11 pages, Existing research and practice related to digital agriculture technology adoption is largely focused on large-scale producers. In this paper, we describe a case of adopting an advanced soil monitoring system in a community-based agricultural organization. We provide guidance for Extension professionals seeking to implement or promote digital agriculture technology adoption on: selecting appropriate technology, incorporating new technology into existing practices, harnessing local technology champions, and avoiding data-driven mission creep.
Gopi, Arepalli (author), Sudha, L. R. (author), and Joseph, S. Iwin Thanakumar (author)
Format:
Book chapter
Publication Date:
2025-01-24
Published:
Scrivener Publishing LLC
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 209 Document Number: D13544
Journal Title Details:
299-319
Notes:
21 pages, chapter 16 from "Smart Factories for Industry 5.0 Transformation", Sensor technologies enable data-driven, efficient, and sustainable precision agriculture. This initiative monitors, manages, and predicts plant diseases using sensors, cloud computing, and data analytics to improve crop health and productivity. Plant and environmental data is monitored by soil, humidity, temperature, and leaf wetness sensors. Machine learning algorithms discover illness outbreak trends and abnormalities in real-time data on a cloud platform. According to the study, a complete IoT infrastructure easily transfers data from field sensors to cloud servers and decision support tools to end-users. Edge computing preprocesses data and delivers only relevant data to the cloud, decreasing latency and bandwidth. This allows fast, accurate disease prediction models to warn farmers of new hazards for proactive management. The study also examines how alternate communication protocols increase data transfer in agricultural fields with poor circumstances. We also explore how geospatial and sensor data accurately map and quantify disease risk. Cloud-based data analytics improves sickness prediction, operational efficiency, and resource management, this study revealed. This integrated strategy reduces plant diseases, herbicides, and fertilizers, improving sustainability. The scalable, cost-effective answers to modern farming problems in this research support precision agriculture.
15 pages, Agriculture is a significant contributor to the global economy and critical for future food and fibre production. To maximise the industry efficiencies and improve sustainability, a knowledgeable workforce is essential. Today’s school-aged youth will be the next generation agriculture workforce. However, there is concern that today’s youth are more detached from agriculture than ever before, viewing the industry as an unattractive career prospect and possessing low levels of agricultural literacy. Using a qualitative approach, this research presents the results from an open-response survey item asking Australian primary and secondary students to ‘list three words you think of when you hear the word ‘agriculture’’. Focus groups with Australian primary and secondary teachers were also conducted to explore these findings. Overall, students appear to have what can be described as a conventional understanding of agriculture as it relates to traditional farming, particularly animal production. However, students appeared to have a lower level of understanding and perception of the industry in less-traditional settings, including modern careers and the technologies involved. Improved agricultural education in Australia, including both formal and informal programs on possible career paths and technology adoption in the industry is recommended to support knowledge development of the modern sector to attract the next generation workforce.
18 pages, Digital agriculture has been developing rapidly over the past decade. However, studies have shown that the need for more ability to use these tools and the shortage of knowledge contribute to current farmer unease about digital technology. In response, this study investigated the influence of communication channels—mass media, social media, and interpersonal meetings—on farmers’ adoption, decision-making, and benefits obtained using technologies. The research uses data from 461 farmers in Brazil and 340 farmers in the United States, leaders in soybean production worldwide. The results show differences and similarities between these countries. LinkedIn has the highest positive association in Brazil between the communication channels and the digital agriculture technologies analyzed. In the United States, YouTube has the highest positive correlation. The overall influence of social media among Brazilian farmers is higher than among American farmers. The perceived benefits of using digital tools are more strongly associated with mass media communication in the United States than in Brazil. Regarding farm management decision-making, the study showed a higher relevance of interpersonal meetings in Brazil than in the United States. Findings can aid farmers, managers, academics and government decision makers to use communication channels more effectively in evaluating and adopting digital technologies.
Levinson, Jeremy (author), Lamie, Dave (author), Vassalos, Michael (author), Eck, Chris (author), Chong, Juang (author), and Reay-Jones, Francis P. F. (author)
Format:
Journal article
Publication Date:
2024-05-15
Published:
USA: Association for Communication Excellence in Agriculture, Natural Resources, and Life and Human Sciences (ACE)
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 208 Document Number: D13277
9 pages, The Train-the-Trainer approach is widely used in Cooperative Extension education to efficiently disseminate research-based information to many clientele groups, including farmers. This paper compares the traditional Train-the-Trainer model to a comprehensive Collaborative Train-the-Trainer model and discusses weaknesses of the traditional model that are addressed in the Collaborative model. Sources of information used by farmers (growers) and overall effectiveness were measured through a survey instrument created and distributed to farmers in South and North Carolina. The Collaborative Train-the-Trainer model, which emphasizes peer-to-peer interaction and feedback loops, represents an enhanced approach for conceptualizing and implementing Extension educational programs.
Wilms, Lisa (author), Komainda, Martin (author), Hamidi, Dina (author), Riesch, Friederike (author), Horn, Juliane (author), and Isselstein, Johannes (author)
Format:
Journal Article
Publication Date:
2024-04-15
Published:
USA: Oxford University Press
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 209 Document Number: D13552
11 pages, Virtual fencing (VF) is a modern fencing technology that requires the animal to wear a device (e.g., a collar) that emits acoustic signals to replace the visual cue of traditional physical fences (PF) and, if necessary, mild electric signals. The use of devices that provide electric signals leads to concerns regarding the welfare of virtually fenced animals. The objective of this review is to give an overview of the current state of VF research into the welfare and learning behavior of cattle. Therefore, a systematic literature search was conducted using two online databases and reference lists of relevant articles. Studies included were peer-reviewed and written in English, used beef or dairy cattle, and tested neck-mounted VF devices. Further inclusion criteria were a combination of audio and electrical signals and a setup as a pasture trial, which implied that animals grazed in groups on grassland for 4 h minimum while at least one fence side was virtually fenced. The eligible studies (n = 13) were assigned to one or two of the following categories: animal welfare (n studies = 8) or learning behavior (n studies = 9). As data availability for conducting a meta-analysis was not sufficient, a comparison of the means of welfare indicators (daily weight gain, daily lying time, steps per hour, daily number of lying bouts, and fecal cortisol metabolites [FCM]) for virtually and physically fenced animals was done instead. In an additional qualitative approach, the results from the welfare-related studies were assembled and discussed. For the learning behavior, the number of acoustic and electric signals and their ratio were used in a linear regression model with duration in days as a numeric predictor to assess the learning trends over time. There were no significant differences between VF and PF for most welfare indicators (except FCM with lower values for VF; P = 0.0165). The duration in days did not have a significant effect on the number of acoustic and electric signals. However, a significant effect of trial duration on the ratio of electric-to-acoustic signals (P = 0.0014) could be detected, resulting in a decreasing trend of the ratio over time, which suggests successful learning. Overall, we conclude that the VF research done so far is promising but is not yet sufficient to ensure that the technology could not have impacts on the welfare of certain cattle types. More research is necessary to investigate especially possible long-term effects of VF.
14 pages, University agricultural educators are challenged to employ innovative approaches to prepare undergraduates in agriculture and natural resources to address complex global problems while understanding interconnected systems. Undergraduates, current members of Generation Z (Gen Z), prefer environmental sustainability and innovation, but solutions for addressing these preferences in educational settings remain elusive. Exploring Gen Z’s environmental consumption values and how those values relate to their systems thinking tendencies may provide university educators with insights on how to best educate Gen Z students. The purpose of this study was to examine the association between Gen Z students’ green consumer values and systems thinking tendencies. Data were collected using a web-based survey instrument of 68 undergraduate students at the University of [state]. Findings revealed respondents somewhat agreed they had green consumer values and respondents often used systems thinking when seeking to make an improvement. A Spearman’s rank-order correlation coefficient indicated a positive, yet weak, association between systems thinking tendencies and green consumer values. The association necessitates further exploration. University agricultural educators should incorporate systems thinking educational tools into classrooms so Gen Z students can effectively engage in systems thinking when addressing complex agricultural issues, like sustainability. Additional implications for systems thinking teaching are explored.
