Neural network enhanced generalised minimum variance self-tuning controller for nonlinear discrete-time systems

A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Progressive erosion of genetic and epigenetic variation in callus-derived cocoa (Theobroma cacao) plants

Relatively little is known about the timing of genetic and epigenetic forms of somaclonal variation arising from callus growth. We surveyed for both types of change in cocoa (Theobroma cacao) plants regenerated from calli of various ages, and also between tissues from the source trees. For genetic change, we used 15 single sequence repeat (SSR) markers from four source trees and from 233 regenerated plants. For epigenetic change, we used 386 methylation-sensitive amplified polymorphism (MSAP) markers on leaf and explant (staminode) DNA from two source trees and on leaf DNA from 114 regenerants. Genetic variation within source trees was limited to one slippage mutation in one leaf. Regenerants were far more variable, with 35% exhibiting at least one mutation. Genetic variation initially accumulated with culture age but subsequently declined. MSAP (epigenetic) profiles diverged between leaf and staminode samples from source trees. Multivariate analysis revealed that leaves from regenerants occupied intermediate eigenspace between leaves and staminodes of source plants but became progressively more similar to source tree leaves with culture age. Statistical analysis confirmed this rather counterintuitive finding that leaves of ‘late regenerants’ exhibited significantly less genetic and epigenetic divergence from source leaves than those exposed to short periods of callus growth.

Optical sensors for monitoring water uptake in plants

The monitoring of water uptake in plants is becoming increasingly important. Optical sensors offer considerable advantages over conventional methods and several sensors have been developed including an optical potometer that monitors water uptake from individual roots, the detection of xylem cavitation using audio acoustic emissions with an interferometric force feedback microphone, and an optical fiber displacement transducer that detects changes in leaf thickness in relation to leaf-water potential.

Reconstruction of historical pollination rates reveals linked declines of pollinators and plants

Widespread reports of low pollination rates suggest a recent anthropogenic decline in pollination that could threaten natural and agricultural ecosystems. Nevertheless, unequivocal evidence for a decline in pollination over time has remained elusive because it was not possible to determine historical pollination rates. Here we demonstrate a widely applicable method for reconstructing historical pollination rates, thus allowing comparison with contemporary rates from the same sites. We focused on the relationship between the oil-collecting bee Rediviva peringueyi (Melittidae) and the guild of oil-secreting orchid species (Coryciinae) that depends on it for pollination. The guild is distributed across the highly transformed and fragmented lowlands of the Cape Region of South Africa. We show that rehydrated herbarium specimens of Pterygodium catholicum, the most abundant member of the guild, contain a record of past pollinator activity in the form of pollinarium removal rates. Analysis of a pollination time series showed a recent decline in pollination on Signal Hill, a small urban conservation area. The same herbaria contain historical species occurrence data. We analyzed this data and found that there has been a contemporaneous shift in orchid guild composition in urban areas due to the local extirpation of the non-clonal species, consistent with their greater dependence on seeds and pollination for population persistence.

Ornamental Mediterranean plants in the UK: root adaptations to hypoxia and anoxia

Mediterranean species are popular landscape plants in the UK and well suited to the predicted climate change scenarios of hotter, drier summers. What is less clear is how these species will respond to the more unpredictable rainfall patterns also anticipated, where soil water-logging may become more prevalent, especially in urban environments where soil sealing can restrict drainage. Pot experiments on flooding of four Mediterranean species (Cistus × hybridus, Lavandula angustifolia ‘Munstead’, Salvia officinalis and Stachys byzantina) showed that the effects of waterlogging were only severe when the temperature was high and flooding prolonged. All plants survived the flooding in winter, but during the summer a 17-day flood resulted in the death of 30-40% of the Salvia officinalis and Cistus × hybridus. To examine the response of roots to oxygen deprivation over a range of conditions from total absence of oxygen (anoxia), low oxygen (hypoxia) and full aeration, rooted cuttings of Salvia officinalis were grown in a hydroponic-based system and mixtures of oxygen and nitrogen gases bubbled through the media. Anoxia was found to reduce root development dramatically. When the plants were subjected to a period of hypoxia they responded by increasing the production of lateral roots close to the surface thus enabling them to acclimate to subsequent anoxia. This greatly increased their chances of survival.

DNA barcodes for Mexican Cactaceae, plants under pressure from wild collecting

DNA barcodes could be a useful tool for plant conservation. Of particular importance is the ability to identify unknown plant material, such as from customs seizures of illegally collected specimens. Mexican cacti are an example of a threatened group, under pressure because of wild collection for the xeriscaping trade and private collectors. Mexican cacti also provide a taxonomically and geographically coherent group with which to test DNA barcodes. Here, we sample the matK barcode for 528 species of Cactaceae including approximately 75% of Mexican species and test the utility of the matK region for species-level identification. We find that the matK DNA barcode can be used to identify uniquely 77% of species sampled, and 79-87% of species of particular conservation importance. However, this is far below the desired rate of 95% and there are significant issues for PCR amplification because of the variability of primer sites. Additionally, we test the nuclear ITS regions for the cactus subfamily Opuntioideae and for the genus Ariocarpus (subfamily Cactoideae). We observed higher rates of variation for ITS (86% unique for Opuntioideae sampled) but a much lower PCR success, encountering significant intra-individual polymorphism in Ariocarpus precluding the use of this marker in this taxon. We conclude that the matK region should provide useful information as a DNA barcode for Cactaceae if the problems with primers can be addressed, but matK alone is not sufficiently variable to achieve species-level identification. Additional complementary regions should be investigated as ITS is shown to be unsuitable

Sugars in crop plants

We review current knowledge of the most abundant sugars, sucrose, maltose, glucose and fructose, in the world's major crop plants. The sucrose-accumulating crops, sugar beet and sugar cane, are included, but the main focus of the review is potato and the major cereal crops. The production of sucrose in photosynthesis and the inter-relationships of sucrose, glucose, fructose and other metabolites in primary carbon metabolism are described, as well as the synthesis of starch, fructan and cell wall polysaccharides and the breakdown of starch to produce maltose. The importance of sugars as hormone-like signalling molecules is discussed, including the role of another sugar, trehalose, and the trehalose biosynthetic pathway. The Maillard reaction, which occurs between reducing sugars and amino acids during thermal processing, is described because of its importance for colour and flavour in cooked foods. This reaction also leads to the formation of potentially harmful compounds, such as acrylamide, and is attracting increasing attention as food producers and regulators seek to reduce the levels of acrylamide in cooked food. Genetic and environmental factors affecting sugar concentrations are described.

Flight to quality? An investigation of the attributes of sold properties in hot and cold markets

This paper uses sales transaction data in order to examine whether flight from risk phenomena took place in the US office property investment market during the financial crisis of 2007-2009. The effect of the crisis on the pricing of property quality attributes, mainly summarized by the class category of each building, is investigated. In addition, the paper examines how turnover levels were affected by the market downturn and whether there were significant variations between different real estate quality types. The results of the hedonic regression models suggest that the price spread between Class, A, B and C grew significantly during the downturn. We also find that property attributes such as size, height and age are priced significantly different in ‘hot’ and ‘cold’ markets.

Evaluating mid-infrared spectroscopy as a new technique for predicting sensory texture attributes of processed cheese

The objective of this study was to investigate the potential application of mid-infrared spectroscopy for determination of selected sensory attributes in a range of experimentally manufactured processed cheese samples. This study also evaluates mid-infrared spectroscopy against other recently proposed techniques for predicting sensory texture attributes. Processed cheeses (n = 32) of varying compositions were manufactured on a pilot scale. After 2 and 4 wk of storage at 4 degrees C, mid-infrared spectra ( 640 to 4,000 cm(-1)) were recorded and samples were scored on a scale of 0 to 100 for 9 attributes using descriptive sensory analysis. Models were developed by partial least squares regression using raw and pretreated spectra. The mouth-coating and mass-forming models were improved by using a reduced spectral range ( 930 to 1,767 cm(-1)). The remaining attributes were most successfully modeled using a combined range ( 930 to 1,767 cm(-1) and 2,839 to 4,000 cm(-1)). The root mean square errors of cross-validation for the models were 7.4(firmness; range 65.3), 4.6 ( rubbery; range 41.7), 7.1 ( creamy; range 60.9), 5.1(chewy; range 43.3), 5.2(mouth-coating; range 37.4), 5.3 (fragmentable; range 51.0), 7.4 ( melting; range 69.3), and 3.1 (mass-forming; range 23.6). These models had a good practical utility. Model accuracy ranged from approximate quantitative predictions to excellent predictions ( range error ratio = 9.6). In general, the models compared favorably with previously reported instrumental texture models and near-infrared models, although the creamy, chewy, and melting models were slightly weaker than the previously reported near-infrared models. We concluded that mid-infrared spectroscopy could be successfully used for the nondestructive and objective assessment of processed cheese sensory quality..