Seed storage proteins comprise a major part of the protein content of the seed and have an important role on the quality of the seed. These storage proteins are important because they determine the total protein content and have an effect on the nutritional quality and functional properties for food processing. Transgenic plants are being used to develop improved lines for incorporation into plant breeding programs and the nutrient composition of seeds is a major target of molecular breeding programs. Hence, classification of these proteins is crucial for the development of superior varieties with improved nutritional quality. In this study we have applied machine learning algorithms for classification of seed storage proteins. We have presented an algorithm based on nearest neighbor approach for classification of seed storage proteins and compared its performance with decision tree J48, multilayer perceptron neural (MLP) network and support vector machine (SVM) libSVM. The model based on our algorithm has been able to give higher classification accuracy in comparison to the other methods.can be hydrolyzed to release its constituent amino acids. These acids are used as a source for reduced nitrogen by the seedling which is essential for germination and early growth of seedling (Spencer and Boulter 1984). Humans and livestock obtain a major fraction of the total protein from the seeds of crop plants. Composition of storage proteins determines the quality of proteins which is very important from the nutritional aspect. For instance, high quality cereals are characterized by the quality of proteins of the grains which are yet determined by the composition of proteins. These storage proteins determine not only the total protein content of the seed but also its quality for various end uses. In cereals, about 50 % of the total protein in mature grains is comprised of storage proteins and thus have an important role on nutritional quality for humans and livestock and on functional properties in food processing (Shewry and Halford 2002). In the case of wheat, the storage proteins from the gluten fraction are important, whose properties are largely responsible for the ability to use wheat flour to make bread and other products (Shewry and Halford 2002). Osborne (1924) classified the storage proteins into groups on the basis of their extraction and solubility in water (albumins), dilute saline (globulins), alcohol ether mixtures (prolamins), and dilute acid or alkali (glutelins).A detailed understanding of storage protein structure and diversity is an important prerequisite for attempts to manipulate quality because it indicates the extent to which the composition of the proteins can be maneuvered without affecting their biological properties (Shewry and Halford 2002). Transgenic plants are being used to develop improved lines for incorporation into plant breeding programs. Improving the nutrient composition of seeds is a major target of molecular breeding and much of the recent work on seed storage proteins was ...

Conductance of quinolinium dichromate has been measured in water and N,N-dimethyl formamide mixtures over the complete compositional range. The limiting molar conductance Λo and the association constant of the ion pair, K A, have been computed using the Shedlovsky equation. Λo increases with an increase in the proportion of water in the solvent mixture. The Kraus−Bray equation has also been used to correlate the limiting molar conductance data, and the dissociation constant of the ion pair, K C, has been computed. The results have been discussed in terms of ion−solvent interactions.

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The electrical conductance of nicoitinium dichromate has been measured in water-N,Ndimethyl formamide mixtures of different compositions in the temperature range 283-313 K. The limiting molar conductance, o and the association constant of the ion-pair, KA have been calculated using Shedlovsky equation. The effective ionic radii (ri) of (C6H6O2) + and (C6H6O2NCr2O7)-ions have been determined from i o values using Gill's modification of the Stokes law. The influence of the mixed solvent composition on the solvation of ions has been discussed with the help of 'R'-factor. Thermodynamic parameters are evaluated and reported. The results of the study have been interpreted in terms of ion-solvent interactions and solvent properties.