20 pages, One of the main drivers of food insecurity is pests, which are estimated to cause around 40% of crop losses worldwide. We examine the food security effects of plant clinics, a novel agricultural extension model that aims to reduce crop losses due to pests through the provision of demand-driven plant health diagnostic and advisory services to smallholder farmers. The study is based on survey data from maize-growing households in Rwanda, where 66 plant clinics have been established. Using switching regression and matching techniques as well as various food security metrics, including the food insecurity experience scale, we find evidence that participation in plant clinics is significantly associated with a reduction in household food insecurity. For instance, among the participating households, plant clinics contribute to a decrease in the period of food shortage by one month and a reduction in the severity of food insecurity by 22 percentage points. We also show that these effects are more pronounced for female-headed households. Overall, our findings suggest that plant clinics can play an important role in achieving the Sustainable Development Goal 2 of zero hunger.
22pgs, We introduce the “coordination frontier” (CF), a simple practical tool to assess the likelihood of success of voluntary coordination in situations where, ex ante, the collective action solution provides an appealing alternative (e.g., for pest and disease control). We demonstrate the value of information conveyed by the CF, explain how to construct the CF from experimental data, and show how to apply the CF in practice. We illustrate the concept with an application to data from a framed field economic experiment, which was designed to elicit the preferences of Florida's citrus growers regarding their willingness to coordinate actions to combat citrus greening disease. This is a highly relevant case study not only because of the significant impact caused by citrus greening on Florida's citrus industry but also because a voluntary area-wide pest management program to control it had been established in 2010 and eventually failed; a similar program is now in place in California, where the disease spread is at an earlier stage. Had the CF been available in Florida, estimates of the (aggregate) chances of successful coordination could have been shared with growers to update their beliefs regarding the chances of successful coordination to help reduce strategic uncertainty. Policymakers in California could use the CF in such way and devise ways to encourage participation to increase the chances of reaching a desired coordination threshold.
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.
Zazueta, Fedro S. (author), Beck, Howard (author), Xin, Jiannong (author), Halsey, Larry (author), and Fletcher, James (author)
Format:
Paper
Publication Date:
1998
Published:
International
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Document Number: C24673
Notes:
Pages 352-358 in Fedro S. Zazueta and Jiannong Xin (eds.), Computers in agriculture: proceedings of the 7th international conference on computers in agriculture, Orlando, Florida, October 26-30, 1998. St. Joseph, Michigan: American Society of Agricultural Engineers. 999 pages.
