Axelson J. (author), Battles J. (author), Bulaon B. (author), Cluck D. (author), Cousins S. (author), Cox L. (author), Estes B. (author), Fettig C. (author), Hefty A. (author), Hushinuma S. (author), Hood S. (author), Kocher S. (author), Mortenson L. (author), Koltunov A. (author), Kuskulis E. (author), Poloni A. (author), Ramirez C. (author), Restaino C. (author), Slaton M. (author), Smith S. (author), and Tubbesing C. (author)
Format:
Online journal article
Publication Date:
2019-03-11
Published:
USA: University of California
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 16 Document Number: D10456
10 pages., via online journal, The collaboration helps to coordinate research on the extent and nature of tree mortality and gets the results to forest managers quickly.
11 pages., Via online journal article, OBJECTIVES: To examine the impact of social media influencer marketing of foods (healthy and unhealthy) on children’s food intake.
METHODS: In a between-subjects design, 176 children (9–11 years, mean 10.5 ± 0.7 years) were randomly assigned to view mock Instagram profiles of 2 popular YouTube video bloggers (influencers). Profiles featured images of the influencers with unhealthy snacks (participants: n = 58), healthy snacks (n = 59), or nonfood products (n = 59). Subsequently, participants’ ad libitum intake of unhealthy snacks, healthy snacks, and overall intake (combined intake of healthy and unhealthy snacks) were measured.
RESULTS: Children who viewed influencers with unhealthy snacks had significantly increased overall intake (448.3 kilocalories [kcals]; P = .001), and significantly increased intake of unhealthy snacks specifically (388.8 kcals; P = .001), compared with children who viewed influencers with nonfood products (357.1 and 292.2 kcals, respectively). Viewing influencers with healthy snacks did not significantly affect intake.
CONCLUSIONS: Popular social media influencer promotion of food affects children’s food intake. Influencer marketing of unhealthy foods increased children’s immediate food intake, whereas the equivalent marketing of healthy foods had no effect. Increasing the promotion of healthy foods on social media may not be an effective strategy to encourage healthy dietary behaviors in children. More research is needed to understand the impact of digital food marketing and inform appropriate policy action.
Online from publisher website. 5 pages., Describes a new Food Trust Consortium , run by IBM, using blockchain technologies to improve food traceability.
New-Aaron, Moses (author), Semin, Jessica (author), Duysen, Ellen G. (author), Madsen, Murray (author), Musil, Kelsie (author), and Rautiainen, Risto H. (author)
Format:
Journal article abstract
Publication Date:
2019
Published:
USA: Taylor & Francis
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 25 Document Number: D10537
8 pages., via online journal., The Bureau of Labor Statistics (BLS) publishes annual statistics on occupational injuries and fatalities in the United States. The BLS fatality data include all agricultural workers while the non-fatal injury data only cover hired employees on large farms. In 2012, the Central States Center for Agricultural Safety and Health (CS-CASH) began collecting regional media monitoring data of agricultural injury incidents to augment national statistics. The aims of this report were: a) to compare CS-CASH injury and fatality data collected via print and online sources to data reported in previous studies, and b) to compare fatality data from media monitoring to BLS Census of Fatal Occupational Injuries (CFOI) data. CS-CASH media monitoring data were collected from a news clipping service and an internet detection and notification system. These data covered years 2012–2017 in seven Midwestern states (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota). CS-CASH occupational fatality data were compared with aggregate CFOI data for the region during 2012–2015. Media monitoring captured 1048 injury cases; 586 (56%) were non-fatal and 462 (44%) were fatal. The numbers of occupational fatality cases from media monitoring and CFOI were nearly identical (280 vs. 282, respectively), and the distributions by type of injury were similar. Findings suggest that media monitoring can capture equal numbers of fatalities compared to CFOI. Non-fatal injuries, not captured by national surveillance systems, can be collected and tracked using print and electronic media. Risk factors, identified in media sources, such as gender, age, time, and source of the incident are consistent with previously reported data. Media monitoring can provide timely access to detailed information on individual cases, which is important for detecting unique and emerging hazards, designing interventions and for setting policy and guiding national strategies.
16 pages., Via online journal., Expertise is dynamic, domain specific, and characterized according to an individual’s level of knowledge, experience, and problem-solving ability. Having expertise in the phenomenon under investigation can be used as an indicator of an individual’s aptitude to effectively serve as a coder in a content analysis or as panelist in a Delphi study. The purpose of this study was to assess 10 years of scholarship published in the premier journals of agricultural education and describe the ways researchers in agricultural communications, education, extension, and leadership disciplines who use content analysis and Delphi study methods are describing the qualifications of the people serving as expert coders and panelists. The study findings revealed the majority of researchers publishing in the premier agricultural education journals are not describing the qualifications used in selecting coders or the credentials the coders possess that would make them qualified to code the data in a content analysis. Furthermore, researchers were inconsistent citing literature that supported their selection of content analysis coders and citing literature to support a decision to describe or not to describe coders’ qualifications. However, a description of Delphi study panelists’ qualifications and citations to support why panelists were selected in a Delphi study were present in all of the Delphi studies analyzed over the 10-year period. Based on these findings, it was concluded that ACEEL researchers should include a description of coder credentials to enhance the consistency, transparency, replicability, rigor, and integrity of ACEEL research. Editors and research professionals who perform journal article reviews for the premier agricultural education journals are encouraged to note the exclusion of a description of content analysis coders’ credentials as part of the peer review process.
1 page., September-November issue via online., Report on a drone service, WeFly Agri, "to help farm and plantation owners regain control of their land."
Online via publisher website., This paper proposes a food safety traceability system based on the blockchain and the EPC Information Services and develops a prototype system.
2 pages, via online magazine archive, Several years ago, Farm Market iD saw that agribusinesses were struggling to use to the data and insights at their disposal to understand how they were performing in the market and needed modern-day data science to power decision-making. Given Farm Market iD's unique and powerful data and our ability to contextualize data to understand and interpret the agricultural market, we knew we had something valuable to offer.
8 pages, via online journal, Rose (Rosa ×hybrida) breeders historically have bred plants based on what they personally have deemed attractive and traits required by growers to produce the crop successfully. End-user preferences were not formally considered in breeding decisions. The purpose of this study was to investigate growers’ and consumers’ opinions of roses available on the market and preferences for future roses coming into the market. A web-based survey tool was developed to measure the attributes consumers were considering in purchasing and growing rose plants, their knowledge of diseases and pests, and their hopes for new plants coming to market. A link was sent to horticultural group mailing lists as well as distributed through personal e-mail lists, Facebook, and a news release from Texas A&M University. The survey was posted for 4 months. It included ≈66 questions and took 30 minutes or more to complete. More than 2000 responses were received from rose growers and nursery consumers worldwide. The respondents preferred roses that were disease resistant, with fragrant, abundant, red, and everblooming flowers. The ideal height of the preferred rose shrubs was waist to shoulder-height. Differences were found in preferences between experienced rose growers and those who were not affiliated with rose associations on variables such as the need to use chemicals to manage diseases, the importance of foliage glossiness and large vs. small blooms, the value of roses in the garden setting, the level of difficulty roses pose in growing situations, and the willingness to pay more for a rose shrub in comparison with other garden plants. Differences also were found among age groups and preferences for flower color, fragrance, foliage color, and foliage glossiness. This information could be helpful in targeting marketing of roses.
17 pages, Modern agriculture is facing unique challenges in building a sustainable future for food production, in which the reliable detection of plantation threats is of critical importance. The breadth of existing information sources, and their equivalent sensors, can provide a wealth of data which, to be useful, must be transformed into actionable knowledge. Approaches based on Information Communication Technologies (ICT) have been shown to be able to help farmers and related stakeholders make decisions on problems by examining large volumes of data while assessing multiple criteria. In this paper, we address the automated identification (and count the instances) of the major threat of olive trees and their fruit, the Bactrocera Oleae (a.k.a. Dacus) based on images of the commonly used McPhail trap’s contents. Accordingly, we introduce the “Dacus Image Recognition Toolkit” (DIRT), a collection of publicly available data, programming code samples and web-services focused at supporting research aiming at the management the Dacus as well as extensive experimentation on the capability of the proposed dataset in identifying Dacuses using Deep Learning methods. Experimental results indicated performance accuracy (mAP) of 91.52% in identifying Dacuses in trap images featuring various pests. Moreover, the results also indicated a trade-off between image attributes affecting detail, file size and complexity of approaches and mAP performance that can be selectively used to better tackle the needs of each usage scenario.
