Phytoplasmas are an economically important group of plant pathogens that negatively impact a wide variety of plants in agricultural and natural ecosystems. In Florida, palm trees are essential elements in the nursery and landscaping industries that suffer from diseases caused by phytoplasmas that are related to each other but are classified in two different subgroups, 16SrIV-A and 16SrIV-D. In this study, a TaqMan assay was developed for digital polymerase chain reaction (dPCR) to detect both palm-infecting phytoplasmas found in Florida. When compared with real-time PCR assays and nested PCR assays, dPCR was capable of detecting the phytoplasmas at much lower concentrations than was possible by using real-time PCR and nested PCR. Additionally, the assay was capable of detecting 16SrIV-B phytoplasma as well as isolates representing the 16SrI and 16SrIII phytoplasma groups. Due to sequence identity of primer annealing regions across diverse phytoplasmas, the assay is likely to be successful for detection of a wide variety of phytoplasmas. The increased sensitivity of this dPCR assay over real-time PCR will allow for earlier detection of phytoplasma infection in palm trees, as well as for screening of salivary glands of candidate insect vector species. These advantages should aid timely management decisions to reduce disease spread and rapid determination of phytoplasma transmission by vectors.

Lethal Bronzing Disease (LB) is a disease of palms caused by the 16SrIV-D phytoplasma. A low-cost electronic nose (eNose) prototype was trialed for its detection. It includes an array of eight Taguchi-type (MQ) sensors (MQ135, MQ2, MQ3, MQ4, MQ5, MQ9, MQ7, and MQ8) controlled by an Arduino NANO^® microcontroller, using heater voltages that vary sinusoidally over a 2.5 min cycle. Samples of uninfected, early symptomatic, moderate symptomatic, and late symptomatic infected palm leaves of the cabbage palm were processed and analyzed. MQ sensor responses were subjected to a 256 element discrete Fourier transform (DFT), and harmonic component amplitudes were reviewed by principal component analysis (PCA). The experiment was repeated three times, each showing clear evidence of differences in sensor responses between the samples of uninfected leaves and those in the early stages of infection. Within each experiment, four groups of responses were identified, demonstrating the ability of the unit to repeatedly distinguish healthy leaves from diseased ones; however, detection of the severity of infection has not been demonstrated. By selecting appropriate coefficients (here demonstrated with plots of MQ5 Cos1 vs. MQ8 Sin3), it should be possible to build a ruleset classifier to identify healthy and unhealthy samples.

An ongoing survey for novel phytoplasmas and viruses that affect palms (Arecaceae) is being conducted in Costa Rica along with potential vectors. During that survey, a new species of derbid planthopper (Hemiptera: Fulgoroidea) in the genus Omolicna Fennah was detected from Heredia and Limón State and is here described as Omolicna xavieri sp. n. This new taxon was first found on declining coconut palms (Cocos nucifera) and subsequently on healthy coconut palms in Tortuguero National Park. Also, two additional species of Omolicna, O. brunnea and O. triata, were collected on coconut in the same habitat and represent new country records. There are no previously published records of Omolicna from Costa Rica. Sequence data for the cytochrome c oxidase subunit I (COI) and the 18S ribosomal RNA gene were obtained. In addition, novel 18S primers specific to auchenorrhynchan insects were developed and presented. The molecular data show high pairwise distances between O. xavieri sp. n. and other Omolicna species (24% to 31% and 10% using COI and 18S, respectively). Based on both morphological and sequence data, we erect and briefly describe the new subgenus Agoo for the new species to reflect the observed differences. A checklist of Omolicna species is presented.

Phytoplasmas are associated with many plant diseases. In palms, lethal bronzing disease, Texas Phoenix palm decline, and coconut lethal yellowing decline are some of them. In Sri Lanka, coconut leaf wilt decline has been reported in the Weligama area of the Southern province, and the disease is called Weligama coconut leaf wilt disease (WCLWD). Unlike other phytoplasma diseases of palms, WCLWD shows slow disease progress. Pathogen detection entirely relies on nested polymerase chain reaction (PCR). However, inconsistencies in pathogen detection have been experienced, i.e., symptomatic plants often produce negative results. The objectives of this study were to reconsider the choice of primers and to determine the best sampling tissue types for consistent detection of the pathogen. Among the six universal primer combinations tested, P1/Tint nested with fU5/rU3 produced consistent results. BLASTn searches of the sequences showed 99–100% similarity to sugarcane white leaf disease (SWL) or grassy shoot (SGS) disease-causing phytoplasma. The optimized nested PCR protocol was successful, with the minimum success rating of 88% and 100% specificity. Midribs of milky white bud leaf samples were the best tissue type for rapid detection. Systemic movement of the pathogen and a tentative latent period were also reported. The findings are helpful in the early detection of the disease.

Phytoplasmas are plant-pathogenic bacteria that are associated with yield losses in many crop plants worldwide. Phytoplasma strain differentiation is accomplished using in silico restriction fragment length polymorphism (RFLP) analysis of 16S ribosomal RNA-encoding gene sequences, which has resulted in the definition of ribosomal groups and subgroups of phytoplasmas. Due to limitations associated with this approach, a complementary classification scheme was recently developed based on RFLP analysis of the single-copy, protein-encoding gene chaperonin-60 (cpn60). We present the CpnClassiPhyR, software that facilitates phytoplasma strain classification using both RFLP and automated phylogenetic analysis of cpn60 sequences. This software is available through a web interface at http://cpnclassiphyr.ca .