Huge livestock population of India is under threat by a large number of endemic infectious (bacterial, viral, and parasitic) diseases. These diseases are associated with high rates of morbidity and mortality, particularly in exotic and crossbred cattle. Beside morbidity and mortality, economic losses by these diseases occur through reduced fertility, production losses, etc. Some of the major infectious diseases which have great economic impact on Indian dairy industries are tuberculosis (TB), Johne’s disease (JD), mastitis, tick and tick-borne diseases (TTBDs), foot and mouth disease, etc. The development of effective strategies for the assessment and control of infectious diseases requires a better understanding of pathogen biology, host immune response, and diseases pathogenesis as well as the identification of the associated biomarkers. Indigenous cattle (Bos indicus) are reported to be comparatively less affected than exotic and crossbred cattle. However, genetic basis of resistance in indigenous cattle is not well documented. The association studies of few of the genes associated with various diseases, namely, solute carrier family 11 member 1, Toll-like receptors 1, with TB; Caspase associated recruitment domain 15, SP110 with JD; CACNA2D1, CD14 with mastitis and interferon gamma, BoLA-DRB3.2 alleles with TTBDs, etc., are presented. Breeding for genetic resistance is one of the promising ways to control the infectious diseases. High host resistance is the most important method for controlling such diseases, but till today no breed is total immune. Therefore, work may be undertaken under the hypothesis that the different susceptibility to these diseases are exhibited by indigenous and crossbred cattle is due to breed-specific differences in the dealing of infected cells with other immune cells, which ultimately influence the immune response responded against infections. Achieving maximum resistance to these diseases is the ultimate goal, is technically possible to achieve, and is permanent. Progress could be enhanced through introgression of resistance genes to breeds with low resistance. The quest for knowledge of the genetic basis for infectious diseases in indigenous livestock is strongly warranted.
First lactation records of 3068 Mehsana buffaloes sired by 118 sires, under field progeny testing programme distributed in different 149 villages of 14 talukas maintained at Dudhsagar Research and Development Association, Dudhsagar Dairy, Mehsana over a period of 24 years (1989-2012) were used to estimate least squares means and heritability of fertility traits like, first service period (FSP), first calving interval (FCI) and daughter pregnancy rate (DPR). The least squares means of these traits were found to be 189.05±3.34 days, 472.97±2.87 days and 31.08±0.59%, respectively. Non genetic factors such as age at first calving and period of calving were found to have highly significant effect on all the traits, whereas, cluster found to be non-significant for FSP and significant for FCI and DPR. Heritability were estimated for FSP, FCI and DPR as 0.02±0.02, 0.004±0.015 and 0.095±0.031; 0.04±0.03, 0.026±0.024 and 0.089±0.032; and 0.01±0.02, 0.032±0.026 and 0.095±0.034 by LSML, BLUP-SM and BLUP-AM, respectively. BLUP-AM was found to be the best model for heritability estimation based on error variance and BLUP-AM gave highly significant and more accurate results than BLUP-SM and LSML in Mehsana buffaloes.
Rabbit rearing across the Indian subcontinent is growing rapidly. Growth traits are important parameters on which rabbits are being evaluated. Mathematical models have been tried to establish a relationship between body weight and time. Data spread over six years on the weekly body weight of Soviet Chinchilla and White Giant rabbits were collected and subjected to analysis for assessment of genetic parameters and factors which influence the weekly body weight. Three nonlinear growth models; Gompertz, Logistic, and Von Bertalanffy were fitted for both the breeds separately as well as collectively. The least squares mean for weekly body weights in rabbits from weaning to maturity showed an increasing trend. White Giant rabbits weigh higher than Soviet Chinchilla. The period and season of kindling had a significant influence on the weekly body weight of rabbits. The value of growth curve parameter k (an indicator of growth performance) was estimated to be higher for White Giant by all three models. All three models performed well with a high coefficient of determination values. However, Von Bertalanffy model fitted well for Soviet Chinchilla and Gompertz model for the White Giant as well as when both the breeds were fitted collectively.
Cloud computing is a novel pattern of computing where resources are provisioned on demand over the Internet. Being pay-as-yougo model, Cloud users lease the required resources and pay for their usage. Services offered by Cloud are broadly divided into three categories: Infrastructure-as-a-Service (IaaS), Platform-as-aService (PaaS) and Software-as-a-Service (SaaS). IaaS provides computing resources such as servers, storage, and other form of low level network and hardware resources. One of the widely used services of Cloud viz. Storage as a Service, falls under IaaS. It provides online storage space to users to store their data. But due to lack of (physical) control over their data, users' worry about security and privacy is apparent. Cryptographic algorithms are evident answers to this problem. But while utilizing traditional cryptographic primitives for data stored on Cloud, issues such as computation cost of algorithm, level of security offered by them, sensitivity of data etc. need to be taken into considerations. This paper aims to address the tradeoffs between these issues and intends to provide guidelines to Cloud users about best security options based on significance of their data.
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