Informatics Publishing Limited

L. Chitra Devi , Sushil Pandey , Anjali Kak , Veena Gupta

Abstract

Thespesia lampas Dalz. & Cibs is a wild medicinal shrub of India. The seeds of this species remain fresh and hard even after 60 days of viability test, suggesting the presence of seed coat dormancy/hard seededness. The tetrazolium test confirmed 100 % viability. This type of dormancy creates problems for the seed analysts while performing laboratory germination test and also during seed regeneration for germplasm managers and plant breeders. To determine the most suitable means of overcoming seed coat dormancy in T. lampas, seeds were exposed to various pre-treatments such as scarification in sand paper, hot water and sulphuric acid. Treated seeds were evaluated for their quality parameters to assess the impact of given treatments. The results revealed that soaking seeds in hot water at 75°C for 10 minutes was found to be most suitable treatment of enhancing germination. The present study provides means to overcome physical dormancy and enhance seed germination of this important medicinal species.

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L. Chitra Devi ¹, T. K. Singh ¹, R. Varatharajan ¹

Affiliations
1 Department of Life Sciences, Manipur University, Canchipur, Imphal 795 003, IN

Abstract

The role of natural enemies on the population of Lipaphis erysimi (Kalt.) infesting B. juncea var. rugosa (Linn.) has been studied in three consecutive crop seasons (1993-96). The study revealed the occurrence of about a dozen natural enemies belonging to four groups viz., syrphids, coccinellids, hemerobiid and aphidiid. Among these, syrphids were found to be dominant over the others in terms of density, species composition and prey consumption potential.

Keywords

Aphidiid, Coccinellids, Hemerobiid, Lipaphis erysimi, Natural Enemy, Syrphids.

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S.M. Hansa , L. Chitra Devi , G. N. K. Suresh Babu

Abstract

With the development and penetration of data mining within different fields and industries, many data mining algorithms have emerged. The selection of a good data mining algorithm to obtain the best result on a particular data set has become very important. What works well for a particular data set may not work well on another. The requirements for data mining systems for large organisation and enterprises range from logical and physical distribution of large data and heterogeneous computational resources to the general need for high performance at a level that is sufficient for interactive work. Data mining has many advantages across different industries. It allows large historical data to be used as the background for prediction. The interpretation and evaluation of the patterns obtained by data mining produces new knowledge that decision-makers can act upon. Data mining provides a means to obtain information that can support decision making and predict new business opportunities. For example, telecommunications, stock exchanges, and credit card and insurance companies use data mining to detect fraudulent use of their services; the medical industry uses data mining to predict the effectiveness of surgical procedures, medical tests, and medications; and retailers use data mining to assess the effectiveness of coupons and special events.

 

Keywords

Data mining, Prediction, Association Rules, Clustering

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