RESULTS: Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities.
CONCLUSION: Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry.
RESULTS: Pineapple juice vinegar, which had the highest total phenolic acid content, also exhibited the greatest in vitro antioxidant capacity compared to coconut juice and nipah juice vinegars. Following acute and sub-chronic in vivo toxicity evaluation, no toxicity and mortality were evident and there were no significant differences in the serum biochemical profiles between mice administered the vinegars versus the control group. In the sub-chronic toxicity evaluation, the highest liver antioxidant levels were found in mice fed with pineapple juice vinegar, followed by coconut juice and nipah juice vinegars. However, compared to the pineapple juice and nipah juice vinegars, the mice fed with coconut juice vinegar, exhibited a higher population of CD4+ and CD8+ T-lymphocytes in the spleen, which was associated with greater levels of serum interleukin-2 and interferon-γ cytokines.
CONCLUSIONS: Overall, the data suggested that not all vinegar samples cause acute and sub-chronic toxicity in vivo. Moreover, the in vivo immunity and organ antioxidant levels were enhanced, to varying extents, by the phenolic acids present in the vinegars. The results obtained in this study provide appropriate guidelines for further in vivo bioactivity studies and pre-clinical assessments of vinegar consumption. © 2017 Society of Chemical Industry.
RESULTS: Results show that drying significantly (p
RESULTS: Sodium dodecyl sulfate-polyacrylamide gel electrophoresis fractionated raw snail extract to approximately 24 protein bands, between 9 and 245 kDa. The prominent band at 33 kDa was detected in all raw and processed snail extracts. Immunoblotting tests of the raw extract demonstrated 19 immunoglobulin E (IgE)-binding proteins, and four of them, at 30, 35, 42 and 49 kDa, were revealed as the major IgE-binding proteins of P. polita. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry identified the 49 and 42 kDa major allergens as actin, whereas the 30 and 35 kDa major allergens were identified as tropomyosin. Immunoblotting revealed that the raw snail had more allergenic proteins than the processed snail. The degree of allergenicity in decreasing order was raw > brine pickled> boiled > roasted > fried > vinegar pickled. The presence of cross-reactivity between P. polita and the shellfish tested was exhibited with either no, complete, or partial inhibitions.
CONCLUSION: Actin and tropomyosin were identified as the major and cross-reactive allergens of P. polita among local patients with snail allergy. Those major allergens are highly stable to high temperatures, acidic pH, and high salt, which might played a crucial role in snail allergy in Malaysia. © 2023 Society of Chemical Industry.
RESULTS: As pod developed, cacao exhibited a rise with the peak of flavonol occurring at months 4 and 5 after pod maturity was initiated while nitrogen balance showed a decreasing trend during maturity. Cacao pods contained high chlorophyll as they developed but chlorophyll content declined significantly on pods that ripened at month 5.
CONCLUSION: Cacao pods harvested at months 4 and 5 can be considered as commercially-ready as the beans have developed good quality and comply with the Malaysian standard on cacao bean specification. Thus, cacao pods can be harvested earlier when they reach maturity at month 4 after pod emergence to avoid germinated beans and over fermentation in ripe pods harvested at month 5. © 2018 Society of Chemical Industry.
RESULTS: In this research, chili pest and disease features extracted using the traditional approach were compared with features extracted using a deep-learning-based approach. A total of 974 chili leaf images were collected, which consisted of five types of diseases, two types of pest infestations, and a healthy type. Six traditional feature-based approaches and six deep-learning feature-based approaches were used to extract significant pests and disease features from the chili leaf images. The extracted features were fed into three machine learning classifiers, namely a support vector machine (SVM), a random forest (RF), and an artificial neural network (ANN) for the identification task. The results showed that deep learning feature-based approaches performed better than the traditional feature-based approaches. The best accuracy of 92.10% was obtained with the SVM classifier.
CONCLUSION: A deep-learning feature-based approach could capture the details and characteristics between different types of chili pests and diseases even though they possessed similar visual patterns and symptoms. © 2020 Society of Chemical Industry.
RESULTS: The relationship between dimensionless moisture content and shrinkage of sweet potato in terms of volume, surface area, perimeter and illuminated area was found to be linearly correlated. The results also demonstrated that the shrinkage of sweet potato based on computer vision and backscattered optical parameters is affected by the product thickness, drying temperature and drying time. A multilayer perceptron (MLP) artificial neural network with input layer containing three cells, two hidden layers (18 neurons), and five cells for output layer, was used to develop a model that can monitor, control and predict the shrinkage parameters and moisture content of sweet potato slices under different drying conditions. The developed ANN model satisfactorily predicted the shrinkage and dimensionless moisture content of sweet potato with correlation coefficient greater than 0.95.
CONCLUSION: Combined computer vision, laser light backscattering imaging and artificial neural network can be used as a non-destructive, rapid and easily adaptable technique for in-line monitoring, predicting and controlling the shrinkage and moisture changes of food and agricultural crops during drying. © 2017 Society of Chemical Industry.