Computers and Electronics in Agriculture

An International Journal

Computers and Electronics in Agriculture - ISSN 0168-1699
Source Normalized Impact per Paper (SNIP): 1.833 Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 0.95 SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Impact Factor: 3.171 (2018) Impact Factor:
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
5 Year Impact Factor: 3.538 (2018) Five-Year Impact Factor:
To calculate the five year Impact Factor, citations are counted in 2016 to the previous five years and divided by the source items published in the previous five years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
Volumes: Volumes 156-167
Issues: 12 issues
ISSN: 01681699

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Description

Computers and Electronics in Agriculture provides international coverage of advances in the development and application of computer hardware, software and electronic instrumentation and control systems for solving problems in agriculture and related industries. These include agronomy, horticulture (in both its food and amenity aspects), forestry, aquaculture, animal/livestock science, veterinary medicine, and food processing.

The journal publishes original papers, reviews, applications notes and book reviews on topics including computerized decision-support aids (e.g., expert systems and simulation models) pertaining to any aspect of the aforementioned industries; electronic monitoring or control of any aspect of livestock/crop production (e.g. soil and water, environment, growth, health, waste products) and post-harvest operations (such as drying, storage, production assessment, trimming and dissection of plant and animal material). Relevant areas of technology include artificial intelligence, sensors, machine vision, robotics and simulation modelling.

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