Development of starch-based films reinforced with cellulosic nanocrystals and essential oil to extend the shelf life of red grapes

Packaging material has an important role in extending the shelf-life of fruits.This study investigated the effectiveness of cellulose nanocrystals(CNCs)derived from Kudzu(Pueraria montana)vine to reinforce to starch-based films.In addition,the essential oil was incorporated into these nanocomposite films to evaluate further improvement in film properties and applications.Different packaging materials,including the pearl millet starch(PMS),PMS reinforced with Kudzu CNCs,and PMS reinforced with Kudzu CNCs stabilized pickering emulsion containing clove bud oil(CBO),was used to develop biodegradable nanocomposite films.The films were investigated for their thermal,morphological,mechanical,and barrier properties.In addition,the films were used as packaging material to improve the shelf life of the grapes for 15 days at 5℃.PMS films reinforced with Kudzu CNCs stabilized pickering emulsion of CBO were most effective in extending the shelf life of red grapes up to 15 days at 5℃ by maintaining the weight,firmness,and soluble solids in grapes for a longer duration during storage.The study suggests that PMS+Kudzu CNCs+EO films have the potential for commercial packaging of fruits during short storage periods without adversely affecting their quality and sensory attributes.

Estimation model for electrical conductivity of red grape juice

The equations for predicting the electrical conductivities of red grape juice at different concentrations have been evaluated in this study.Three samples of red grape juice having concentrations of 10.5,12.5 and 14.5°Brix were ohmically heated by applying three different voltage gradients(10,12 and 15 V/cm)in the temperature range of 25-80℃.The mathematical models using multiple linear regression analysis indicated that electrical conductivity depended on temperature and concentration.The predictions of electrical conductivities using the mathematical models was found to be highly accurate with R2 value of 0.9975 when compared with the experimental data of red grape juice with concentration of 11.5°Brix.The reducing chi-square(χ^(2))and the root mean square error(RMSE)from the mathematical models were calculated and compared with the experimental data.As the results,multiple linear regressions on the coefficients of the mathematical model of electrical conductivity prediction have given highest values of the R2 and lowestχ^(2)and RMSE so the established model was confirmed as highly accurate when estimating electrical conductivities of red grape juice.

Grape size detection and online gradation based on machine vision

This research investigated the size detecting and online grading of Red Globe grapes using images of entire cases,rather than individual grapes.Method of ellipse fitting based on iterative least median squares was proposed and the process of grape grading includes the following four steps:stem removal from the RGB and NIR images collected by the 2-CCD camera;edge extraction by multiple methods of edge detection,image binarization,morphological processing,et al.;size determination of individual grapes by using image segmentation and ellipse fitting to calculate short axis length;Finally,grading based on the 15%downgrade principle,this means that if the case contains more than 15%of multiple grades,then the case is re-evaluated.Thirty-eight cases of Red Globe grapes were graded using these methods and 35 cases were correctly graded with an accuracy rate reaching 92.1%.The results showed that the accuracy and speed meet the requirements of grape automatic online detection.

Design and test of portable comprehensive quality non-destructive detector for grape bunches based on spectrum

Based on the analysis technology of visible/near infrared diffuse reflectance spectroscopy a portable and nondestructive detector was designed to test comprehensive quality of red globe grape bunches in the growth period.The detector included spectrum acquisition probe,spectrometer,lithium battery,halogen lamp light source,advanced RISC machines(ARM)board and peripheral circuit.Based on microsoft foundation classes(MFC)development tool,the real-time analysis and processing software of the detector was written by C++language.The optimal partial least squares regression(PLSR)detection model of multi-quality parameters was implanted into the hardware device.This paper selected the red globe grapes bunches in the growth period as the research samples,collected the visible/near infrared diffuse reflectance spectrum information,and then used the established PLSR model to detect the soluble solid content(SSC),total acid(TA)and pH of the samples to generate comprehensive quality parameter.So as to realize the nondestructive detecting of comprehensive quality of red globe grapes bunches in the growth period.In conclusion,the detector could realize real-time and non-destructive detecting of red globe grapes bunches in growth period aiming at the comprehensive quality.