OZONE TREATMENT FOR IMPROVING QUALITY PARAMETERS AND SURFACE DISINFECTION OF CUCUMBER

Abstract

The consumption of fresh horticultural crops represents a pivotal aspect of human diets across cultures and continents. Cucumbers (Cucumis sativus L.) have high water content, making them incredibly hydrating. The use of pesticides in traditional farming makes cucumber poisonous. Furthermore, cucumbers may sometimes be contaminated with bacteria, parasites, or viruses, leading to foodborne illnesses. Washing with tap water is not highly effective in removing pesticide residue or microbial contamination. Ozone technology, an emerging non- thermal processing method, proves highly effective in disinfecting food products. It holds significant potential for improving the shelf life of the produce. Ozone process parameters such as ozone concentration (%) and treatment time (minutes) were separately optimized for two groups of pesticides such as chlorpyrifos (organophosphate) and deltamethrin (pyrethroid). The optimized condition for maximum chlorpyrifos degradation in cucumber was found to be 100% ozone concentration and 10 minutes of treatment time. For maximum degradation of deltamethrin in cucumber sample, the optimum ozone concentration and treatment time were found to be 100% and 30 minutes, respectively. In addition, the optimized samples were packed in polyethylene bags and cling film and was stored in room temperature and refrigerated storage for shelf-life analysis. During the storage period quality parameters such as firmness, color, Ascorbic acid, DPPH scavenging activity, Moisture loss, weight loss and TSS were analyzed every 5 days of storage The optimized sample (Maximum chlorpyrifos degradation) in poly ethylene package under refrigerated condition experienced were acceptable till 30th day of storage with better quality attributes. Thus, aqueous ozone treatment retained all the quality parameters of cucumber along with a significant reduction in the pesticide degradation and the count of surface microorganisms. Furthermore, Near infrared technology were used to predict the nutritional components of cucumber such as carbohydrate, Protein, fat, ash and moisture content. The result showed that NIRS can predict the nutritional components of cucumber accurately (R2= 0.86- 0.97).