skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: "We need a better system": Maryland crop growers' perspectives on reducing food loss through donation
The donation of unharvested or unsold crops to rescue organizations has been promoted as a strat­egy to improve healthy food access for food inse­cure households while reducing production-level food loss and waste (FLW). In this study, we aimed to assess the motivations, barriers, and facili­tators for crop donation as a FLW reduction strat­egy among Maryland farmers. We interviewed 18 Maryland-based food producers (nine frequent crop donors and nine infrequent, by self-report) in 2016 – 2017, soliciting their perspectives on crop donation motivators, process feasibility, and inte­r­ventions aimed at increasing crop donation. The interviews were thematically coded. All respond­ents were aware of crop donation as an option, and most expressed interest in reducing FLW by divert­ing crop surpluses for human consumption. While financial barriers represented one aspect influenc­ing donation decisions, respondents also cited con­venience, process knowledge, and liability as key considerations. In contrast to frequent donors, many of whom considered donation a moral imperative, some infrequent donors questioned the expectation that they would donate crops without compensation. Both frequent and infrequent donors were aware of pro-donation tax incentives, and infrequent donors reported being unlikely to use them. This research demonstrates that crop donation motivations, barriers, and facilitators can be diverse. Given the existence of crop surpluses and their potential benefits as emergency food, our results suggest that multiple interventions and poli­cies may contribute to incentivizing and facilitating crop donation (or enabling the purchase of surplus crops) rather than one-size-fits-all approaches. Our findings also highlight a need to prioritize crop recovery methods that enhance growers’ financial stability.  more » « less
Award ID(s):
2115405
PAR ID:
10465090
Author(s) / Creator(s):
; ; ; ; ; ;
Date Published:
Journal Name:
Journal of Agriculture, Food Systems, and Community Development
ISSN:
2152-0801
Page Range / eLocation ID:
1 to 18
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; (, Qualitative Health Research)
    The objective of this study was to investigate factors influencing one’s decision to become a live kidney donor under the framework of sociotechnical systems, by expanding the focus to include larger organizational influences and technological considerations. Semi-structured interviews were conducted with live kidney donors who donated through University of Louisville Health, Trager Transplant Center, a mid-scale transplant program, in the years 2017 through 2019. The interview transcripts were analyzed for barriers and facilitators to live kidney donation within a sociotechnical system. The most salient facilitators included: having an informative, caring, and available care team; the absence of any negative external pressure toward donating; donating to a family or friend; and the ability to take extra time off work for recovery. The most recurrent barriers included: short/medium-term (<1 year) negative health impacts because of donation; the need to make minor lifestyle changes (e.g., less alcohol consumption) after donation; and mental health deterioration stemming from the donation process. The sociotechnical systems framework promotes a balanced system comprised of social, technical, and environmental subsystems. Assessing the facilitators and barriers from the sociotechnical system perspective revealed the importance of and opportunities for developing strategies to promote integration of technical subsystem, such as social media apps and interactive AI platforms, with social and environmental subsystems to enable facilitators and reduce barriers effectively. 
    more » « less
  2. ; (, Predicting Food Donor Contribution Behavior Using Support Vector Regression)
    Hunger and food insecurity are present in each American county. Government and non-government organizations are working to address food insecurity in the United States. Food banks are nonprofit hunger relief organizations that collect food and monetary donations from donors and distribute food to local agencies which serve people in need. Contributions come from retail donors, communities, and food manufacturers. The uncertainty of donation amounts and frequency is a challenge for food banks in the fight against hunger. In this research, we analyze local food bank donation data and propose a predictive model to forecast the contribution of different donors. Our study shows the necessary behavioral attributes to classify donors and the best way to cluster donor data to improve the prediction model. We also compare the accuracy of prediction for different conventional forecasting techniques with the proposed Support Vector Regression (SVR) model. 
    more » « less
  3. ; ; ; ; (, BMJ Global Health)
    null (Ed.)
    Introduction Living-donor kidney transplantation is the gold standard treatment for patients with end-stage kidney disease. However, potential donors ubiquitously face financial as well as logistical barriers. To remove these disincentives from living kidney donations, the governments of 23 countries have implemented reimbursement programmes that shift the burdens of non-medical costs from donors to the governments or private entities. However, scientific evidence for the effectiveness of these programmes is scarce. The present study investigates whether these reimbursement programmes designed to ease the financial and logistical barriers succeeded in increasing the number of living kidney donations at the country level. The study examined within-country variations in the timing of such reimbursement programmes. Method The study applied the difference-in-difference (two-way panel fixed-effect) technique on the Poisson distribution to estimate the effects of these reimbursement programmes on a 17 year long (2000–2016) dataset covering 109 countries where living donor kidney transplants were performed. Results The results indicated that reimbursement programmes have a statistically significant positive effect. Overall, the model predicted that reimbursement programmes increased country-level donation numbers by a factor of 1.12–1.16. Conclusion Reimbursement programmes may be an effective approach to alleviate the kidney shortage worldwide. Further analysis is warranted on the type of reimbursement programmes and the ethical dimension of each type of such programmes. 
    more » « less
  4. ; ; ; ; (, JMIR Medical Informatics)
    BackgroundLiving kidney donation currently constitutes approximately a quarter of all kidney donations. There exist barriers that preclude prospective donors from donating, such as medical ineligibility and costs associated with donation. A better understanding of perceptions of and barriers to living donation could facilitate the development of effective policies, education opportunities, and outreach strategies and may lead to an increased number of living kidney donations. Prior research focused predominantly on perceptions and barriers among a small subset of individuals who had prior exposure to the donation process. The viewpoints of the general public have rarely been represented in prior research. ObjectiveThe current study designed a web-scraping method and machine learning algorithms for collecting and classifying comments from a variety of online sources. The resultant data set was made available in the public domain to facilitate further investigation of this topic. MethodsWe collected comments using Python-based web-scraping tools from the New York Times, YouTube, Twitter, and Reddit. We developed a set of guidelines for the creation of training data and manual classification of comments as either related to living organ donation or not. We then classified the remaining comments using deep learning. ResultsA total of 203,219 unique comments were collected from the above sources. The deep neural network model had 84% accuracy in testing data. Further validation of predictions found an actual accuracy of 63%. The final database contained 11,027 comments classified as being related to living kidney donation. ConclusionsThe current study lays the groundwork for more comprehensive analyses of perceptions, myths, and feelings about living kidney donation. Web-scraping and machine learning classifiers are effective methods to collect and examine opinions held by the general public on living kidney donation. 
    more » « less
  5. ; ; (, Agronomy Journal)
    Abstract In agriculture, important unanswered questions about machine learning and artificial intelligence (ML/AI) include will ML/AI change how food is produced and will ML algorithms replace or partially replace farmers in the decision process. As ML/AI technologies become more accurate, they have the potential to improve profitability while reducing the impact of agriculture on the environment. However, despite these benefits, there are many adoption barriers including cost, and that farmers may be reluctant to adopt a decision tool they do not understand. The goal of this special issue is to discuss cutting‐edge research on the use of ML/AI technologies in agriculture, barriers to the adoption of these technologies, and how technologies can affect our current workforce. The papers are separated into three sections: Machine Learning within Crops, Pasture, and Irrigation; Machine Learning in Predicting Crop Disease; and Society and Policy of Machine Learning. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email