Results 61 to 70 of about 10,357,758 (230)
Efficacy of fungicides for control of rice tungro disease
, 2003 This article 'Efficacy of fungicides for control of rice tungro disease' appeared in the International Rice Research Notes series, created by the International Rice Research Institute (IRRI) to expedite communication among scientists concerned with the development of improved technology for rice and rice-based systems. The series is a mechanism to help
Bhaktavatsalam, G. +2 more
openaire +1 more source
Characterization of Oryza rufipogon–Derived Resistance to Tungro Disease in Rice [PDF]
Plant Disease, 2007 Rice tungro disease (RTD) is caused by the interaction between Rice tungro spherical virus (RTSV) and Rice tungro bacilliform virus (RTBV), both of which are transmitted by green leafhoppers (GLH). In order to define the resistance against RTD in rice cv. Matatag 9 which was developed by interspecific hybridization between RTD-susceptible cv. IR64 and
Yuji, Shibata +3 more
openaire +2 more sources
PLDC‐Net: A Domain‐Specific Base Model for Plant Leaf Disease Classification Domain Adaptation Tasks
Plant Direct, Volume 10, Issue 4, April 2026.ABSTRACT Plant diseases are the cause of heavy losses of crop production and, therefore, a big contributor to food shortages. Identifying these diseases as early as possible is important to limit the negative effects that these diseases have on the yields, as slow response time will lead to the spread of diseases and further loss.
David J. Richter, Kyungbaek Kim
wiley +1 more source
Epidemiological Study on the Current Status of Rice Tungro Disease in South Sulawesi, Indonesia
, 2020 Integrated management of Rice Tungro Disease (RTD) by combining the appropriate planting time and cultivar rotation has successfully controlled the disease in South Sulawesi, Indonesia.
N. Rosida +3 more
semanticscholar +1 more source
Management of the Rice Tungro Virus Vector \u3ci\u3eNephotettix virescens\u3c/i\u3e (Homoptera: Cicadellidae) with Controlled-Release Formulations of Carbofuran [PDF]
, 1984 Field trials were conducted in lowland flooded rice in the Philippines to evaluate a number of carbofuran controlled-release formulations in comparison with commercial formulations. The test formulations were based on a biodegradable matrix of pine kraft
Aquino, G. B. +4 more
core +1 more source
Effect of Azolla on Rice Tungro Virus Disease
, 1983 This article 'Effect of Azolla on Rice Tungro Virus 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 rice ...
Mariappan, V. +3 more
openaire +1 more source
Food Science &Nutrition, Volume 13, Issue 12, December 2025.This study proposes a NN‐based framework for automated recognition and classification of rice diseases using leaf imagery. Feature extraction techniques such as texture analysis, GLCM, GLDM, FFT, and DWT extract critical image characteristics, while dimensionality reduction (PCA, KPCA, Sparse AE, Stacked AE) and feature selection (ANOVA F‐measure, Chi ...
Farida Siddiqi Prity +5 more
wiley +1 more source
The failure farmers in panti district to control tungro disease which endemic in 2014-2019
Journal of Physics: Conference Series, 2020 Tungro disease in rice plants is transmitted by green leafhoppers (Nephotettix virescens) in a semi-persistent manner. This disease has spread in Panti District from 2014-2019, especially at the beginning and the end of rainy season. This paper wanted to
W. Wahyuni, J. B. A. Sayekti
semanticscholar +1 more source
Gulma Inang Virus Tungro Dan Kemampuan Penularannya Ke Tanaman Padi [PDF]
, 2013 Tungro disease in rice (Oryza sativa Linn) is caused by rice tungro virus (RTV), which consists of two forms of particles, namely Rice Tungro Bacilliform Virus and Rice Tungro Spherical Virus.
Ladja, F. (Fausiah)
core
Hybrid AI Model With CNNs and Vision Transformers for Precision Pest Classification in Crops
Food Science &Nutrition, Volume 13, Issue 11, November 2025.This study proposes a hybrid deep learning model integrating CNNs, attention mechanisms, and Vision Transformers for accurate classification of five major rice crop pests. The model captures both fine‐grained local features and global spatial relationships, achieving a high accuracy of 95% on an augmented dataset.
Neha Sharma +4 more
wiley +1 more source