COMPUTED TOMOGRAPHY OF ASPIRATION PNEUMONIA IN A DOG

A dog with aspiration pneumonia was examined by computed tomography (CT) with 8-mm continuous scans of the chest. The results demonstrated that CT is a useful procedure for evaluating pneumonia, although high cost prevents its routine use. A normal littermate was examined, and normal structures of the chest and chest wall were compared.     

Comparison of chlorophyll fluorescence curves and texture analysis for automatic plant identification

With automatic plant identification methods, the amount of herbicides used in agriculture can be reduced when herbicides are sprayed only on weeds. In the present study, leaves of oat (Avena sativa) and dandelion (Taraxacum officinale, TAROF) were arranged so that there was overlap between the species, imaged with a pulse amplitude modulation fluorescence camera and photographed with a digital color camera. The fluorescence induction curves from each pixel were parameterized to obtain a set of features and from color photographs, texture features were calculated. A support vector algorithm that also performed feature selection was used for pattern recognition of both data sets. Fluorescence-based identification worked well with oat leaves, producing 92.2 % of correctly identified pixels, whereas the texture-based method often mis-identified the central vein of a TAROF leaf as oat, identifying correctly only 66.5 % of oat pixels. With TAROF that shows a clear dicot-type texture, the texture method was slightly better (96.4 % correctly identified pixels) than the fluorescence method (94.6 %). In fluorescence-based identification, the accuracy varied between entire TAROF leaves, probably reflecting the genetic variability of TAROF. The results suggest that the accuracy of identification could be improved by combining two identification methods.     

Automatic Plant Identification with Chlorophyll Fluorescence Fingerprinting

The development of precision farming needs methods for automatic identification of individual plant species. We have earlier shown that chlorophyll fluorescence induction curves can be reliably used for automatical identification of plants (Tyystjärvi et al., 1999). In the present study we show that a high accuracy of recognition can be obtained even if the teaching set for pattern recognition is collected several weeks before identifying a test batch of plants. It is also shown that very simple fluorescence traces can be used for the identification, and that dark pre-incubation of the plants can be shortened to a few seconds without seriously compromising the power of the method. The method is even more powerful if the aim is only to distinguish one crop species from weeds. The data shown here suggest that the fluorescence fingerprint can be developed to a method of practical importance for precision farming.     

Detection of dead or defoliated spruces using digital aerial data

The purpose of this study was to develop a method for detecting dead and defoliated spruces and defoliated stands in remote-sensing material using a semi-automatic pattern-recognition technique, spectral properties of trees, and different degrees of defoliation. The study material included two mapped defoliation stands in the municipality of Juupajoki (61°50′N, 24°18′E) in southern Finland. The ground truth data were collected during 1996–1997. The aerial color infrared (CIR) photographs, scaled to 1:5000, were taken on 28 June 1995 and on 19 June 1997. The degree of defoliation was visually estimated for every conifer in the defoliation stands. Individual trees in the digital aerial photographs were segmented using a robust segmentation method based on the recognition of tree crown patterns at a sub-pixel accuracy. The images were filtered with a Gaussian N×N smoothing operator, and local maxima above a threshold level were segmented using a directional derivate with some constraints. The segments were placed into defoliation classes using linear Fisher classification models, the parameters of which were estimated by cross-validation. Discriminant analysis was used to find variables for the segment classification. Defoliated tree segments and stands were classified satisfactorily. The accuracy of the pattern-recognition method proved adequate for detecting dead or heavily defoliated trees and heavily defoliated stands. The method described provides an interesting approach to using digital aerial data for automatically detecting severely defoliated spruce stands or individual trees.     

Inferring Reference Conditions of Hypolimnetic Oxygen for Deteriorated Lake Mallusj?rvi in the Cultural Landscape of Mallusjoki, Southern Finland Using Fossil Midge Assemblages

Lake Mallusjärvi in the cultural landscape of Mallusjoki, southern Finland, suffers from algal blooms during summers and oxygen depletions during winters due to increased nutrient input resulting from extensive agricultural activities in the catchment. In this study, a sediment profile from the lake was studied using fossil midge (Diptera: Nematocera) analysis and a hypolimnetic oxygen transfer function was applied to establish baseline conditions of hypolimnetic oxygen. In addition, physical properties of the sediment were determined. The inferred late winter hypolimnetic oxygen content was elevated in the beginning of the sediment sequence, but decreased dramatically at ca. 200 cal BP, as the inferred values indicated frequently anoxic condition coinciding with increased agricultural use in the catchment. The results indicated that dramatic changes have occurred in the taxon composition. The high-oxygen Stempellina?CAblabesmyia monilis-type community first changed to moderate-oxygen Procladius?CStempellinella community, and finally to low-oxygen Microchironomus tener?CChironomus plumosus-type community, following the eutrophication process. These changes in macrobenthic faunal assemblages reproduced considerably higher inferred hypolimnetic oxygen reference condition values for hypolimnetic oxygen, compared to the present status.     

Inhalation of organic dusts and lipopolysaccharide increases gelatinolytic matrix metalloproteinases (MMPs) in the lungs of heaves horses

We report the effects of mouldy hay/straw exposure, inhaled hay dust suspension (HDS) and inhaled lipopolysaccharide (LPS) on bronchoalveolar lavage fluid (BALF) gelatinolytic matrix metalloproteinase (MMP) levels and degree of activation in healthy (n = 6) and heaves- (previously termed chronic obstructive pulmonary disease) affected (n = 6 or 7) horses. Gelatinolytic MMPs in BALF were quantified by zymography, and gelatinases were shown by Western immunoblotting to be MMP-2 and MMP-9. Hay/straw and HDS challenges increased BALF total gelatinolytic activity only in heaves horses, with the majority of gelatinolytic activity comprising pro- and active MMP-9. The 5 h duration hay/straw challenge increased BALF gelatinolytic MMP activity in heaves horses at 5 and 24 h after the start of this challenge, with activity returning to baseline by Day 4. In contrast to hay/straw and HDS challenges, LPS inhalation increased BALF gelatinolytic MMP activity in both groups. For all challenges, absolute BALF neutrophil counts were highly significantly correlated (P<0.0001) with levels of proMMP-9 and active MMP-9, but not with levels of MMP-2 (P>0.05). As gelatinolytic MMPs are pro-inflammatory agents, they may contribute to lung dysfunction and tissue destruction in heaves horses exposed to airborne organic stable dusts.