Regulated irrigation of woody ornamentals to improve plant quality and precondition against drought stress

Regulated irrigation has the potential to improve crop quality in woody ornamentals by reducing excessive vigour and promoting a more compact habit. This research aimed to compare the effectiveness and the mode of action of two techniques, regulated deficit irrigation (RDI) and partial root drying (PRD), when applied to container-grown ornamentals through drip irrigation. Results showed that RDI and PRD reduced growth in Cotinus coggygria 'Royal Purple', but in Forsythia x intermedia 'Lynwood', significant reductions were recorded only with RDI. Physiological measurements in Forsythia indicated that reductions in stomatal conductance (g(s)) occurred in both treatments, but those in the RDI tended to be more persistent. Reduced g(s) in PRD was consistent with the concept that chemical signals from the root can regulate stomatal aperture alone; however, the data also suggested that optimising the growth reduction required a moderate degree of shoot water deficit (i.e. a hydraulic signal to be imposed). As RDI was associated with tissue water deficit, it was used in a second experiment to determine the potential of this technique to precondition container-grown plants against subsequent drought stress (e.g. during retail stages or after planting out). Speed of acclimation would be important in a commercial context, and the results demonstrated that both slow and rapid imposition of RDI enabled Forsythia plants to acclimate against later drought events. This article discusses the potential to both improve ornamental plant quality and enhance tolerance to subsequent adverse conditions through controlled, regulated irrigation.

Liming upland grassland: the effects on earthworm communities and the chemical characteristics of carbon in casts

Different earthworm species have different tolerances of acid soil conditions, and the application of lime to upland grassland to improve the grazing quality may therefore alter the size and diversity of the earthworm community. Altering soil properties may also affect the chemical characteristics of organic C in earthworm casts. We surveyed the earthworm community of an upland grassland in southern Scotland at the outset of annual lime applications, and after 3 years, and used C-13 nuclear magnetic resonance (NMR) spectroscopy to assess the distribution of C between different functional groups in the organic matter. In addition, soil was incubated for 8 weeks with several earthworm species in the presence or absence of lime, and the earthworm casts were subsequently analysed by C-13 NMR spectroscopy. Liming did not significantly affect earthworm abundance or species diversity, but it did affect the chemical composition of the casts. Casts from earthworms incubated in unlimed soil had greater ratios of alkyl-C to O-alkyl-C, indicative of more decomposed, recalcitrant C, and spectra from litter-feeding species had the greatest intensities of O-alkyl-C signals. In limed soil, the largest O-alkyl-C signal intensities were not restricted to litter-feeding species, indicating an increase in the quality of organic matter ingested by geophagous species.

Electrochemical determination of plant-derived leuco-indigo after chemical reduction by glucose

Electrochemical determination of redox active dye species is demonstrated in indigo samples contaminated with high levels of organic and inorganic impurities. The use of a hydrodynamic electrode system based on a vibrating probe (250 Hz, 200 mu m lateral amplitude) allows time-independent diffusion controlled signals to be enhanced and reliable concentration data to be obtained under steady state conditions at relatively fast scan rates up to 4 V s-1In this work the indigo content of a complex plant-derived indigo sample (dye content typically 30%) is determined after indigo is reduced by addition of glucose in aqueous 0.2 M NaOH. The soluble leuco-indigo is measured by its oxidation response at a vibrating electrode. The vibrating electrode, which consisted of a laterally vibrating 500 mu m diameter gold disc, is calibrated with Fe(CN)(6) 3-/4- in 0.1 M KCl and employed for indigo determination at 55, 65, and 75 C in 0.2 M NaOH. Determinations of the indigo content of 25 different samples of plant-derived indigo are compared with those obtained by conventional spectrophotometry. This comparison suggests a significant improvement by the electrochemical method, which appears to be less sensitive to impurities.

Complex extreme learning machine applications in terahertz pulsed signals feature sets

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.

The potential for chemical mixtures from the environment to enable the cancer hallmark of sustained proliferative signalling

The aim of this work is to review current knowledge relating the established cancer hallmark, sustained cell proliferation to the existence of chemicals present as low dose mixtures in the environment. Normal cell proliferation is under tight control, i.e. cells respond to a signal to proliferate, and although most cells continue to proliferate into adult life, the multiplication ceases once the stimulatory signal disappears or if the cells are exposed to growth inhibitory signals. Under such circumstances, normal cells remain quiescent until they are stimulated to resume further proliferation. In contrast, tumour cells are unable to halt proliferation, either when subjected to growth inhibitory signals or in the absence of growth stimulatory signals. Environmental chemicals with carcinogenic potential may cause sustained cell proliferation by interfering with some cell proliferation control mechanisms committing cells to an indefinite proliferative span.