Soil exploration by sorghum root systems in wide row cropping systems

Wide and ‘skip row’ row configurations have been used as a means to improve yield reliability in grain sorghum production. However, there has been little effort put to design of these systems in relation to optimal combinations of root system characteristics and row configuration, largely because little is known about root system characteristics. The studies reported here aimed to determine the potential extent of root system exploration in skip row systems. Field experiments were conducted under rain-out shelters and the extent of water extraction and root system growth measured. One experiment was conducted using widely-spaced twin rows grown in the soil. The other experiment involved the use of specially constructed large root observation chambers for single plants. It was found that the potential extent of root system exploration in sorghum was beyond 2m from the planted rows using conventional hybrids and that root exploration continued during grain filling. Preliminary data suggested that the extent of water extraction throughout this region depended on root length density and the balance between demand for, and supply of, water. The results to date suggest that simultaneous genetic and management manipulation of wide row production systems might lead to more effective and reliable production in specific environments. Further study of variation in root-shoot dynamics and root system characteristics is required to exploit possible opportunities.

Lack of mycorrhizal autoregulation and phytohormonal changes in the supernodulating soybean mutant nts1007

Autoregulatory mechanisms have been reported in the rhizobial and the mycorrhizal symbiosis. Autoregulation means that already existing nodules or an existing root colonization by an arbuscular mycorrhizal fungus systemically suppress subsequent nodule formation/root colonization in other parts of the root system. Mutants of some legumes lost their ability to autoregulate the nodule number and thus display a supernodulating phenotype. On studying the effect of pre-inoculation of one side of a split-root system with an arbuscular mycorrhizal fungus on subsequent mycorrhization in the second side of the split-root system of a wild-type soybean (Glycine max L.) cv. Bragg and its supernodulating mutant nts1007, we observed a clear suppressional effect in the wild-type, whereas further root colonization in the split-root system of the mutant nts1007 was not suppressed. These data strongly indicate that the mechanisms involved in supernodulation also affect mycorrhization and support the hypothesis that the autoregulation in the rhizobial and the mycorrhizal symbiosis is controlled in a similar manner. The accumulation patterns of the plant hormones IAA, ABA and Jasmonic acid (JA) in non-inoculated control plants and split-root systems of inoculated plants with one mycorrhizal side of the split-root system and one non-mycorrhizal side, indicate an involvement of IAA in the autoregulation of mycorrhization. Mycorrhizal colonization of soybeans also resulted in a strong induction of ABA and JA levels, but on the basis of our data the role of these two phytohormones in mycorrhizal autoregulation is questionable.

Vector Error-Correction Models in a consumer packaged goods category forecasting decision support system

A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.

The effect of copper toxicity on the growth and root morphology of Rhodes grass (Chloris gayana Knuth.) in resin buffered solution culture

A solution culture experiment was conducted to examine the effect of Cu toxicity on Rhodes grass (Chloris gayana Knuth.), a pasture species used in mine-site rehabilitation. The experiment used dilute, solution culture to achieve external nutrient concentrations, which were representative of the soil solution, and an ion exchange resin to maintain stable concentrations of Cu in solution. Copper toxicity was damaging to plant roots, with symptoms ranging from disruption of the root cuticle and reduced root hair proliferation, to severe deformation of root structure. A reduction in root growth was observed at an external Cu concentration of < 1 mu M, with damage evident from an external concentration of 0.2 mu M. Critical to the success of this experiment, in quantitatively examining the relationship between external Cu concentration and plant response, was the use of ion exchange resin to buffer the concentration of Cu in solution. After some initial difficulty with pH control, stable concentrations of Cu in solution were maintained for the major period of plant growth. The development of this technique will facilitate future investigations of the effect of heavy metals on plants.

Tracking the states of a nonlinear and nonstationary system in the weight-space of artificial neural networks

We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We de. ne a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states i and j in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.