Informatics Publishing Limited

Seema Jaggi , A. S. Gill , Cini Varghese , V. K. Sharma , N. P. Singh

Abstract

Fodder trees in agro-forestry system are planted to overcome the effects of the seasonal shortages or to insure against risks of drought and also to deliver benefits such as shelter, soil conservation, timber and fuel wood. An attempt was made to investigate the performance of fodder trees in the presence and absence of crops. The data pertaining to growth parameters and biomass parameters of the four fodder trees from an agro-forestry experiment for six years (1999-2005) was analyzed. Contrast analysis has been performed to study the performance of the different tree species with and without crops. The combined analysis of the tree data over the years was also performed.

Keywords

Fodder Trees, Crops, Agro-forestry, Contrast Analysis, Combined Analysis

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Arfa Anjum ¹, Seema Jaggi ², Shwetank Lall ³, Eldho Varghese ⁴, Anil Rai ¹, Arpan Bhowmik ³, Dwijesh Chandra Mishra ¹

Affiliations
1 Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, IN
2 Agricultural Education Division,ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, IN
3 Division of Design of Experiments, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, IN
4 Fishery Resources Assessment Division, ICAR-Central Marine Fisheries Research Institute, Kochi 682 018, IN

Abstract

The field of whole genomic studies and investigations is currently focused on change-point detection. Over time, various segmentation techniques have been pro­posed to identify these change points. To effectively locate segments within a genome, it is helpful to pinpoint the intervals or boundaries between them, which are known as change points. By treating these change points as outliers, they can be identified. The anomalies or outliers in a dataset are the observations which are significantly different from the rest of the observations. They can be attributed to some measurement errors or properties of the data themselves. Studying the fluctuations over different segments also revealed the heterogeneity bet­ween consecutive segments. In this paper, anomaly identification approach or influential point detection has been discussed and studied in cow genome data of chromosome 25. Furthermore, the observed anomalies have been confirmed to determine whether or not they are true change points. The two-step technique resulted in the identification of change sites based on observed abnormalities and is efficient in terms of calculation time and cost. This study aims to detect any anomalies in genomic data and determine the exact points at which the data segment significantly differed from the rest of the segments. We have developed relevant R codes for data processing and applied methodologies.

Keywords

Anomalies, change points, genomic sequences, segmentation, two-step procedure

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