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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.

Commercial sweet orange cultivars lack resistance to Huanglongbing (HLB), a serious phloem limited bacterial disease that is usually fatal. In order to develop sustained disease resistance to HLB, transgenic sweet orange cultivars ‘Hamlin’ and ‘Valencia’ expressing an Arabidopsis thaliana NPR1 gene under the control of a constitutive CaMV 35S promoter or a phloem specific Arabidopsis SUC2 (AtSUC2) promoter were produced. Overexpression of AtNPR1 resulted in trees with normal phenotypes that exhibited enhanced resistance to HLB. Phloem specific expression of NPR1 was equally effective for enhancing disease resistance. Transgenic trees exhibited reduced diseased severity and a few lines remained disease-free even after 36 months of planting in a high-disease pressure field site. Expression of the NPR1 gene induced expression of several native genes involved in the plant defense signaling pathways. The AtNPR1 gene being plant derived can serve as a component for the development of an all plant T-DNA derived consumer friendly GM tree. [ABSTRACT FROM AUTHOR]

Variability in yield among sugarcane (a complex hybrid of Saccharum spp.) genotypes grown with and without mill mud application on sand soils in Florida has been documented, but little is known about what causes yield differences and if there are any relationships between yield components and physiological parameters. This study determined responses of leaf relative chlorophyll level (SPAD readings), photochemical efficiency of photosystem II in dark-adapted leaves (Fv/Fm), leaf stomatal conductance (gs), net photosynthetic rate (Pn), transpiration rate (E), difference between leaf and air temperatures (Tl-Ta), and spectral reflectance in one Erianthus [Erianthus arundinaceus (Rez.) Jeswiet] and seven sugarcane genotypes and their relationships to yield components across genotypes. Reflectance, Fv/Fm, SPAD, gs, Pn, E, and Tl-Ta were measured on leaves at the top visible dewlap during the first- and second-ratoon crops on a Margate sand soil (siliceous, hyperthermic Mollic Psammaquent) with or without mill mud added before planting. Mill mud application reduced leaf reflectance at wavelengths of 560 and 710 nm and significantly increased leaf SPAD, gs, Pn, and E in the first-ratoon crop only. Genotypic differences were detected in most physiological traits and yield components. Most physiological traits correlated with cane and sucrose yields when no mill mud was added. Genotypic variation in physiological and yield responses to mill mud application and genotype x mill mud interactions in yields indicated that augmenting yield selection of genotypes with leaf physiological traits will improve sugarcane breeding programs for sand soils. [ABSTRACT FROM AUTHOR]

Background Huanglongbing (HLB) or citrus greening is a devastating disease of citrus. The gram-negative bacterium Candidatus Liberibacter asiaticus (Las) belonging to the α-proteobacteria is responsible for HLB in North America as well as in Asia. Currently, there is no cure for this disease. Early detection and quarantine of Las-infected trees are important management strategies used to prevent HLB from invading HLB-free citrus producing regions. Quantitative real-time PCR (qRT-PCR) based molecular diagnostic assays have been routinely used in the detection and diagnosis of Las. The oligonucleotide primer pairs based on conserved genes or regions, which include 16S rDNA and the β-operon, have been widely employed in the detection of Las by qRT-PCR. The availability of whole genome sequence of Las now allows the design of primers beyond the conserved regions for the detection of Las explicitly. Results We took a complimentary approach by systematically screening the genes in a genome-wide fashion, to identify the unique signatures that are only present in Las by an exhaustive sequence based similarity search against the nucleotide sequence database. Our search resulted in 34 probable unique signatures. Furthermore, by designing the primer pair specific to the identified signatures, we showed that most of our primer sets are able to detect Las from the infected plant and psyllid materials collected from the USA and China by qRT-PCR. Overall, 18 primer pairs of the 34 are found to be highly specific to Las with no cross reactivity to the closely related species Ca. L. americanus (Lam) and Ca. L. africanus (Laf). Conclusions We have designed qRT-PCR primers based on Las specific genes. Among them, 18 are suitable for the detection of Las from Las-infected plant and psyllid samples. The repertoire of primers that we have developed and characterized in this study enhanced the qRT-PCR based molecular diagnosis of HLB. [ABSTRACT FROM AUTHOR]

In Florida, long-term results for identifying high yielding sugarcane (Saccharum spp.) cultivars have been better for Histosols (muck soils) than sand soils. We examined whether selection could be improved by comparing genotypes on a sand soil with and without added mill mud (MM) (in Florida, MM is primarily muck soil). One Erianthus and 31 sugarcane genotypes were planted in 2007 with MM at 0 or 1510 m³ ha-1 in main plots and genotypes as subplots in a 3-yr field experiment on a Margate sand soil (siliceous, hyperthermic Mollic Psammaquent). Commercial recoverable sucrose (CRS) (g kg-1), and cane (CY) and sucrose (SY) yields (Mg ha-1) were determined during the next 3yr. Mill mud reduced CRS from 127 to 111 g kg-1 but increased cane and sucrose yields from 80 to 150 and 10 to 17 Mg ha-1, respectively. Compared with the check of CP 89-2143, 2, 10, and 8 genotypes were differentially affected by soil treatment (P = 0.10) for CRS, CY, and SY, respectively. CP 01-2390 was the most adapted sand genotype; its CYs on sand with and without MM were 147 and 143 Mg ha-1, respectively. Compared with previous research, CY responses were well predicted for five genotypes, but poorly predicted for four genotypes in this study. Multiple locations are needed for sugarcane genotype selection on sand soils. Using a sand soil with and without added MM can be a useful supplemental, rather than singular approach for improving sugarcane genotype selection in Florida. [ABSTRACT FROM AUTHOR]

Accurate seasonal estimates of fiber are needed to maximize profits whether producing sugarcane (Saccharum spp.) for sucrose or ethanol. The main purpose of this study was to determine the effects of sample date and crop cycle on fiber content of three sugarcane cultivars growing on sand and organic (muck) soils, and secondarily to determine if fiber could be reliably estimated 1 mo before the beginning of the harvest season. From September through February, from 2007-2009, fiber content was estimated from monthly sampled stripped stalks of cultivars CP 72-2086, CP 78-1628, and CP 89-2143 growing in three replications of field plots in south Florida in the plant-cane, first-ratoon, and second-ratoon crop cycles on Pompano fine sand (siliceous, hyperthermic Typic Psammaquent) or Margate sand (Siliceous, hyperthermic Mollic Psammaquent), and Torry muck (euic, hyperthermic Typic Haplosaprist) soils. Linear increases in fiber content ranged from 0.07 to 0.28 g kg-1 d-1 Quadratic models usually predicted maximum fiber content from December through early January. On sand soils, the cultivar rankings were often similar to expectations, with fiber content of CP 78-1628 > CP 89-2143 > CP 72-2086. On the muck soil, CP 78-1628 fiber content was high, but differences between CP 72-2086 and CP 89-2143 were not consistent. For all soils, overall means were often not indicative of fiber status due to significant, but inconsistent interactions. Researchers should analyze fiber content whenever they analyze sucrose content, and mills should monitor fiber content daily of unique cultivar × crop cycle × soil deliveries. [ABSTRACT FROM AUTHOR]

• We analyze the short and long term mechanisms of spread for the Citrus tristeza virus, using a method that is generalizable for other crop diseases. • Present a methodology that is applicable to plots of discrete observations and is not a combinatorial model. • Model the probabilities of infection overtime for each observation using Ordinary Differential Equations. This allows each observation to be considered a Bernoulli trial with conditional independence, given the probability of infection. • Use the conditional independence of observations to construct a joint likelihood, from which Bayesian and Information theoretic techniques can be used for model and parameter inference. The Citrus tristeza virus (CTV) is one of the most economically devastating citrus diseases worldwide. The spread of CTV in eastern Spain was studied by Gottwald et al. with the goal of determining the spatio-temporal mechanisms of spread. Since the subjects in this study are individual trees, it is natural to think of infections as Bernoulli trials. This approach is difficult however, due to the spatial and temporal dependence of the observations. Consequently, a system of ordinary differential equations (ODE) was used to model the probabilities of infection as well as the spatial and temporal dependence. Given the parameters in the ODE, the probabilities of infection are treated as conditionally independent. Using the conditional independence we then specify the joint likelihood function as a Poisson binomial distribution. For the purpose of model selection and hypothesis testing we, employed accumulated prediction error (APE) which has connections to both Bayesian and frequentist frameworks. We demonstrated the robustness of our method in accounting for spatio-temporal dependencies in the data by accurately predicting the spatial distribution of the disease through Join Counts. [ABSTRACT FROM AUTHOR]