COMPARISON OF ELISA AND RT-PCR FOR THE DETECTION OF PEANUT BUD NECROSIS VIRUS IN ONION (ALLIUM CEPA.L)

ABSTRACT: Peanut bud necrosis virus (PBNV) is an important re-emerging viral pathogen in onion (Allium cepa L.) in India. The virus transmitted by thrips vectors; it belongs to the genus Tospovirus and family Bunyaviridae. The onion crop infected by PBNV and it is a major problem in Southern India. This paper presents the comparison of DAC-ELISA and RT-PCR in the detection of PBNV infected onion samples from South India. The PBNV suspected onion samples (n=145) were collected in the major growing areas of Andhra Pradesh, Tamil Nadu and Karnataka states from South India. Among these collected onion samples, Seventy five samples (51.72%) were confirmed as PBNV infected by DAC-ELISA using the PBNV specific antiserum and in RT-PCR method one hundred twenty four samples (85.51%) were amplified (~800bp) by using the PBNV-CP gene specific primers. In comparison studies the RT-PCR method has added the advantage that it is more sensitive than the DAC-ELISA in the detection of PBNV in onion

OVERVIEW OF MULTIMODAL BIOMETRICS

ABSTRACT Confidentiality is very important for every organization. Now a days, Biometric technologies have became a foundation for identification and personal verification. Biometric refers to technologies that measure and analyze the physiological characteristics of a human body for verification or identification. Most Biometrics are unimodal, Which rely on single source of information for authentication. But these systems are facing variety of problems such as Noise in sensed data, Non-universality, Spoof attacks, Distinctiveness. To overcome these drawbacks a new research area multimodal biometrics is emerged. Multimodal biometric systems consist of combining two or more biometric modalities in a single identification system. As multimodal biometric systems depend on multiple sources of information, these are categorized into six classes like Multi sensor systems, Multi algorithm systems, Multi instance systems, Multi sample systems, Multi modal systems and Hybrid systems. The various levels of fusion are also discussed in this paper