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您的检索式：作者名="ASIMA SHAH"
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| 1 | Development of potato starch based active packaging films loaded with antioxidants and its effect on shelf life of beet显示文摘 | INAM U NISA BILAL AHMAD ASHWAR ASIMA SHAH | 2015 | J Food Sci Technol2015，52，11： | 1 |
| 2 | Extraction of protein from churpi of yak milk origin:Size reduction,nutraceutical potential and as a wall material for resveratrol显示文摘Resveratrol is a known anti-oxidant and anti-cancer bioactive.The low bioavailability and poor water solubility of resveratrol is a major barrier that restricts its usage in food applications.To overcome these problems,the study presents micro and nano encapsulation of resveratrol in casein micelles extracted from Himalayan cheese(Churpi).Resveratrol loaded casein microparticles(CS-rm)were obtained using emulsion-freeze drying.Whereas,resveratrol loaded casein nanoparticles(CS-rn)were obtained using ultrasonication.Both were characterized using dynamic light scattering(DLS),scanning electron microscopy(SEM)and attenuated total reflectance-fourier transform infrared spectroscopy(ATR-FTIR).DLS revealed hydrodynamic diameter of 71.24μm and 387.023 nm and zeta potential of-22.62 and-28.08 mV for CS-rm and CS-rn.FTIR confirmed the characteristic peaks of resveratrol at 965.4,1380.86,1586.66 and 1607 cm-1 confirmed successful micro and nanoencapsulation.CS-rm displayed high encapsulation efficiency(52.32%)and swelling power(77.90 at pH 3 and 68.65 at pH 7.5)than CS-rn.Both micro and nanoencapsulation protected resveratrol in gastric conditions,however,CS-rn showed high release of resveratrol then CS-rm in simulated intestinal conditions.The anti-oxidant and anti-cancer activity of resveratrol under simulated gastric and intestinal conditions(SGID)was significantly higher(p≤0.05)for CS-rn,showing that nanoencapsulation improved release and nutraceutical profile of resveratrol.Resveratrol loaded nano and micro casein particles can be used a source of fortified protein supplement in growing food and nutraceutical industry. | Asir Gani Nairah Noor Adil Gani Jenno Joseph-Leenose-Helen Asima Shah Zanoor ul Ashraf | 2022 | Food Bioscience2022，46，2： | 0 |
| 3 | Deep Learning-Based Classification of Fruit Diseases:An Application for Precision Agriculture显示文摘Agriculture is essential for the economy and plant disease must be minimized.Early recognition of problems is important,but the manual inspection is slow,error-prone,and has high manpower and time requirements.Artificial intelligence can be used to extract fruit color,shape,or texture data,thus aiding the detection of infections.Recently,the convolutional neural network(CNN)techniques show a massive success for image classification tasks.CNN extracts more detailed features and can work efficiently with large datasets.In this work,we used a combined deep neural network and contour feature-based approach to classify fruits and their diseases.A fine-tuned,pretrained deep learning model(VGG19)was retrained using a plant dataset,from which useful features were extracted.Next,contour features were extracted using pyramid histogram of oriented gradient(PHOG)and combined with the deep features using serial based approach.During the fusion process,a few pieces of redundant information were added in the form of features.Then,a“relevance-based”optimization technique was used to select the best features from the fused vector for the final classifications.With the use of multiple classifiers,an accuracy of up to 99.6%was achieved on the proposed method,which is superior to previous techniques.Moreover,our approach is useful for 5G technology,cloud computing,and the Internet of Things(IoT). | Inzamam Mashood Nasir Asima Bibi Jamal Hussain Shah Muhammad Attique Khan Muhammad Sharif Khalid Iqbal Yunyoung Nam Seifedine Kadry | 2021 | Computers, Materials & Continua2021，，2： | 0 |
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