The impact of soil carbon management and environmental conditions on N mineralization

Soil carbon (C) management is identified as a key element of sustainable agriculture, and an increase in nitrogen (N) mineralization rates is expected with an increase in soil C. However, any practical recommendation for using soil C management to substitute the application of synthetic N fertilizer needs to account simultaneously for other important agronomic variables and environmental conditions. For this purpose we investigated the simultaneous impact of soil C management, environmental conditions, and soil structure on N mineralization in two apple orchard systems in Havelock North, New Zealand. One system is an organic orchard using regular compost applications and the other is a neighboring integrated orchard with no external inputs of organic matter. The soil type, texture, and climate are identical in both orchards. We selected different temperatures (10°C, 15°C, and 20°C) and soil moistures (?30, ?100, and ?300?kPa) as the environmental conditions for N mineralization. Simultaneously, the hot-water extractable C (HWC) contents were measured and served as the indicator for the soil C management of the orchards. To analyze the impact of soil structure, the N mineralization of undisturbed cores was compared with that of disturbed samples. The net N mineralization of the soil in the organic orchard was on average six times higher than that in the integrated orchard. At the same time, in the organic orchard the HWC contents at the beginning of the N mineralization experiment were about two times higher than in the integrated orchard. In a multiple regression as a practical recommendation for the orchards of our case study, we could explain 84% of the variability of N mineralization rates using HWC and environmental conditions as the independent variables. The HWC content was the most significant variable in the multiple regression model and showed that soil C management has a more prominent role than the environmental conditions. Soil C management such as regular compost applications which increase the soil??s HWC contents can also be used to manage N mineralization. The significant difference between the undisturbed and disturbed samples showed the soil structure can have an effect on N mineralization.     

Comparison of two fibrin glues in anastomoses and skin closure

To control intra-operative haemorrhage, fibrin glues are preferred by many surgeons because of their biological advantages and convenience of application. Manufacturers have developed a few kinds of fibrin glues with a little difference in their composition. This study was to compare the effectiveness of two commercially available fibrin glues; Greenplast (Green Cross P. D. Company, Yongin, Korea) and Tisseel (Baxter-Immuno AG, Vienna, Austria). They were applied experimentally to several kinds of surgery in dogs - renal vessel anastomosis, partial splenectomy, intestinal anastomosis and incision skin wound - and evaluated for their haemostatic and adhesive effects. When the two glues were applied in renal vessel anastomosis, the amount of haemorrhage in artery and vein decreased significantly. They also decreased the haemorrhage in partial splenectomy. At 10 min after application of the glues to an incision skin wound, the tensile strengths developed were significantly higher than that of control. The present study indicates that two-component fibrin glues have a haemostatic effect as a mechanical barrier in renal vessel anastomosis and an adhesive effect in the early stage of incision skin wound closure, and the two glues have similar effects with no complications.     

Perturbation analysis of the steady-state fiber bundle flow by the random phase spectral method

This research reports on the variation behavior of the bundle thickness in a fiber bundle flow process, when the stochastic perturbation occurs. The stochastic perturbation is specified by an autocorrelation function, which is generated on the basis of the random phase spectrum. The profiles of the bundle thickness and velocity in a steady state were simulated, while the mathematical model describing the fiber bundle flow dynamics is employed. Simulation results showed that a stochastic signal with a specified autocorrelation function could apply to variations in the fiber bundle parameter and draft ratio. The distribution profiles of the velocity and linear density of the fiber bundle were estimated under the auto-correlated perturbations. Disturbances in the material parameter revealed a larger influence on the dynamic states of the fiber bundle flow than those in draft ratio.     

Limitations and capabilities of the NOAA satellite advanced very high resolution radiometer (AVHRR) for remote sensing of the Earth's surface

The advanced very high resolution radiometer (AVHRR) is an operational, high-quality, crosstrack, line-scanning multispectral radiometer. Its data at 1.1 km maximum spatial resolution, 2800 km swath width and five spectral bands have widespread applications in meteorology, oceanography, climatology, agriculture, hydrology, forestry and many other disciplines. Two AVHRR are maintained in continuous operational mode, borne by two National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites. Particularly valuable is the fact that this operational system provides imagery of all parts of the globe at least four times daily, large portions of which are archived centrally in several data centers around the world. Historical data are available back to 1985.

As a remote sensing system, the NOAA/TIROS-N satellites are arguably one of the most successful and extensively used components of the US space program. Through the direct-broadcast system, environmental data from the AVHRR and other sensors have been made available around the world to properly equipped users of all nations. The data are broadcast in two modes, automatic picture transmission (APT, low-cost, low-resolution, two-channel data) and high resolution picture transmission (HRPT, full resolution, all channels and other sensor data).

The purpose of this paper is to briefly describe the system, outlining its limitations and capabilities, to help potential new users keep their expectations within realistic levels. There are five categories of limitations on the utility of the AVHRR data for Earth surface applications: (1) spatial resolution and its space-time variability; (2) atmospheric effects on measurements; (3) no in-flight calibration of visible and near-infrared sensors; (4) special problems with the mid-infrared sensor; (5) the wide spectral sensitivity bands of the data channels.     

The use of visible and near‐infrared spectroscopy for the analysis of soil water repellency

This study investigated the potential of visible/near‐infrared reflectance spectroscopy (Vis‐NIRS) to predict soil water repellency (SWR). The top 40 mm of soils (n = 288) across 48 sites under pastoral land‐use in the North Island of New Zealand, which represented 10 soil orders and covered five classes of drought proneness, were analysed by standard laboratory methods and Vis‐NIRS. Soil WR was measured by using the molarity of ethanol droplet (MED) and the water drop penetration time (WDPT) tests. Soil organic carbon content (%C) was also measured to examine a possible relationship with SWR. A partial least squares regression (PLSR) model was developed by using Vis‐NIRS spectral data and the reference laboratory data. In addition, we explored the power of discrimination based on WDPT classes using partial least squares discriminant analysis (PLS‐DA). The PLSR of the processed spectra produced moderately accurate prediction for MED (R²_val = 0.61, RPD_val = 1.60, RMSE_val = 0.59) and good prediction for %C (R²_val = 0.82, RPD_val = 2.30, RMSE_val = 2.72). When the data from the 10 soil orders were considered separately and based on soil order rather than being grouped, the prediction of MED was further improved except for the Allophanic, Brown, Organic and Ultic soil orders. The PLS‐DA was successful in classifying 60% of soil samples into the correct WDPT classes. Our results indicate clearly that Vis‐NIRS has the potential to predict SWR. Further improvement in the prediction accuracy of SWR is envisaged by increasing the understanding of the relationship between Vis‐NIRS and the SWR of all New Zealand soil orders as a function of their physical properties and chemical constituents such as hydrophobic compounds.