30 pages, While Georgia is one of the top producers of cotton and peanuts in the Unites States, much attention has been centered on ensuring sustainability in the production of these crops. The need to understand what drives farmers’ decision to utilize voluntary best management practices is critical for the improvement of strategies focused on increasing farmers’ adoption of these practices. Empirical evidence that identifies influential factors in farmers’ decision to adopt best management practices have yet to produce consistent predictors of adoption behavior. This has led to increased calls for unique approaches examining how farmers’ views and motivations impact their adoption decisions regarding these practices. This study builds on previous research using Q methodology to provide an in-depth investigation of the differences in farmers’ views on best management practices for cotton and peanut production in southwest Georgia. A purposive sample of 21 participants completed the Q sorting exercise and semi-structured interviews. Analysis of the data revealed three primary viewpoints that were identified and labeled as the: (1) land preservers, (2) ambitious self-starters, and (3) principled go-getters. These perspectives show the differences in motivations for adoption behavior and denote the range of influential factors on farm management decisions. The findings of this study reveal key viewpoints held by Georgia cotton and peanut farmers toward best management practices, which can inform the development of strategically tailored educational resources and opportunities. These targeted educational approaches must account for the specific needs and preferences of farmers found in this study to potentially increase adoption.
23 pages, Cotton is the most significant natural fiber in the world and an important part of the global economy. Yet, the cotton industry faces several challenges in securing its place in the global fiber market share, reaching new consumers, and maintaining relationships with current consumers. Furthermore, the cotton industry has a unique opportunity to share evidence-based information with followers through its product marketing on social media. The study described herein used content analysis to explore Instagram content on the @discovercotton profile. Content included categories of promoted products (i.e. women, men, children, or home); comments, posts, and caption stimuli; and most frequently used word, hashtag, and retail partner stimuli. We analyzed 434 Instagram stimuli (244 single photos, 142 carousels, and 48 videos) from March 2, 2021, to March 2, 2023. Across all stimuli, there were 110,143 likes and 5,799 comments with total response (engagement: likes and comments) reaching 115,942. We found that women’s products were promoted most often followed by men, home, and children—only 8.48% of stimuli depicted cotton, a cotton plant, or the seal of cotton. We identified six major themes in caption stimuli on @discovercotton: qualities of cotton, style, sustainability, check the label, women, and cotton production. Cotton was the most frequently used word stimuli in captions, and cotton as a fabric was the most promoted theme.
Bin, Li (author), Shahzad, Muhammad (author), Khan, Hira (author), Bashir, Muhammad Mehran (author), Ullah, Arif (author), and Siddique, Muhammad (author)
Format:
Journal article
Publication Date:
2023-09-18
Published:
Switzerland: MDPI
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 206 Document Number: D12959
20 pages, Sustainable agriculture is a pivotal driver of a nation’s economic growth, especially considering the challenge of providing food for the world’s expanding population. Agriculture remains a cornerstone of many nations’ economies, so the need for intelligent, sustainable farming practices has never been greater. Agricultural industries worldwide require sophisticated systems that empower farmers to manage their crops efficiently, reduce water wastage, and optimize yield quality. Yearly, substantial crop losses occur due to unpredictable environmental changes, with improper irrigation practices being a leading cause. In this paper, we introduce an innovative irrigation time control system for smart farming. This system leverages fuzzy logic to regulate the timing of irrigation in cotton crop fields, effectively curbing water wastage while ensuring that crops receive neither too little nor too much water. Additionally, our system addresses a common agricultural challenge: whitefly infestations. Users can adjust climatic parameters, such as temperature and humidity, through our system, which minimizes both whitefly populations and water consumption. We have developed a portable measurement technology that includes air humidity sensors, temperature sensors, and rain sensors. These sensors interface with an Arduino platform, allowing real-time climate data collection. This collected climate data is then sent to the fuzzy logic control system, which dynamically adjusts irrigation timing in response to changing environmental conditions. Our system incorporates an algorithm that generates highly effective (IF-THEN) fuzzy logic rules, significantly improving irrigation efficiency by reducing overall irrigation duration. By automating the irrigation process and precisely delivering the right amount of water, our system eliminates the need for human intervention, rendering the agricultural system more dependable in achieving successful crop yields. Water supply commences when the environmental conditions reach specific thresholds and halts when the requisite climate conditions are met, maintaining an optimal environment for crop growth.
Wallander, Steven (author), Smith, David (author), Bowman, Maria (author), and Claassen, Roger (author)
Format:
Research report
Publication Date:
2021-02
Published:
USA: Economic Research Service, U.S. Department of Agriculture
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 202 Document Number: D12143
Notes:
Economic Information Bulletin Number 222. 33 pages., This report detailed how cover crops are managed on corn, cotton, soybean, and wheat fields in the United States. "These surveys reveal that there are many different approaches to using cover crops."
USA: U.S. Department of Agriculture, Washington, D.C.
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 201 Document Number: D11770
Notes:
Online via AgriMarketing Weekly. 1 page., U.S. Department of Agriculture reports that more than 90 percent of corn, soybean, and cotton acreage involves herbicide-resistant varieties. Currently, 92 percent of U.S. cotton acres are planted with genetically-engineered, insect-resistant seeds and 83 percent of U.S. corn acres.
Benavidez, Justin R. (author), Ribera, Luis A. (author), and Thayer, Anastasia (author)
Format:
Paper
Publication Date:
2020
Published:
International
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 201 Document Number: D11717
Notes:
Paper presented at the 2020 Agricultural and Applied Economics Association Annual Meeting, Kansas City, Missouri, July 26-28, 2020. 20 pages., Authors assessed the impact of tweets by U.S. President Donald Trump on agricultural commodity prices during the trade war with China. Results indicated tht days with high counts of tweets with keywords associated with the 2018-2019 trade war led to statistically significant structural breaks in the price series for hogs, corn, cotton, and soybeans.
26 pages., via online journal., This paper employs the patent data of four major genetically modified (GM) crops, soybeans, cotton, maize and rapeseed, to illustratee how the innovation of GM crop technology diffused and distributed globally over time. Data collected from the Derwent Innovation Index, were employed to construct country patent citation networks, from 1984 to 2015, and the results revealed that developed countries were early adopters, and the primary actors in the innovation of GM crop technology. Only seven developing countries appeared in the country citation network. Most developed countries were reluctant to apply GM crop technology for commercial cultivation. Private businesses stood out in the patent citation network. The early adoption and better performance of developed countries can be explained by the activities of large established private companies.
12 pages, We use the 2013 cotton precision farming survey data to study the adoption of irrigation technologies by cotton farmers in 14 states of the United States. We find that farmers with a higher irrigated yield, and who are from the Southern Plains (Texas and Oklahoma), adopt water-efficient irrigation technologies, such as sub-surface drip and trickle irrigation technologies. There are 10 irrigation technologies that farmers can adopt for cotton production in these 14 cotton-growing states. The intensity of the irrigation technologies, as measured by the number of irrigation technologies adopted in cotton production, is affected by the irrigated cotton yield realized, land holding (total land owned), education, computer use, and the origin of the cotton farmer being from the Southern Plains. We use a multivariate fractional regression model to identify land allocation by the different irrigation technologies used. Our results indicate that significant variables affecting land allocation with different irrigation technologies are the age of the operator, the cover crop, the information sources used, the per acre irrigated yield, the education, and the cotton farmer being from the Southern Plains.
14 pages., via online journal., This study has investigated farm households' simultaneous use of social networks, field extension, traditional media, and modern information and communication technologies (ICTs) to access information on cotton crop production. The study was based on a field survey, conducted in Punjab, Pakistan. Data were collected from 399 cotton farm households using the multistage sampling technique. Important combinations of information sources were found in terms of their simultaneous use to access information. The study also examined the factors influencing the use of various available information sources. A multivariate probit model was used considering the correlation among the use of social networks, field extension, traditional media, and modern ICTs. The findings indicated the importance of different socioeconomic and institutional factors affecting farm households' use of available information sources on cotton production. Important policy conclusions are drawn based on findings.
Identified online via keyword search of UI eCatalog, Examines the inter-relationship between journalism and poetry in the 19th century, when poems on topical issues regularly appeared in newspapers alongside prose reports of the same events.
Nidumolu, U.B. (author), Lubbers, M. (author), Kanellopoulos, A. (author), van Ittersum, M.K. (author), Kadiyala, D.M. (author), and Sreenivas, G. (author)
Format:
Journal article
Publication Date:
2016-11
Published:
India
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 159 Document Number: D07676
Kotsiri, Sofia (author), Rejesus, Roderick M. (author), Larkin, Sherry (author), Lambert, Dayton M. (author), English, Burton C. (author), Larson, James A. (author), Velandia, Margarita M. (author), Roberts, Roland K. (author), Mishra, Ashok K. (author), and Paudel, Krishna P. (author)
Format:
Paper
Publication Date:
2013-02-03
Published:
USA
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 186 Document Number: D00900
Notes:
Paper presented at the Southern Agricultural Economics Association annual meeting, Orlando, Florida, February 3-5, 2013. 31 pages.
30 pages., via online journal., In this article we present and discuss two experiments designed to test the effectiveness of the Internet as a tool of agricultural information. Subjects were cotton producers from Thessaly, Greece. Findings suggest that, in the early stages of an innovation diffusion process, the Internet is more effective than social sources (Experiment 1). However, when urgent situations that force quick decisions occur (Experiment 2), the Internet is significantly less effective than face-to-face communication channels. In both cases, farmers who used the Internet spent more time and devoted extra effort. The experiments proved that agronomists remain the most effective information source. Results also illustrate that Internet adoption is not necessarily synonymous with its use.
