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Mechanisation of large‐scale agricultural fields in developing countries – a review

Overview of attention for article published in Journal of the Science of Food and Agriculture, April 2016
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Title
Mechanisation of large‐scale agricultural fields in developing countries – a review
Published in
Journal of the Science of Food and Agriculture, April 2016
DOI 10.1002/jsfa.7699
Pubmed ID
Authors

Daniel I Onwude, Rafia Abdulstter, Chandima Gomes, Norhashila Hashim

Abstract

Mechanisation of large scale agricultural fields often requires the application of modern technologies such as mechanical power, automation, control and robotics. These technologies are generally associated with relatively well developed economies. The application of these technologies in some developing countries in Africa and Asia is limited by factors such as technology compatibility with the environment, availability of resources to facilitate the technology adoption, cost of technology purchase, government policies, adequacy of technology and appropriateness in addressing the needs of the population. As a result, many of the available resources have been used inadequately by farmers, who continue to rely mostly on conventional means of agricultural production, using traditional tools and equipment in most cases. This has led to low productivity and high cost of production amongst others. Thus, this paper attempts to evaluate the application of present day technology and its limitations to the advancement of large scale mechanisation in developing countries of Africa and Asia. Particular emphasis is given to a general understanding of the various levels of mechanization, present day technology, its management and application to large scale agricultural fields. This review also focuses on/ gives emphasis to future outlook that will enable a gradual, evolutionary, and sustainable technological change. The study concludes that large scale-agricultural farm mechanisation for sustainable food production in Africa and Asia must be anchored on a coherent strategy based on the actual needs and priorities of the large- scale farmers.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 1%
Nigeria 1 1%
Unknown 84 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 22%
Student > Master 15 17%
Student > Doctoral Student 9 10%
Lecturer 5 6%
Researcher 5 6%
Other 15 17%
Unknown 18 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 16%
Engineering 11 13%
Economics, Econometrics and Finance 9 10%
Social Sciences 7 8%
Business, Management and Accounting 7 8%
Other 14 16%
Unknown 24 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 November 2019.
All research outputs
#7,714,335
of 25,374,647 outputs
Outputs from Journal of the Science of Food and Agriculture
#1,055
of 4,642 outputs
Outputs of similar age
#102,184
of 315,829 outputs
Outputs of similar age from Journal of the Science of Food and Agriculture
#14
of 77 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 4,642 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 315,829 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 77 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.