intake (9%) and energy consumption (23%) per capita in the Asian region.
Choubey Shilpi, Divya
doaj   +1 more source

Rice virus disease in Indonesia: epidemiology and varietal resistance

Phytopathology Research
The geographical location of Indonesia in the tropical region, characterized by high temperatures and humidity, is favorable for the development of viral diseases in rice.
I Nyoman Widiarta, Firmansyah Firmansyah, Muhamad Yunus, Aniversari Apriana, Atmitri Sisharmini, Tri Joko Santoso, Rerenstradika Tizar Terryana, Rahmini Rahmini, Indrastuti Apri Rumanti, Trias Sitaresmi, Swisci Margaret, Chaerani Chaerani, Ani Widarti, Yudhistira Nugraha, Aris Hairmansis   +14 more
doaj   +1 more source

Exploring Deep Learning and Explainable AI for Precise Rice Leaf Disease Detection and Classification

IEEE Access
This study presents an innovative approach to detect and classify four types of rice leaf diseases, including bacterial leaf blight, brown spot, tungro, and blast, as well as healthy leaves, using deep learning techniques.
Tanjim Mahmud, Mst. Sharmin Akter, Tahmina Akter, Mohammad Shahadat Hossain, Karl Andersson   +4 more
doaj   +1 more source