An innovative microplate assay to facilitate the detection of antimicrobial activity in plant extracts.

A microplate assay was modified for the detection of antimicrobial activity in plant extracts. The aim was to develop an in vitro assay that could rapidly screen plant extracts to provide quantitative data on inhibition of microbial growth. A spectrophotometric assay using a microplate with serial dilutions of the plant extract and the bacteria was developed. Two bacteria, Staphylococcus aureus and Escherichia coli, were used for this study. Essential oils, oregano (Origanum vulgare) and lemon myrtle (Backhousia citriodora), and three active components carvacrol, thymol and citral were evaluated. The reproducibility of the assay was high, with correlation coefficients (r aureus and E. coli between 0.9321 and 0.9816. Similarly, r and 0.9814. This assay could also be used to measure antimicrobial activity in plant extracts which vary in pH and color.

The DOOR manual for plant nurseries

In the nursery industry, generic research conducted by government institutions is often not specific enough to be highly valued and adopted by the individual operator. Operators need practical solutions to their particular problems. Such problems almost invariably involve sets of conditions common to few other enterprises. This uniqueness reflects the almost infinite variation of options available in terms of species grown, media used, fertiliser, amendments and chemicals applied and the way water is supplied. The DOOR (Do Our Own Research) method advocates a relatively unexplored way of generating new, statistically sound research information in the nursery industry. The manual aims to enhance nursery operators' understanding and skills development in the following areas: critially evaluating opportunities and problems in the nursery environment, gathering relevant information, deriving and prioritising potential solutions to problems and opportunities, becoming familiar with the scientific method employed in testing potential solutions, carrying out statistically sound aand rigorous research, and developing recommendations that flow from the research information generated. The DOOR approach has application in a number of other industries and may provide important support at a time of declining research, development and extension investment by the public sector.

A checklist of plant pathogenic and other microfungi in the rainforests of the wet tropics of northern Queensland

Microfungi that cause disease or are associated with diseased plants in the wet tropics of northern Queensland are listed. A total of 206 host-pathogen combinations on 148 host species has been compiled from the results of plant disease surveys in the Wet Tropics World Heritage Area in 1992 and 1993, from herbarium records and from previously published host-pathogen combinations.

Plot size matters: interference from intergenotypic competition in plant phenotyping studies

Genetic and physiological studies often comprise genotypes diverse in vigour, size and flowering time. This can make the phenotyping of complex traits challenging, particularly those associated with canopy development, biomass and yield, as the environment of one genotype can be influenced by a neighbouring genotype. Limited seed and space may encourage field assessment in single, spaced rows or in small, unbordered plots, whereas the convenience of a controlled environment or greenhouse makes pot studies tempting. However, the relevance of such growing conditions to commercial field-grown crops is unclear and often doubtful. Competition for water, light and nutrients necessary for canopy growth will be variable where immediate neighbours are genetically different, particularly under stress conditions, where competition for resources and influence on productivity is greatest. Small hills and rod-rows maximise the potential for intergenotypic competition that is not relevant to a crop’s performance in monocultures. Response to resource availability will typically vary among diverse genotypes to alter genotype ranking and reduce heritability for all growth-related traits, with the possible exception of harvest index. Validation of pot experiments to performance in canopies in the field is essential, whereas the planting of multirow plots and the simple exclusion of plot borders at harvest will increase experimental precision and confidence in genotype performance in target environments.

Variation in water extraction with maize plant density and its impact on model application

The use of maize simulation models to determine the optimum plant population for rainfed environments allows the evaluation of plant populations over multiple years and locations at a lower cost than traditional field experimentation. However the APSIM maize model that has been used to conduct some of these 'virtual' experiments assumes that the maximum rate of soil water extraction by the crop root system is constant across plant populations. This untested assumption may cause grain yield to be overestimated in lower plant populations. A field experiment was conducted to determine whether maximum rates of water extraction vary with plant population, and the maximum rate of soil water extraction was estimated for three plant populations (2.4, 3.5 and 5.5 plants m(-2)) under water limited conditions. Maximum soil water extraction rates in the field experiment decreased linearly with plant population, and no difference was detected between plant populations for the crop lower limit of soil water extraction. Re-analysis of previous maize simulation experiments demonstrated that the use of inappropriately high extraction-rate parameters at low plant populations inflated predictions of grain yield, and could cause erroneous recommendations to be made for plant population. The results demonstrate the importance of validating crop simulation models across the range of intended treatments. (C) 2013 Elsevier E.V. All rights reserved.

Complete genome sequence and integrated protein localization and interaction map for alfalfa dwarf virus, which combines properties of both cytoplasmic and nuclear plant rhabdoviruses

Summary We have determined the full-length 14,491-nucleotide genome sequence of a new plant rhabdovirus, alfalfa dwarf virus (ADV). Seven open reading frames (ORFs) were identified in the antigenomic orientation of the negative-sense, single-stranded viral RNA, in the order 3′-N-P-P3-M-G-P6-L-5′. The ORFs are separated by conserved intergenic regions and the genome coding region is flanked by complementary 3′ leader and 5′ trailer sequences. Phylogenetic analysis of the nucleoprotein amino acid sequence indicated that this alfalfa-infecting rhabdovirus is related to viruses in the genus Cytorhabdovirus. When transiently expressed as GFP fusions in Nicotiana benthamiana leaves, most ADV proteins accumulated in the cell periphery, but unexpectedly P protein was localized exclusively in the nucleus. ADV P protein was shown to have a homotypic, and heterotypic nuclear interactions with N, P3 and M proteins by bimolecular fluorescence complementation. ADV appears unique in that it combines properties of both cytoplasmic and nuclear plant rhabdoviruses.

Induced carotenoid accumulation in Dunaliella salina and Tetraselmis suecica by plant hormones and UV-C radiation

Carotenoids prevent different degenerative diseases and improve human health. Microalgae are commercially exploited for carotenoids, including astaxanthin and β-carotene. Two commercially important microalgae, Dunaliella salina and Tetraselmis suecica, were treated with plant hormones salicylic acid (SA) and methyl jasmonate (MJ), or by UV-C radiation (T. suecica only) and a combination thereof. Significant increases in total carotenoids were found for D. salina and T. suecica after treatment with MJ (10 μmol/L) and SA (70–250 μmol/L), respectively. T. suecica also had significant increases in total carotenoids following UV-C radiation compared to control cultures. Among the carotenoids, lutein was the highest induced carotenoid. A combination of these two treatments also showed a significant increase in total carotenoids and lutein for T. suecica, when compared to controls. Plant hormones and UV-C radiation may be useful tools for increasing carotenoid accumulation in green microalgae although the responses are species- and dose-specific and should be trialed in medium to large scale to explore commercial production.

Markers for seedling and adult plant crown rot resistance in four partially resistant bread wheat sources

QTL identified for seedling and adult plant crown rot resistance in four partially resistant hexaploid wheat sources. PCR-based markers identified for use in marker-assisted selection. Crown rot, caused by Fusarium pseudograminearum, is an important disease of wheat in many wheat-growing regions globally. Complete resistance to infection by F. pseudograminearum has not been observed in a wheat host, but germplasm with partial resistance to this pathogen has been identified. The partially resistant wheat hexaploid germplasm sources 2-49, Sunco, IRN497 and CPI133817 were investigated in both seedling and adult plant field trials to identify markers associated with the resistance which could be used in marker-assisted selection programs. Thirteen different quantitative trait loci (QTL) conditioning crown rot resistance were identified in the four different sources. Some QTL were only observed in seedling trials whereas others appeared to be adult plant specific. For example while the QTL on chromosomes 1AS, 1BS, and 4BS contributed by 2-49 and on 2BS contributed by Sunco were detected in both seedling and field trials, the QTL on 1DL present in 2-49 and the QTL on 3BL in IRN497 were only detected in seedling trials. Genetic correlations between field trials of the same population were strong, as were correlations between seedling trials of the same population. Low to moderate correlations were observed between seedling and field trials. Flanking markers, most of which are less than 10 cM apart, have now been identified for each of the regions associated with crown rot resistance.

An asparaginyl endopeptidase mediates in vivo protein backbone cyclization

Proteases can catalyze both peptide bond cleavage and formation, yet the hydrolysis reaction dominates in nature. This presents an interesting challenge for the biosynthesis of backbone cyclized (circular) proteins, which are encoded as part of precursor proteins and require post-translational peptide bond formation to reach their mature form. The largest family of circular proteins are the plant-produced cyclotides; extremely stable proteins with applications as bioengineering scaffolds. Little is known about the mechanism by which they are cyclized in vivo but a highly conserved Asn (occasionally Asp) residue at the C terminus of the cyclotide domain suggests that an enzyme with specificity for Asn (asparaginyl endopeptidase; AEP) is involved in the process. Nicotiana benthamiana does not endogenously produce circular proteins but when cDNA encoding the precursor of the cyclotide kalata B1 was transiently expressed in the plants they produced the cyclotide, together with linear forms not commonly observed in cyclotide-containing plants. Observation of these species over time showed that in vivo asparaginyl bond hydrolysis is necessary for cyclization. When AEP activity was suppressed, either by decreasing AEP gene expression or using a specific inhibitor, the amount of cyclic cyclotide in the plants was reduced compared with controls and was accompanied by the accumulation of extended linear species. These results suggest that an AEP is responsible for catalyzing both peptide bond cleavage and ligation of cyclotides in a single processing event.

A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets

Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

Detection and use of QTL for complex traits in multiple environments.

QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.