Agriculture products

2007 ◽  
pp. 48-53
Keyword(s):  
Agriculture Products

Community Development and Role of Tourism: A Case Study of Tourist Destination Manali in Himachal Pradesh (India)

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Sunil
Keyword(s):  
Traffic Congestion ◽  
Local Community ◽  
Negative Impact ◽  
Himachal Pradesh ◽  
Tourism Industry ◽  
Cultural Development ◽  
Infrastructure Development ◽  
Tourism Sector ◽  
The Government ◽  
Agriculture Products

Tourism sector has a significant role in the economic development of our country. Tourism sector has contributed 6.88 percent to the GDP and has 12.36 percent share in employment (direct and indirect) in the year 2014. It has also a significant share in foreign exchange earnings. The benefit of tourism mostly goes to the local community (Sonya & Jacqueline, Mansour E. Zaei & Mahin E. Zaei, 2013). In this paper, an attempt has been made to assess how the tourism industry has created an opportunity for the economic, political, social and cultural development of the local community at Manali in Himachal Pradesh (India) and also tried to study the problems that are associated with the tourism in the region. The study found that the tourism industry has been extending its contribution for the development of local community at Manali. It has been providing employment, business and investment opportunities, revenue generation for the government, encouraging the community to promote and preserve its art, culture and heritage, raising the demand of agriculture products, provided opportunities for local people to run and work in the transport business and by promoting MSMEs in the region. Besides the opportunities, the tourism industry has also added many problems to the local community. Traffic congestion, increase in water and air pollution, solid waste generation, degradation of the cultural heritage, ecological imbalances, rise in cost of living, increase in crime, noise and environment pollution, migration of people to the region, negative impact on local culture, and extra pressure on civic services during the tourists season, are the problems associated with the tourism. The study suggest that effective management of natural resources, dissemination of environment protection information, involvement of local community in decision making, professionalization in the working of local administration, extending the support of government in sponsoring the events, infrastructure development, tracking records of migrants with the help of local community to curb the crime rate, promotion and preservation of art, culture and heritage, involvement of NGOs, compliance of the rules can make tourism more beneficial in the development of local community.

Prediction of Future Market Price for Agricultural Commodities

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Sagar Pathane ◽  
Uttam Patil ◽  
Nandini Sidnal
Keyword(s):  
Mobile Application ◽  
Market Price ◽  
Commodity Prices ◽  
Future Price ◽  
Future Market ◽  
Graphical Interface ◽  
Agricultural Commodities ◽  
Agricultural Commodity ◽  
Web Based ◽  
Agriculture Products

The agricultural commodity prices have a volatile nature which may increase or decrease inconsistently causing an adverse effect on the economy. The work carried out here for predicting prices of agricultural commodities is useful for the farmers because of which they can sow appropriate crop depending on its future price. Agriculture products have seasonal rates, these rates are spread over the entire year. If these rates are known/alerted to the farmers in advance, then it will be promising on ROI (Return on Investments). It requires that the rates of the agricultural products updated into the dataset of each state and each crop, in this application five crops are considered. The predictions are done based on neural networks Neuroph framework in java platform and also the previous years data. The results are produced on mobile application using android. Web based interface is also provided for displaying processed commodity rates in graphical interface. Agricultural experts can follow these graphs and predict market rates which can be informed to the farmers. The results will be provided based on the location of the users of this application.

scholarly journals Augmenting Crop Detection for Precision Agriculture with Deep Visual Transfer Learning—A Case Study of Bale Detection

2020 ◽  
Vol 13 (1) ◽  
pp. 23
Author(s):  
Wei Zhao ◽  
William Yamada ◽  
Tianxin Li ◽  
Matthew Digman ◽  
Troy Runge
Keyword(s):  
Object Detection ◽  
Transfer Learning ◽  
Precision Agriculture ◽  
Crop Production ◽  
Domain Adaptation ◽  
Training Data ◽  
Detection Accuracy ◽  
Detection Model ◽  
Agriculture Products

In recent years, precision agriculture has been researched to increase crop production with less inputs, as a promising means to meet the growing demand of agriculture products. Computer vision-based crop detection with unmanned aerial vehicle (UAV)-acquired images is a critical tool for precision agriculture. However, object detection using deep learning algorithms rely on a significant amount of manually prelabeled training datasets as ground truths. Field object detection, such as bales, is especially difficult because of (1) long-period image acquisitions under different illumination conditions and seasons; (2) limited existing prelabeled data; and (3) few pretrained models and research as references. This work increases the bale detection accuracy based on limited data collection and labeling, by building an innovative algorithms pipeline. First, an object detection model is trained using 243 images captured with good illimitation conditions in fall from the crop lands. In addition, domain adaptation (DA), a kind of transfer learning, is applied for synthesizing the training data under diverse environmental conditions with automatic labels. Finally, the object detection model is optimized with the synthesized datasets. The case study shows the proposed method improves the bale detecting performance, including the recall, mean average precision (mAP), and F measure (F1 score), from averages of 0.59, 0.7, and 0.7 (the object detection) to averages of 0.93, 0.94, and 0.89 (the object detection + DA), respectively. This approach could be easily scaled to many other crop field objects and will significantly contribute to precision agriculture.

Bayer

2021 ◽  
Vol 32 (3) ◽  
pp. 123-124
Keyword(s):  
Health Care ◽  
Natural Resources ◽  
Health Needs ◽  
World Population ◽  
Health And Nutrition ◽  
Global Leader ◽  
Agriculture Products ◽  
Aging World

A growing and aging world population and the increasing strain on nature's ecosystems are among the major challenges facing humanity. As a global leader in health and nutrition, Bayer is able to play a key role in devising solutions to tackle these challenges. Guided by its purpose "Science for a better life," it delivers breakthrough innovations in health care and agriculture. It contributes to a world in which diseases are not only treated but effectively prevented or cured, in which people can take better care of their own health needs, and in which enough agriculture products are produced while respecting the planet's natural resources. That is because at Bayer, it is believed that growth and sustainability should go hand in hand. In short, they are working to make their vision "Health for all, hunger for none" a reality.

Kojic Acid: A Comprehensive Review

2021 ◽  
Author(s):  
Farah Bashir ◽  
Kishwar Sultana ◽  
Maryam Khalid ◽  
Hafza Rabia ◽  
Najm ul Hassan Khan
Keyword(s):  
Food Industry ◽  
Organic Molecules ◽  
Kojic Acid ◽  
Economic Potential ◽  
Vital Function ◽  
Medical Field ◽  
Analgesic Agent ◽  
Bacterial Agent ◽  
Agriculture Products ◽  
Skin Care Products

Due to the emerging nature of kojic acid, current project was conducted to introduce the abilities in details. KA is produced industrially by Aspergillus species in aerobic fermentation. Its structure was identified as 5-hydroxymethyl-pyrone. The KA plays an important role in determining certain chemical and physical properties it possesses. KA has different applications in various fields. It is broadly utilized in cosmetics, medicine, food, agriculture, chemical and other industries. These days kojic acid performs a vital function in cosmetics specically skin care products because it enhances the capability to prevent UV radiation it extensively utilized in whitening creams and lotions because of its anti tyrosinase activity. Kojic acid keeps getting hold on attention because of its economic potential as an anti-inflammatory and analgesic agent in the medical field. KA is utilized as an anti-bacterial agent in food industry & because of its antioxidant activity it is utilized as an antibrowning agent for agriculture products. Due to various uses of organic molecules the demand for kojic acid has rapidly increased. It also has some drawbacks, such as the KA is highly unstable upon exposure air and sunlight it changes its color and the other drawback is cytotoxicity which may be overcome by way of the formation of kojic acid peptides which are more stable.

scholarly journals Design and Implementation of an Efficient Rose Leaf Disease Detection using K-Nearest Neighbours

2020 ◽  
Vol 9 (3) ◽  
pp. 21-27
Keyword(s):  
Plant Disease ◽  
Spot Size ◽  
Extraction Process ◽  
Disease Classification ◽  
Identification System ◽  
Automated Identification ◽  
Accurate Identification ◽  
Leaf Disease ◽  
Key Factor ◽  
Agriculture Products

Plants are prone to different diseases caused by multiple reasons like environmental conditions, light, bacteria, and fungus. These diseases always have some physical characteristics on the leaves, stems, and fruit, such as changes in natural appearance, spot, size, etc. Due to similar patterns, distinguishing and identifying category of plant disease is the most challenging task. Therefore, efficient and flawless mechanisms should be discovered earlier so that accurate identification and prevention can be performed to avoid several losses of the entire plant. Therefore, an automated identification system can be a key factor in preventing loss in the cultivation and maintaining high quality of agriculture products. This paper introduces modeling of rose plant leaf disease classification technique using feature extraction process and supervised learning mechanism. The outcome of the proposed study justifies the scope of the proposed system in terms of accuracy towards the classification of different kind of rose plant disease.

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