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Since the discovery of citrus Huanglongbing (HLB) in Florida in 2005, research efforts to develop and identify germplasm resistant to HLB have intensified greatly.  Many research groups in Florida and elsewhere are screening existing citrus varieties and members of the Rutaceae in an attempt to identify useful sources of resistance that can be used in traditional breeding programs to produce commercial scions and rootstocks resistant to HLB.  Although progress has been made, it is generally accepted that although some level of tolerance and resistance have been identified, it is not likely that these will be sufficient to confer commercially acceptable levels of resistance in the short term.  Similarly, it is widely accepted that genetic modification using a biotechnology approach is likely to be the only way to achieve acceptable levels of resistance in commercial varieties in the near term.  Progress has been made by many groups to produce and screen plants with a wide variety of genes and approaches, and more than one group is starting the process to collect the data necessary for deregulation.  However, the deregulation process is daunting and full of hurdles and the science may actually be the easiest and the cheapest part of the project.  The process as it applies to one project will be presented to demonstrate what is involved as the industry moves forward with this technology.

Field data on intensity of plant diseases is very often irregularly spaced (i.e., there are varying amounts of distance between rows, ponds, voids, roads, houses, or other land areas). Typically, this type of data is gridded and the average disease intensity of the plants within the grid is used instead of the original data on each separate plant. This is done because the underlying statistical assumptions in the analysis of spatial data usually require that data be equally spaced. However, a new method of analysis, sometimes called second-generation wavelet analysis, can be used on irregularly spaced spatial data. Wavelet analysis is a method used to analyze variations in scale and position of non-stationary spatial signals (non-stationary for our data means the statistical properties can vary based on location within the orchard), and the second-generation refers to an iterative process, called a lifting scheme (1), which allows for the irregular spacing. Irregular spacing is often found in citrus groves as spacing within and between rows is often not uniform, and on a larger spatial scale, distance between blocks and plantings are not necessarily simple multiples of distances between rows and trees. In addition, there are a number of other issues such as missing trees, the presence of irregular roads, ponds, staging areas, etc., that cause citrus groves to have irregular distances between trees when viewed at the plantation or regional scale. Therefore, to test this new method, we conducted a second-generation spatial wavelet analysis on a large irregularly spaced citrus planting (Southern Gardens) in Florida where over 260,000 trees were assessed for incidence of huanglongbing (HLB) over five sampling times.

There are many reports in the literature, both historical and recent, that indicate that fruit from trees affected by Huanglongbing (HLB) can have off-flavors and result in off-flavored juice.  Several recent studies from Florida where fairly comprehensive sensory and chemical testing has been done, have shown that there are differences in flavor and specific chemical components in juice from healthy and HLB infected trees in some varieties and during some times of the year. However, there are also recent reports from Florida, mainly from production associated research trials and demonstration plots, where juice quality from HLB infected trees is reported to be good and similar to that of juice from healthy trees.  In virtually all of these production-related research trials, the variables measured for juice quality were Brix, acid and ratio and no other organoleptic components were considered.  Although these are standard measures of juice quality, they do not encompass the wide range parameters that are considered by processors and the beverage industry in the evaluation of raw input and final products.  In many cases, sensory evaluation by trained panelists is a routine procedure in the evaluation of input streams and the final product.  Thus sensory components should not be ignored when considering HLB management options, especially as the Florida industry moves towards 100% infection with HLB.  This paper will present some of the progress that has been made to develop methodology to discriminate juice produced from fruit from healthy and infected trees using methods that directly and indirectly measure compounds and characteristics that impact flavor.

Abstract Background Huanglongbing (HLB, previously known as citrus greening), is associated with Candidatus Liberibacter species and is a serious threat to citrus production world-wide. The pathogen is a Gram negative, unculturable, phloem-limited bacterium with limited known genomic information. Expanding the genetic knowledge of this organism may provide better understanding of the pathogen and possibly develop effective strategies for control and management of HLB. Results Here, we report cloning and characterization of an additional 14.7 Kb of new genomic sequences from three different genomic regions of the Candidatus Liberibacter asiaticus (Las). Sequence variation analyses among the available Ca. Liberibacter species sequences as well as the newly cloned 1.5 Kb of rpoB gene from different Ca. Liberibacter strains have identified INDELs and SNPs. Phylogenetic analysis of the deduced protein sequences from the cloned regions characterizes the HLB-associated Candidatus Liberibacter as a new clade in the sub-division of the α-proteobacteria. Conclusion Comparative analyses of the cloned gene regions of Candidatus Liberibacter with members of the order Rhizobiales suggest overall gene structure and order conservation, albeit with minor variations including gene decay due to the identified pseudogenes. The newly cloned gene regions contribute to our understanding of the molecular aspects of genomic evolution of Ca. Liberibacter.