Business and Politics in Zimbabwe's Commercial Agriculture Sector

1999 ◽  
pp. 177 ◽  
Author(s):  
Scott D. Taylor
Keyword(s):  
Commercial Agriculture ◽  
Agriculture Sector ◽  
Business And Politics

Sustainable Agriculture and Rural Development in South Africa

1995 ◽  
Vol 24 (3) ◽  
pp. 163-165 ◽  
Author(s):  
Marthinus D. Saunderson
Keyword(s):  
South Africa ◽  
Rural Development ◽  
Agricultural Research ◽  
Small Scale ◽  
Commercial Agriculture ◽  
Sustainable Rural Development ◽  
Agriculture Sector ◽  
Agricultural Research And Development ◽  
Small Scale Farmers ◽  
White Farmers

South Africa is divided into two different worlds when it comes to agriculture. One is the commercial agriculture sector, dominated by white farmers, and the other is the developing sector of small-scale, disadvantaged farmers. This is of course the result of the old system of apartheid, Agricultural research and development as well as extension have been focused on white commercial farmers, to the neglect of the small scale farmers. Agricultural research aimed at their specific conditions is essential for sustainable rural development.

scholarly journals Economic Incentives to Reduce the Quantity of Chemicals Used in Commercial Agriculture

1972 ◽  
Vol 4 (1) ◽  
pp. 203-208 ◽  
Author(s):  
Ronald D. Lacewell ◽  
William R. Masch
Keyword(s):  
Economic Incentives ◽  
Social Costs ◽  
Primary Effect ◽  
Commercial Agriculture ◽  
Agriculture Sector ◽  
Legislative Action ◽  
The Social ◽  
Agricultural Areas

In recent years, considerable national attention has focused on the use of chemicals by the agriculture sector. Recent descriptive analyses have addressed the problem.of attempting to determine, or to describe, some of the social “costs” of chemicals used in agriculture which later move to non-agricultural areas. The primary effect of the attention on chemical use in agriculture has been legislative action relative to specific pesticides such as DDT and 2,4,5-T. These actions have made national news along with reports of measured residues of these pesticides in wildlife, fish and other forms of foodstuffs.

Business and politics.

1961 ◽  
Vol 16 (3) ◽  
pp. 142-142 ◽  
Author(s):  
Joan Fiss
Keyword(s):  
Business And Politics

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. 

Sign in / Sign up

Export Citation Format

Share Document