Enhancing molecular screening of hidden insect infestation in rice grains by COI barcoding
The hidden insect infestation in rice grains poses a significant challenge to both producers and consumers across the globe and has far-reaching implications for food security, economic stability, and public health. Two genetically close insect species - Sitophilus oryzae and Sitophilus zeamais – commonly known as rice weevils, have long plagued rice storage facilities, leading to substantial economic losses and food quality degradation. Both weevils are particularly adapted to attack rice grains and spend a considerable part of their life cycle, including the entire larval feeding period, inside them. They do this by creating an entrance hole, covering it after entry, and then, after the pupation process an exit hole is created, from which it then emerges.
These insects constitute the hidden infestation that visual inspection cannot successfully detect, and traditional techniques such as measuring produced carbon dioxide (CO2), ninhydrin method, grain flotation, X-ray images, and acoustic sound patterns, according to ISO 6639-4 of 1987, have proven inadequate in providing the required specificity and sensitivity for precise identification of these insidious insect infestations.
To address this pressing issue, this work focused on developing a specific and fast molecular detection method, such as a multiplex real-time polymerase chain reaction (RT-PCR). Firstly, adopting a deoxyribonucleic acid (DNA) barcoding approach, by using a standardized region of insect genomes, the cytochrome oxidase I (COI) gene, as the foundation for species-specific primer and probe design, and testing them for their efficiency in amplifying the target DNA. Secondly, an assay to determine the limit of detection of the RT-PCR was done, which is a critical parameter for the implementation of this technique as a quality control method in food processing and pest management in storage facilities. By doing so, this work offers a comprehensive framework for stakeholders seeking the most effective means to detect, monitor, and combat hidden insect infestation in rice grains.
