22 pages, The objective of this study was to provide a comprehensive overview of the recent advancements in the use of deep learning (DL) in the agricultural sector. The author conducted a review of studies published between 2016 and 2022 to highlight the various applications of DL in agriculture, which include counting fruits, managing water, crop management, soil management, weed detection, seed classification, yield prediction, disease detection, and harvesting. The author found that DL’s ability to learn from large datasets has great promise for the transformation of the agriculture industry, but there are challenges, such as the difficulty of compiling datasets, the cost of computational power, and the shortage of DL experts. The author aimed to address these challenges by presenting his survey as a resource for future research and development regarding the use of DL in agriculture.
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 161 Document Number: D07899
Notes:
In the e-book: Kerry J. Byrnes, Giants in their realms: close encounters of the celebrity kind. Posted on the website of Okemos High School Alumni, Okemos, Michigan. 11 pages.
Madushanka, L.S. (author), Weerasinghe, K.S. (author), Weerakkody, W.J.S.K. (author), and Department of Plantation Management, Faculty of Agriculture and Plantation Management, Wayamba University of Sri Lanka, Makandura, Gonawila (NWP), Sri Lanka
ICT Center, Wayamba University of Sri Lanka, Makandura, Gonawila (NWP), Sri Lanka
Format:
Conference paper
Publication Date:
2017-01-23
Published:
Sri Lanka: Institute of Electrical and Electronics Engineers Inc.
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 162 Document Number: D08140
Notes:
16th International Conference on Advances in ICT for Emerging Regions, ICTer 2016; Jetwing BlueNegombo; Sri Lanka; 1 September 2016 through 3 September 2016; Category numberCFP1686L-ART; Code 126111. Article number 7829902, pp. 80-86
Knierim, Andrea (author) and Prager, Katrin (author)
Format:
Report
Publication Date:
2015-07
Published:
International
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 149 Document Number: D06722
Notes:
Online via Proakis.com.eu. 4 pages., "Overall, the analysis revealed that European AKIS are characterised by a mix of public and private actors, and there are no countries where only public actors dominate the knowledge system."
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 139 Document Number: D05918
Notes:
Via website of the United Nations Conference on Trade and Development (UNCTAD), Geneva, Switzerland. UNCTAD Current Studies on Science, Technology and Innovation, No. 9. 84 pages.
Hundal, Gaganpreet Singh (author), Laux, Chad Matthew (author), Buckmaster, Dennis (author), Sutton, Mathias J (author), and Langemeier, Michael (author)
Format:
Journal article
Publication Date:
2023-01-09
Published:
Switzerland: MDPI
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 206 Document Number: D12835
16 pages, The production of row crops in the Midwestern (Indiana) region of the US has been facing environmental and economic sustainability issues. There has been an increase in trend for the application of fertilizers (nitrogen & phosphorus), farm machinery fuel costs and decreasing labor productivity leading to non-optimized usage of farm inputs. Literature describes how sustainable practices such as profitability (return on investments), operational cost reduction, hazardous waste reduction, delivery performance and overall productivity might be adopted in the context of precision agriculture technologies (variable rate irrigation, variable rate fertilization, cloud-based analytics, and telematics for farm machinery navigation). The literature review describes low adoption of Internet of Things (IoT)-based precision agriculture technologies, such as variable rate fertilizer (39%), variable rate pesticide (8%), variable rate irrigation (4%), cloud-based data analytics (21%) and telematics (10%) amongst Midwestern row crop producers. Barriers to the adoption of IoT-based precision agriculture technologies cited in the literature include cost effectiveness, power requirements, wireless communication range, data latency, data scalability, data storage, data processing and data interoperability. Therefore, this study focused on exploring and understanding decision-making variables related to barriers through three focus group interview sessions conducted with eighteen (n = 18) subject matter experts (SME) in IoT- based precision agriculture practices. Dependency relationships described between cost, data latency, data scalability, power consumption, communication range, type of wireless communication and precision agriculture application is one of the main findings. The results might inform precision agriculture practitioners, producers and other stakeholders about variables related to technical and operational barriers for the adoption of IoT-based precision agriculture practices.
Findings prompt researchers to recommend the use of information and communications technologies with conventional approaches in conservation agriculture knowledge networks.
