Plant Biomarker Pattern, Screening Programme for Phytochemical Differences in Plants Exposed to Stress

A screening programme is developed to investigate phytochemical differences in plants xposed to stress compared with non-exposed plants. The screening programme, in its resent form or in a more simplified form, can be utilized in several different areas as a preliminary broad screening. The screening programme covers the most general groups of compounds found in plants. The following groups of phytochemical compounds are included in the programme: Unspecific compounds, organic acids, lipids, phenolic compounds, carbohydrates, terpenoids and N-, S- and P-containing compounds

A New Phytochemical Screening Programme used for Crops grown with Organic and Conventional Methods

A broad screening programme, covering the most general phytochemical groups of compounds, was developed on the basis of Thin Layer Chromatography (TLC). A total of 46 TLC systems, comprising 26 derivatization reagents, 3 stationary phases, and 4 mobile phases, were included. The TLC systems were classified according to the groups of phytochemical compounds detected: Alcohols and phenolic compounds; Carbohydrates; N-containing compounds; Organic acids and lipids; P-containing compounds; S-containing compounds, and Terpenoids. Furthermore, one group of TLC systems detected compounds from several of the mentioned groups. The screening programme was applied in the screening of potatoes (S. tuberosum L.), peas (P. sativum L.), kale (B. oleracea L.), carrots (D. carota L.), and apples (M. domestica Borkh.), cultivated with combinations of organic and conventional methods for plant protection and nutrient supply, for phytochemical differences (biomarkers). Distinctive phytochemical differences were found between the differently cultivated samples of these crops. In peas and carrots only one biomarker was found. In peas the biomarker was related to the soil conditions, while the biomarker in carrots was related to the use of pesticides. In potato, two biomarkers related to the use of pesticides were found. Three biomarkers were found in kale. Two of these could be related to the use of pesticide, while the last was related to either fertiliser or soil conditions. Several biomarkers were found apples, but a relation to the cultivation methods was not clear. Three of the biomarkers in apples could be related to either the use of pesticides or fertiliser, while no conclusions could be drawn from the other biomarkers found. The results of the screening programme form the basis for a potential development of a kit to detect whether crops are organically- or conventionally cultivated. Furthermore, the results from this part and other parts of the project "Organic food and health – a multigenerational animal experiment" provide basis for the selection of which secondary compounds to quantify by specific chemical analysis, isolate, and/or structure elucidation

Static and dynamic effective stress coefficient of chalk

Deformation of a hydrocarbon reservoir can ideally be used to estimate the effective stress acting on it. The effective stress in the subsurface is the difference between the stress due to the weight of the sediment and a fraction (effective stress coefficient) of the pore pressure. The effective stress coefficient is thus relevant for studying reservoir deformation and for evaluating 4D seismic for the correct pore pressure prediction. The static effective stress coefficient [Formula: see text] is estimated from mechanical tests and is highly relevant for effective stress prediction because it is directly related to mechanical strain in the elastic stress regime. The corresponding dynamic effective stress coefficient [Formula: see text] is easy to estimate from density and velocity of acoustic (elastic) waves. We studied [Formula: see text] and [Formula: see text] of chalk from the reservoir zone of the Valhall field, North Sea, and found that [Formula: see text] and [Formula: see text] vary with differential stress (overburden stress-pore pressure). For Valhall reservoir chalk with 40% porosity, [Formula: see text] ranges between 0.98 and 0.85 and decreases by 10% if the differential stress is increased by 25 MPa. In contrast, for chalk with 15% porosity from the same reservoir, [Formula: see text] ranges between 0.85 and 0.70 and decreases by 5% due to a similar increase in differential stress. Our data indicate that [Formula: see text] measured from sonic velocity data falls in the same range as for [Formula: see text], and that [Formula: see text] is always below unity. Stress-dependent behavior of [Formula: see text] is similar (decrease with increasing differential stress) to that of [Formula: see text] during elastic deformation caused by pore pressure buildup, for example, during waterflooding. By contrast, during the increase in differential stress, as in the case of pore pressure depletion due to production, [Formula: see text] increases with stress while [Formula: see text] decreases.</jats:p