skip to main content

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 11:00 PM ET on Thursday, February 13 until 2:00 AM ET on Friday, February 14 due to maintenance. We apologize for the inconvenience.


Title: Factors affecting farmer perceived challenges towards precision agriculture
Precision Agriculture (PA) manages field heterogeneities and enables informed site-specific management. While PA helps improve farming efficiency and profitability, challenges prior to and following PA adoption can prevent many farmers from widely using it. This paper aims to understand producers’ challenge perceptions using 1119 survey responses from U.S. Midwest farmers. The majority (59%) of respondents have adopted at least one PA technology, while the minority (14%) had not adopted any PA technologies. Cost (equipment and service fee), brand compatibility, and data privacy concerns topped other concerns from the average producer’s point of view. Among all producers, 60% regarded PA equipment and service fee as too high, followed by 50% who viewed brand compatibility and data privacy as their major concerns. Producers at more advanced adoption stage indicated reduced concerns in most categories. Yet, there were similar concerns towards data privacy issue regardless of the adoption status. Furthermore, brand compatibility issue is more of a concern for adopters than for non-adopters. Estimation results from partial proportional odds (PPO) models show that factors that frequently affect producers’ perceived challenges include adoption status, cropland acres, age, education, information sources, farming goals, soil characteristics, and region variables. Findings from this study can aid PA stakeholders in identifying target groups, tailoring future development, research, and outreach efforts, and ultimately promoting efficient PA usage on a broader scale.  more » « less
Award ID(s):
2119753
PAR ID:
10479197
Author(s) / Creator(s):
; ;
Publisher / Repository:
Springer Link
Date Published:
Journal Name:
Precision Agriculture
Volume:
24
Issue:
6
ISSN:
1385-2256
Page Range / eLocation ID:
2456 to 2478
Subject(s) / Keyword(s):
Adoption Farmer survey Patial proportional odds model Perceived challenges Precision agriculture
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    The use of intelligent decision support systems (DSS) in precision farming provides an opportunity to improve agricultural recommendations and reduce the impacts of agriculture on the environment. Despite the benefits offered by DDS, many farmers remain skeptical of using these hardware and software tools, and their adoption rates have remained low. A survey of 312 South Dakota farmers examined the barriers and opportunities for their engagement with DSS. Exploratory factor analysis was used to analyze 13 Likert scale survey items that probed farmers’ concerns about DSS. Factor loadings indicated that farmers’ concerns are related to high cost, insufficient knowledge, lack of confidence, and cyber security and privacy. A latent profile analysis (LPA) method was used to classify respondents into profiles or groups based on their dimensions of concerns (cost, knowledge, confidence, and security). Results of the LPA revealed that the sample of farmers could be grouped into four distinct profiles that ranged from low to high confidence in the use of DSS for agronomic decision‐making. Giving attention to farmer comfort/concern profiles allows for a more inclusive and better targeted engagement with farmers and potentially increase the adoption of PA. This knowledge can be vital for technology developers, policymakers, and extension services who are keen to promote PA usage among large‐, medium‐, and small‐scale farmers in the United States.

     
    more » « less
  2. While conservation practices promote soil health and reduce the negative environmental effects from agricultural production, their adoption rates are generally low. To facilitate farmer adoption, we carried out a survey to identify potential challenges faced by farmers regarding conservation tillage and cover crop adoption in the western margin of the US Corn Belt. We found farmers' top two concerns regarding conservation tillage were delayed planting, caused by slow soil warming in spring, and increased dependence on herbicide and fungicides. Narrow planting window and lack of time/labor were perceived by farmers as the two primary challenges for cover crop adoption. Some sense of place factors, including the commonly included dimensions of attachment, identity and dependence, played a role in farmers' perceived challenges. For example, respondents more economically dependent on farming perceived greater challenges. We found that farmers' challenge perceptions regarding reduced yield and lack of time/labor significantly decreased as years of usage increased, implying that time and experience could dilute some challenges faced by farmers. Our findings indicate that social network use, technical guidance and economic subsidies are likely to address the concerns of farmers and facilitate their adoption of conservation practices.

     
    more » « less
  3. Precision Agriculture (PA) technologies are well known to be useful in addressing field heterogeneities and enabling informed site-specific management decisions. While profitability is the foremost factor considered by farmers when making PA adoption decisions, information in this regard is lacking from the farmers' perspective. This paper analyzed 1119 farmer responses from a 2021 survey conducted in four states along the western margins of the U.S. Midwest. Our findings show that while most (around 60%) non-adopters indicate that they are unaware of PA profit change, adopters are likely to rate a major profit increase. About two thirds of adopters rated at least a 5% increase in profitability towards variable rate (VR) fertilizer application (72%), VR seed application (68%), and automatic section control (66%). We modeled farmers' profit change subsequent to PA adoptions. Our regression results demonstrate that the profits from PA usage increase over time and that use of conservation practices likely influences PA profitability in a positive way. As soil quality and weather factors also affect profit ratings, it would be beneficial to compare and demonstrate profitability potential of various PA technologies on a regional basis and tailor the promotion efforts to farmers most likely to benefit from them. 
    more » « less
  4. Abstract

    Artificial intelligence (AI) represents technologies with human‐like cognitive abilities to learn, perform, and make decisions. AI in precision agriculture (PA) enables farmers and farm managers to deploy highly targeted and precise farming practices based on site‐specific agroclimatic field measurements. The foundational and applied development of AI has matured considerably over the last 30 years. The time is now right to engage seriously with the ethics and responsible practice of AI for the well‐being of farmers and farm managers. In this paper, we identify and discuss both challenges and opportunities for improving farmers’ trust in those providing AI solutions for PA. We highlight that farmers’ trust can be moderated by how the benefits and risks of AI are perceived, shared, and distributed. We propose four recommendations for improving farmers’ trust. First, AI developers should improve model transparency and explainability. Second, clear responsibility and accountability should be assigned to AI decisions. Third, concerns about the fairness of AI need to be overcome to improve human‐machine partnerships in agriculture. Finally, regulation and voluntary compliance of data ownership, privacy, and security are needed, if AI systems are to become accepted and used by farmers.

     
    more » « less
  5. Precision farming enables agricultural management decisions to be tailored spatially and temporally. Site-specific sensing, sampling, and managing allow farmers to treat a field as a heterogeneous entity. Through targeted use of inputs, precision farming reduces waste, thereby cutting both private variable costs and the environmental costs such as those of agrichemical residuals. At present, large farms in developed countries are the main adopters of precision farming. But its potential environmental benefits can justify greater public and private sector incentives to encourage adoption, including in small-scale farming systems in developing countries. Technological developments and big data advances continue to make precision farming tools more connected, accurate, efficient, and widely applicable. Improvements in the technical infrastructure and the legal framework can expand access to precision farming and thereby its overall societal benefits. 
    more » « less