Results 91 to 100 of about 1,110 (183)

Web‐Based Sustainable Detection and Treatment Recommendation System for Wheat Plant Diseases Using Convolutional Neural Networks

Food Science &Nutrition, Volume 14, Issue 1, January 2026.
A comprehensive dataset of wheat crop images, including healthy plants and samples affected by YR and BR diseases, was developed from public sources. A Convolutional Neural Network (CNN) model was trained and optimized for accurate detection and classification of wheat diseases.
Nergis Gulzar Abbasi, Aiman Khan Nazir, Sadia Ali, Hamza Iqbal, Atif Ali, Asghar Ali Shah, Sagheer Abbas, Muhammad Adnan Khan   +7 more
wiley   +1 more source

Effect of N on False Smut (FS) in Upland Rice

, 1989
This article 'Effect of N on False Smut (FS) in Upland Rice' 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 ...
Bhardwaj, C. L., Thakar, K. S., Thakar, D. R., Bassi, K.   +3 more
openaire   +2 more sources

Field evaluation of fungicides against false smut disease of rice

Journal of Pharmacognosy and Phytochemistry, 2020
False smut disease of rice caused by Ustilaginoidea virens is an emerging biotic stress of rice. A field experiment to evaluate bioefficacy of solo and combination fungicides against false smut disease of rice was conducted in two consecutive Kharif seasons (2017 and 2018).
H Sharanabasav, D Pramesh, E Chidanandappa, A Saddamhusen, Amoghvarsha Chittaragi, A Raghunandana, MK Prasanna Kumar, BT Raghavendra, R Harischandra Naik, SB Mallesh, K Mahantashivayogayya, Sujay Huruli, BGM Reddy, SB Gowdar   +13 more
openaire   +1 more source

Multi‐Decadal Analysis on the Impact of Climate Change, Genetic Gain, Cultivar Type, and Harvest Timing on Main and Ratoon Rice Yield and Quality

Global Change Biology, Volume 32, Issue 1, January 2026.
An analysis of 33 years of data estimated the impact of climate change, genetic gain, cultivar type, and harvest timing on rice yield and quality. Degree‐days (˚D) and atmospheric [CO2] have increased 11.6% and 18.4%, respectively. Several climatic variables have impacted grain yield, some positively and some negatively, and many have reduced grain ...
Lloyd T. Wilson, S. Omar P. B. Samonte, Y. Yang   +2 more
wiley   +1 more source

Adaptive Attention‐Enhanced Multiscale Vision Transformers for Real‐Time Leaf Disease Detection in Smart Agriculture

International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
Plant diseases represent a major challenge to global agricultural productivity and require precise and rapid diagnostic tools for effective intervention. This study presents an adaptive attention‐enhanced multiscale vision transformer (MS‐ViT) framework for plant disease classification.
Xuan Yang, Xuewei Wang, Dejuan Li, Zhiqing Bai, Yujie Li, M. Khosravi, Richard Murray   +6 more
wiley   +1 more source

Biological invasions: a global assessment of geographic distributions, long‐term trends, and data gaps

Biological Reviews, Volume 100, Issue 6, Page 2542-2583, December 2025.
ABSTRACT Biological invasions are one of the major drivers of biodiversity decline and have been shown to have far‐reaching consequences for society and the economy. Preventing the introduction and spread of alien species represents the most effective solution to reducing their impacts on nature and human well‐being.
Hanno Seebens, Laura A. Meyerson, David M. Richardson, Bernd Lenzner, Elena Tricarico, Franck Courchamp, Alla Aleksanyan, Emre Keskin, Hanieh Saeedi, Perpetra Akite, Jake M. Alexander, Sarah A. Bailey, Dino Biancolini, Tim M. Blackburn, Hans Juergen Boehmer, Alejandro Bortolus, Marc W. Cadotte, César Capinha, James T. Carlton, Jo Anne Crouch, Curtis C. Daehler, Franz Essl, Llewellyn C. Foxcroft, Jason D. Fridley, Nicol Fuentes, Mirijam Gaertner, Bella Galil, Emili García‐Berthou, Pablo García‐Díaz, Sylvia Haider, Liam Heneghan, Kevin A. Hughes, Cang Hui, Ekin Kaplan, Andrew M. Liebhold, Chunlong Liu, Elizabete Marchante, Hélia Marchante, Alicia Marticorena, David W. Minter, Rodrigo A. Moreno, Wolfgang Nentwig, Aidin Niamir, Ana Novoa, Ana L. Nunes, Aníbal Pauchard, Sebataolo Rahlao, Anthony Ricciardi, James C. Russell, K.V. Sankaran, Anna Schertler, Evangelina Schwindt, Ross T. Shackleton, Daniel Simberloff, David L. Strayer, Alifereti Tawake, Marco Thines, Cristóbal Villaseñor‐Parada, Jean Ricardo Simões Vitule, Viktoria Wagner, Victoria Werenkraut, Karsten Wesche, Demian A. Willette, Rafael D. Zenni, Petr Pyšek   +64 more
wiley   +1 more source

Development of Colloidal Gold‐Based Lateral Flow  Immunoassay for Rapid Qualitative and SemiQuantitative Analysis of Ustiloxins A and B in Rice  Samples

Toxins, 2017
Rice false smut is a worldwide devastating rice disease infected by the fungal pathogen Villosiclava virens. Ustiloxin A (UA) and ustiloxin B (UB), cyclopeptide mycotoxins, were the major ustiloxins isolated from the rice false smut balls (FSBs) that ...
Xiaoxiang Fu, Rushan Xie, Jian Wang, Xiaojiao Chen, Xiaohan Wang, Weibo Sun, Jiajia Meng, Daowan Lai, Ligang Zhou, Baomin Wang   +9 more
doaj   +1 more source

Breeding for quantitative disease resistance: Case studies, emerging approaches, and exploiting pathogen variation

Crop Science, Volume 65, Issue 6, November/December 2025.
Abstract Host resistance, using qualitative genes with major effects, such as resistance (R) genes, is one of the most effective disease control strategies. However, because major gene‐derived resistance wanes over time, breeders must increasingly focus on quantitative trait loci and minor effect genes, which, when pyramided together, can confer ...
R. McGee, M. Zaleski‐Cox, M. A. Jayawardana, B. L. Tillman, O. Wally, L. Esquivel‐Garcia, W. G. D. Fernando, H. Raman, H. S. Bariana, T. Copley, A. H. Carter, V. Hoyos‐Villegas   +11 more
wiley   +1 more source

SURVEY OF FALSE SMUT (USTILAGINOIDEA VIRENS) OF RICE (ORYZA SATIVA L.) IN SELECTED DISTRICTS OF UTTAR PRADESH, INDIA [PDF]

, 2014
A survey was carried out in selected districts of Uttar Pradesh (India) to evaluate the incidence of false smut of rice. Among all districts surveyed, the highest incidence (80%) was recorded in Gaur block of Basti district.
SHIVAM SINGH, ABHILASHA A. LAL, SOBITA SIMON   +2 more
core   +1 more source

Screening and Agronomic Trait Association of Rice Germplasm for False Smut Resistance

International Journal of Bio-Resource and Stress Management
The experiment was conducted during kharif, 2021 and 2022 (June–October) at the College Farm, College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad, Telangana, India to study on screening of rice
Somshetty Ravali, S. Ameer Basha, Y. Chandra Mohan, T. Kiran Babu, S. N. C. V. L. Pushpavalli, S. N. C. V. L. Pushpavalli, B. Balaji Naik   +6 more
doaj   +1 more source