Results 91 to 100 of about 701 (168)

Available cloned genes and markers for genetic improvement of biotic stress resistance in rice. [PDF]

Front Plant Sci, 2023
Simon EV, Hechanova SL, Hernandez JE, Li CP, Tülek A, Ahn EK, Jairin J, Choi IR, Sundaram RM, Jena KK, Kim SR.   +10 more
europepmc   +1 more source

Characterization of a novel psyllid-transmitted waikavirus in carrots. [PDF]

Virus Res, 2023
Shushan A, Luria N, Lachman O, Sela N, Laskar O, Belausov E, Smith E, Dombrovsky A.   +7 more
europepmc   +1 more source

Introgression of tsv1 improves tungro disease resistance of a rice variety BRRI dhan71. [PDF]

Sci Rep, 2022
Hore TK, Inabangan-Asilo MA, Wulandari R, Latif MA, Nihad SAI, Hernandez JE, Gregorio GB, Dalisay TU, Diaz MGQ, Ch B, Swamy BPM.   +10 more
europepmc   +1 more source

Survivomics: natural product clues from virus-unaffected crops for next-generation plant immunity. [PDF]

Front Plant Sci
Pant P.
europepmc   +1 more source

A comprehensive dataset of rice leaf images for disease detection using machine learning. [PDF]

Data Brief
Hasan A, Layes TA, Afridi AS, Rifat SH, Nur FN, Moon NN.   +5 more
europepmc   +1 more source

Transgenic rice plants that overexpress transcription factors RF2a and RF2b are tolerant to rice tungro virus replication and disease. [PDF]

Proc Natl Acad Sci U S A, 2008
Dai S, Wei X, Alfonso AA, Pei L, Duque UG, Zhang Z, Babb GM, Beachy RN.   +7 more
europepmc   +1 more source

A hybrid vision transformer and ResNet18 based model for biotic rice leaf disease detection. [PDF]

Front Plant Sci
Sennan S, Somula R, Cho Y, Sennan S.
europepmc   +1 more source

Phylogenomics, population structure, and symbiont diversity refine the systematics of Southeast Asian rice leafhoppers (Hemiptera: Cicadellidae). [PDF]

J Insect Sci
Detcharoen M, Saksongmuang V, Nilsai A.
europepmc   +1 more source

Artificial Intelligence-Assisted CRISPR/Cas Systems for Targeting Plant Viruses. [PDF]

Genes (Basel)
Iksat N, Madirov A, Zhanassova K, Masalimov Z.   +3 more
europepmc   +1 more source

Hybrid deep learning for smart paddy disease diagnosis using self supervised hierarchical reconstruction and attention based temporal analysis. [PDF]

Sci Rep
Thanuboddi N, Nelakuditi UR.
europepmc   +1 more source