Supervised hybrid feature selection based on PSO and rough sets for medical diagnosis.

Medical datasets are often classified by a large number of disease measurements and a relatively small number of patient records. All these measurements (features) are not important or irrelevant/noisy. These features may be especially harmful in the case of relatively small training sets, where this irrelevancy and redundancy is harder to evaluate. On the other hand, this extreme number of features carries the problem of memory usage in order to represent the dataset. Feature Selection (FS) is a solution that involves finding a subset of prominent features to improve predictive accuracy and to remove the redundant features. Thus, the learning model receives a concise structure without forfeiting the predictive accuracy built by using only the selected prominent features. Therefore, nowadays, FS is an essential part of knowledge discovery. In this study, new supervised feature selection methods based on hybridization of Particle Swarm Optimization (PSO), PSO based Relative Reduct (PSO-RR) and PSO based Quick Reduct (PSO-QR) are presented for the diseases diagnosis. The experimental result on several standard medical datasets proves the efficiency of the proposed technique as well as enhancements over the existing feature selection techniques.

Management of root lesion nematode, Pratylenchus delattrei in crossandra using oil cakes.

Selected oil cakes, neem, castor and mahua, were tried independently and in combination with a chemical nematicide (carbofuran 3G) for the management of Pratylenchus delattrei in crossandra under glass house conditions. The neem oil cake was effective compared to other oil cakes used and there was a synergistic effect when the neemcake was coupled with carbofuran 3G in the management of Pratylenchus delattrei. The treatment resulted in better establishment of seedlings, and with increased plant bio-mass and flower yield.

Management of root-knot nematode in tomato Lycopersicon esculentum, Mill, with biogas slurry.

The effect of biogas slurry application on the severity of root-knot nematode, Meloidogyne incognita, attack on tomato cv. Co-1, was tested in the green house with two levels of biogas slurry: 5% and 10% (w/w) added to soil. Both the number (3 fruits/plant) and fruit yield (35.2 g/plant) of tomato increased significantly with 10% (w/w) biogas slurry. The plants amended with biogas slurry put up more vegetative growth and tended to flower and fruit much earlier than did those of the control. The nematode population in the soil decreased thus decreasing the severity of nematode attack.