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Nidoni, Udaykumar
- Therapeutic Properties Of Ocimum Santum linn. ( Tulsi)
Abstract Views :283 |
PDF Views:0
Authors
Affiliations
1 Department of Processing and Food Engineering, College of Agricultural Engineering,University of Agricultural Sciences, Raichur Karnataka, IN
1 Department of Processing and Food Engineering, College of Agricultural Engineering,University of Agricultural Sciences, Raichur Karnataka, IN
Source
International Journal of Processing and Post harvest Technology, Vol 5, No 1 (2014), Pagination: 99-104Abstract
Ocimum sanctum popularly known as Tulsi and called Holy Basil in English. It is ranked among the few wonder herbs, which has a versatile role in traditional systems of medicine. Several studies are being conducted regarding the efficacy of whole plant or its parts for treatment of different diseases and ailments. The active compound of the plant includes eugenol, ursolic acid, phenolic compounds, flavonoids etc. The health promoting and disease preventing properties such as antimicrobial, antioxidant, heptaproctetive, radio-protective, antistress, antiinflammatory, antidiabetic, antifertility, neuroprotective, antiulcer, cardio-protective, anticancer, anticarcinogenic, immunomodulatory and mosquito repellent properties have been described. These benefits have been investigated and verified by modern scientific research. The various aspects of therapeutic properties of Ocimum sanctum have been discussed in the present paper.Keywords
Anticarcinogenic, Antidiabetic, Eugenol, Ocimum Sanctum, Therapeutic Properties
- Drying Characteristics of Bijapur White Onion (Allium cepa L.) Using Solar Tunnel Dryer
Abstract Views :325 |
PDF Views:0
Authors
Affiliations
1 Department of Processing and Food Engineering, College of Agricultural Engineering, University of Agricultural Sciences, Raichur (Karnataka), IN
1 Department of Processing and Food Engineering, College of Agricultural Engineering, University of Agricultural Sciences, Raichur (Karnataka), IN
Source
International Journal of Processing and Post harvest Technology, Vol 6, No 1 (2015), Pagination: 87-92Abstract
Fresh Bijapur white onion (Allium cepa L.) were treated with 10 per cent NaCl for 1 h, 0.2 per cent KMS for 15 min and 10 per cent NaCl + 0.2 per cent KMS for 15 min and dried in solar tunnel dryer (STD) and open yard sun drying (OYSD). A comparative study was conducted to evaluate two drying methods with respect to temperature and time combinations. The sample of Bijapur white onion required 18 to 21 h to dry under open yardsun drying and 16 to 18h in solar tunnel drier to bring down initial moisture content ranging from 599.30-774.13 per cent (d.b.) to final moisture content of 4.56-5.25 per cent (d.b.). Drying took place in the falling rate period and the Midilli and kocuck model was found to be the best fit to describe the drying behaviour of Bijapur white onion.Keywords
Bijapur White, STD and OYSD, Pre-Treatment, Drying, Drying Models.- Development and Evaluation of Pearl Millet Based Novel Health Drink
Abstract Views :279 |
PDF Views:2
Authors
Affiliations
1 University of Agricultural Sciences, Raichur, Karnataka - 584 133, IN
1 University of Agricultural Sciences, Raichur, Karnataka - 584 133, IN
Source
The Indian Journal of Nutrition and Dietetics, Vol 53, No 4 (2016), Pagination: 468-474Abstract
Malnutrition in general and nutritional anaemia in particular is a public health problem in India. The remedies for which lies with the people if they are educated to utilize the locally available nutrient rich food sources. In this background, an effort was made to develop a novel food product from bajra, an iron rich health drink as a supplementary food to combat malnutrition. Bajra or pearl millet is extensively grown in Raichur district, which is a rich source of iron, Ca, Zn and high level of fat. But its uses are limited. Novel health drink was prepared using sprouted and dried pearl millet flour, sprouted and dried finger millet powder, malted soya flour, sugar powder and milk powder, and popped and milled amaranth seed powder in different combinations. The pearl millet flour was fortified with other ingredients used in different combinations i.e., 50, 60,70 and 80% respectively along with other ingredients and 100% pearl millet flour was used as control. The effect of germination on nutritional composition in terms of proximate was assessed and sensory evaluation was done for all the fortified samples using 9 point hedonic scale. Sensory evaluation of fortified samples showed that 50 per cent bajra concentration sample was the most accepted sample with respect to all the qualities followed by 60%. Germination enhanced the protein and minerals especially iron content with the reduction in fat.Keywords
Pearl Millet, Germination, Sprouting, Health Food, Sensory Evaluation.References
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- Performance of Advanced Machine Learning Models in the Prediction of Amylose Content in Rice Using Internet of Things-Based Colorimetric Sensor
Abstract Views :123 |
PDF Views:70
Authors
Shrinivas Deshpande
1,
Udaykumar Nidoni
2,
Sharanagouda Hiregoudar
2,
K. T. Ramappa
2,
Devanand Maski
3,
Nagaraj Naik
4
Affiliations
1 ICAR-Krishi Vigyan Kendra, Kandali, Hassan 573 217, IN
2 Department of Processing and Food Engineering, College of Agricultural Engineering, University of Agricultural Sciences, Raichur 584 104, IN
3 Department of Renewable Energy Engineering, College of Agricultural Engineering, University of Agricultural Sciences, Raichur 584 104, IN
4 Pesticide Residue and Food Quality Analysis Laboratory, College of Agricultural Engineering, University of Agricultural Sciences, Raichur 584 104, IN
1 ICAR-Krishi Vigyan Kendra, Kandali, Hassan 573 217, IN
2 Department of Processing and Food Engineering, College of Agricultural Engineering, University of Agricultural Sciences, Raichur 584 104, IN
3 Department of Renewable Energy Engineering, College of Agricultural Engineering, University of Agricultural Sciences, Raichur 584 104, IN
4 Pesticide Residue and Food Quality Analysis Laboratory, College of Agricultural Engineering, University of Agricultural Sciences, Raichur 584 104, IN
Source
Current Science, Vol 124, No 6 (2023), Pagination: 722-730Abstract
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.Keywords
Amylose Content, Artificial Intelligence, Machine Learning, Mathematical Modelling, Rice.Full Text
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