The Cost of Off-Flavor

Off-flavor problems in farm-raised catfish Ictalurus punctatus increase production costs and pose inventory management problems for catfish farmers. Multiperiod mathematical programming techniques were used to test the effect of 16 different off-flavor scenarios on expected net returns above variable cost with and without cash flow restrictions. The patterns of off-flavor incidence had less effect on farm profits than whether or not fish are off-flavor during certain key months of the year. To be feasible, systems designed to purge off-flavor from catfish would need to cost less than $0.05 to $0.06/kg (if cash flow is not a consideration) or $0.04/kg to $0.25/ke (with cash flow considerations).     

Immune response following vaccination against Salmonella Enteritidis using 2 commercial bacterins in laying hens

The humoral and cell-mediated immune (CMI) response to 2 commercial killed Salmonella Enteritidis (SE) vaccines (Layermune and MBL SE4C) was evaluated in laying hens. Layers were distributed in 2 experimental groups. The first received a single immunization at 16 wk of age, while the second experimental group was immunized at 12 wk of age and again at 18 wk of age. Serum immunoglobulin (Ig)G antibodies were measured using a commercial SE ELISA kit and showed persistent levels from 3 to 32 and 34 wk post-vaccination. The vaccination protocol using 2 immunizations showed a higher seroconversion level than the single vaccination. However, our results for bacterial intracellular survival indicated that IgG titers were not linked with bacterial killing. Local IgA production was measured in the intestines and oviducts with an in-house SE whole cell antigen ELISA. Only the MBL SE4C vaccine elicited IgA antibody production when tested on intestine and oviduct mucosal secretions, 3-weeks post-vaccination in both immunization protocol groups. To evaluate the CMI response, the splenic T-cells and B-cells populations were analyzed using flow cytometry. The CD3/B-cell ratio decreased 3 wk after the second immunization in the twice vaccinated Layermune group due to an increase in B-cells.     

Comparative analysis of three chemometric techniques for the spectroradiometric assessment of canopy chlorophyll content in winter wheat

Hyperspectral data sets contain useful information for characterizing vegetation canopies not previously available from multi-spectral data sources. However, to make full use of the information content one has to find ways for coping with the strong multi-collinearity in the data. The redundancy directly results from the fact that only a few variables effectively control the vegetation signature. This low dimensionality strongly contrasts with the often more than 100 spectral channels provided by modern spectroradiometers and through imaging spectroscopy. With this study we evaluated three different chemometric techniques specifically designed to deal with redundant (and small) data sets. In addition, a widely used 2-band vegetation index was chosen (NDVI) as a baseline approach. A multi-site and multi-date field campaign was conducted to acquire the necessary reference observations. On small subplots the total canopy chlorophyll content was measured and the corresponding canopy signature (450-2500 nm) was recorded (n_obs = 42). Using this data set we investigated the predictive power and noise sensitivity of stepwise multiple linear regression (SMLR) and two ‘full spectrum’ methods: principal component regression (PCR) and partial least squares regression (PLSR). The NDVI was fitted to the canopy chlorophyll content using an exponential relation. For all techniques, a jackknife approach was used to obtain cross-validated statistics. The PLSR clearly outperformed all other techniques. PLSR gave a cross-validated RMSE of 51 mg m⁻² for canopy chlorophyll contents ranging between 38 and 475 mg m⁻² (0.99 ≤ LAI ≤ 8.74 m² m⁻²). The lowest accuracy was achieved using PCR (RMSE_cv = 82 mg m⁻² and ). The NDVI, even using chlorophyll optimized band settings, could not reach the accuracy of PLSR. Regarding the sensitivity to artificially created (white) noise, PCR showed some advantages, whereas SMLR was the most sensitive chemometric technique. For relatively small, highly multi-collinear data sets the use of partial least square regression is recommended. PLSR makes full use of the rich spectral information while being relatively insensitive to sensor noise. PLSR provides a regression model where the entire spectral information is taken - in a weighted form - into account. This method seems therefore much better adapted to deal with potentially confounding factors compared to any 2-band vegetation index which can only avoid the most harmful factor of variation.     

Integrating landscape ecology and conservation physiology

The need to understand how anthropogenic landscape alteration affects fauna populations has never been more pressing. The importance of developing an understanding of the processes behind local extinction is widely acknowledged, but inference from spatial patterns of fauna distribution continues to dominate. However, this approach is limited in its ability to generate strong predictions about future distributions and local extinctions, especially when population-level responses to landscape alteration are subject to long time lags. We review the potential for indices of physiological stress and condition to contribute to understanding of how landscape pattern affects species persistence. Such measures can indicate habitat quality from the perspective of the individual animal, and can reveal environmental stressors before their negative consequences begin to manifest at a population level. Spatial patterns of chronic stress may therefore yield valuable insight into how landscape alteration influences species. We propose that the emerging disciplines of conservation physiology and macrophysiology have much to offer spatial ecology, and have great potential to reveal the physiological pathways through which habitat alteration affects fauna populations and their persistence in fragmented landscapes.     

Intra- and inter-provenance variability in phloem phenols of Picea abies and relationship to a bark beetle-associated fungus

One hundred Norway spruce (Picea abies (L.) Karst.) clones (three ramets per clone) were analyzed for phloem phenol composition and concentration before and 10 days after wound inoculation with sterile malt agar. Fifty clones (Experiment 1) belonged to the same provenance, whereas the remaining clones (Experiment 2) belonged to five provenances from three geographic areas. In Experiment 2, two additional ramets from the same clones were mass inoculated with Ceratocystis polonica (Siem.) C. Moreau to quantify the resistance of each clone. Tree response to wound inoculations was characterized by increased catechin concentration in both experiments, accompanied by increases in astringin and decreases in piceid in Experiment 1. In both experiments, we observed a diverse group of phenolic compounds whose concentrations increased (catechin, astringin) or did not vary (taxifolin glucoside) in response to wound inoculations, whereas concentrations of a homogeneous group of stilbene compounds decreased (piceid) or did not vary (isorhapontin, unidentified stilbene). In Experiment 2, provenances from the alpine and Hercynian-Carpatic areas differed from provenances from the Baltic area with respect to the relative importance of these two groups of compounds, further indicating that the two groupings of phenolic compounds structure the Norway spruce populations. Eighty days after mass inoculation, the percentage of healthy sapwood, which was taken as a measure of tree resistance, indicated that clones from the Baltic area were less resistant to mass inoculations than clones from the alpine and Hercynian-Carpatic areas. We conclude that the degree of resistance of Norway spruce trees to mass inoculations with a bark beetle-associated fungus can be predicted based on the diversity of constitutive phloem phenols and the ability to induce phenol synthesis in response to wounding.