Sustainable, Inclusive Agriculture Sector Growth in Armenia

10.1596/29699 ◽  
2017 ◽  
Author(s):  
Garry Christensen
Keyword(s):  
Agriculture Sector

Machine Learning in Agriculture

2018 ◽  
Vol 8 (6) ◽  
pp. 26 ◽  
Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Diagnosis ◽  
Automated Detection ◽  
Disease Prediction ◽  
Paper Briefly ◽  
Agriculture Sector ◽  
Modern Agriculture ◽  
Crop Disease

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

Role of Research and Development in Sustaining Indian Agriculture: A Brief Review

2020 ◽  
pp. 396-401
Keyword(s):  
Research And Development ◽  
Production Process ◽  
Annual Increase ◽  
Agriculture Sector ◽  
The Past ◽  
Indian Agriculture ◽  
Self Sufficiency ◽  
Development Institutions ◽  
Agriculture Development

Technology united with research and development has evolved as a grave differentiator of the agriculture sector in India including production, processing, and agriculture packing and marketing of given crops. Near about 50 percent of the Indian workforce was engaged in the agriculture sector but its share in GDP was only 14 percent, much lower in comparison to former. Though, certain agriculture items showed a steady annual increase in terms of kilograms per hectare. Agriculture transformed significantly over the past few decades but when it comes to investment in research and development there is a lot more which needs to be done. The paper analyzes the role of various research and development institutions in boosting the growth of the agriculture sector that helps in attaining sustainable agriculture development and self-sufficiency in the production process since independence. It also focusesed on the various issues faced by these development institutions. The findings unveiled that since independence a lot more was done to boost the research and development in the agriculture sector at both the center and state levels but a proper implementation of these policies along with transparency could bring more desirable outcomes than were gained at present.

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