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The present study aims at the extension of shelf life of Jasmine flowers (Jasminum multiforum L.) which are extremely perishable in nature. Flowers were treated with different chemical treatment combinations and observed at ambient condition for 5 days. The effect of chemical treatment and packaging material on the physiological loss in weight, freshness index, flower opening index, total phenol content and respiration rate was evaluated. The optimization was carried out in design expert software with multi-level categoric design having 100 runs. The flowers treated with (Sucrose 20 % + GA3 (100ppm) + Boric acid-2%) packed in polypropylene bags of 200 gauge without ventilation were effective in extending shelf life up-to 130 hours (5.40 days) with minimum physiological loss in weight of 31.3%, higher freshness index of 59.5, lower respiration rate of 5.49 ml-Co2/kg-h and lower total phenol content of 10.33 mg/g at the end of 5 days. [ABSTRACT FROM AUTHOR]

Rice ageing is a complicated process that is difficult to examine methodically. Several physicochemical properties of rice change with age as a function of moisture content and storage temperature. Among these qualities, amylose content is the most important and numerous metrics depend on it. Several sensors, Internet of Things, Information and Communication Technology, artificial intelligence and machine learning (ML) approaches are being used in technological interventions to tackle this problem. In the present study, seven advanced ML models were evaluated to classify the different concentrations of amylose using light-intensity data obtained by the novel colorimetric amylose sensor. From the performance of the evaluated ML models, it was observed that for the light intensity dataset obtained from the sensor, higher and similar model parameters and an accuracy value of 0.77 were observed for both artificial neural network (ANN) and k-nearest neighbour (KNN) algorithms, followed by accuracy values of 0.75, 0.74, 0.65, 0.61 and 0.61 respectively, for the decision tree, random forest, AdaBoost, logistic regression and support vector machine algorithms. Thus ANN and KNN are promising in predicting the different classes of amylose in rice. [ABSTRACT FROM AUTHOR]

The bi-products of rice and pulse industries were utilised for development of rice analogues as value added products. Analogues rice was produced by converting the broken rice and pigeonpea dhal into flour along with water and sodium alginate as binding agent in the cold extrusion process. The analogue rice resembling the raw rice were extruded by varying two process variables viz., broken pigeonpea dhal flour (BPDF) (20, 30 and 40%) and moisture content (25, 30 and 35%). The optimisation was carried out for arriving at the combinations for composite flour for producing the rice analogues resembling raw rice enriched with protein content using design expert software. The optimisation process established highest desirability of 0.855 for 30% BPDF and 30% moisture content. The optimum combination had highest crude protein, carbohydrate, ash contents of 12.73, 71.72 and 0.990%, respectively. The colour values L*, a* and b* were found to be 69.30, 4.62 and 26.31, respectively. The pasting temperature and peak viscosity were 77.65oC and 23173.3 cP. [ABSTRACT FROM AUTHOR]

A simple and sensitive ultra high-performance liquid chromatography with fluorescence detector based analytical method was developed for the separation and quantification of aflatoxin isomers residues in red chilli samples. The separation was performed on purospher STAR RP 18e column with an optimised solvent system consisting of 0.2% acetic acid in water and 1:1 methanol and acetonitrile. The response of detector was linear with correlation coefficient >0.99 and limit of quantification was 2 µg kg-1. Calibration curves were linear in the concentration range of 2-50 ng mL-1. A satisfactory RSDr and recoveries were in the range of 0.1-4.2% and 82.9-114.7%, respectively. The validated method was applied to quantify aflatoxin isomers residues in 48 red chilli and red chilli powder samples collected from the farmers' field, cold storage and local market. The study revealed that, the AFG1 and AFG2 were not detected in the collected samples and the red chilli powder samples collected from local market showed the presence of AFB2 in 2 samples which was below the quantification limit (<1 µg kg-1). Whereas, the contamination of AFB1 was detected in 5 and 19 samples out of 22 field collected red chillies and 23 local market collected red chilli powder, respectively. However, none of the cold storage collected samples shown the presence of AFB1. This method could be used for monitoring of four different isomers of aflatoxin in different agricultural and horticultural produce. [ABSTRACT FROM AUTHOR]