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).
