Introduction to the development of an information management system for soil mix technology using artificial neural networks

This paper introduces current work in collating data from different projects using soil mix technology and establishing trends using artificial neural networks (ANNs). Variation in unconfined compressive strength as a function of selected soil mix variables (e.g., initial soil water content and binder dosage) is observed through the data compiled from completed and on-going soil mixing projects around the world. The potential and feasibility of ANNs in developing predictive models, which take into account a large number of variables, is discussed. The main objective of the work is the management and effective utilization of salient variables and the development of predictive models useful for soil mix technology design. Based on the observed success in the predictions made, this paper suggests that neural network analysis for the prediction of properties of soil mix systems is feasible. © ASCE 2011.

The Effects of Lead Sources on Oral Bioaccessibility in Soil and Implications for Contaminated Land Risk Management

Lead (Pb) is a non-threshold toxin capable of inducing toxic effects at any blood level but availability of soil screening criteria for assessing potential health risks is limited. The oral bioaccessibility of Pb in 163 soil samples was attributed to sources through solubility estimation and domain identification. Samples were extracted following the Unified BARGE Method. Urban, mineralisation, peat and granite domains accounted for elevated Pb concentrations compared to rural samples. High Pb solubility explained moderate-high gastric (G) bioaccessible fractions throughout the study area. Higher maximum G concentrations were measured in urban (97.6 mg kg−1) and mineralisation (199.8 mg kg−1) domains. Higher average G concentrations occurred in mineralisation (36.4 mg kg−1) and granite (36.0 mg kg−1) domains. Findings suggest diffuse anthropogenic and widespread geogenic contamination could be capable of presenting health risks, having implications for land management decisions in jurisdictions where guidance advises these forms of pollution should not be regarded as contaminated land.

Influence of Soil and Irrigation Management on the Quality of Seedless Crimson Table Grapes

The market for table grapes is moving into mass production of specialty seed-less grapes in covered areas, aiming at obtaining premium prices with early or late production of high quality products. Production of quality seedless grapes is not straightforward since it is requires the correct combination of various independent characteristics, such as color, sugars, size and quantity at the right moment for successful harvesting and marketing. The present study was carried out at the two largest Portuguese producers located in Alentejo, and has the objective of studying the effect of irrigation management strategies and two different soils on the various relevant parameters for successful production and marketing. The management strategies were the application of ten day stress at the end of the cycle, in order to promote early maturing of the grapes. Three different timings of the stress were applied. Soil moisture, sap flow, bark thickness, as well as leaf water potential, stomatal conductance and chlorophyll content were measured regularly during the production season. The results indicate that the roots explore a rather large soil volume and the plants can successfully withstand reasonable periods of drought without significant changes to the plant physiology. Additionally late rains can mask the effect of any farmer applied drought and invalidate any farmer induced stress to the plants. Water-logged soils tend to cause early onset of maturity, but cause the ripening stage to extend over a longer period of time, and thus, in effect result in a delay in the harvest date. Topography also has some effect on the ripening, since hot air tends to accumulate under the plastic at the higher areas of the field. This work is funded by PRODER, 4.1, within the scope of project MORECRIMSON