Factors That Influence On-Farm Decision-Making: Evidence from Weed Management

Pasture persistence and performance, and associated issues such as black beetle, are of central concern to dairy farmers. The Pasture Renewal Survey 2010 aimed to better understand farmers' confidence in their ability to make informed decisions on their pasture renewal practices, their satisfaction with the success of this decision-making and the performance of their renewed pastures over time. In addition, the survey investigated their attitudes to information sources and what barriers they saw to improving pasture performance on farm. A postal and online survey elicited responses from 776 dairy farmers in the Waikato and Bay of Plenty regions. The four main findings of the work were: 1. Farmers are more confident of their ability to make appropriate on-farm management decisions for renewed pasture than they are of their ability to choose appropriate cultivars and endophyte. 2. Farmers, while generally satisfied with their own success in renewing pasture, reported decreasing levels of satisfaction with renewed pastures over the 3 successive years following renewal. 3. Farmers do not rate information sources very highly in terms of their usefulness in relation to pasture renewal. 4. Weather-related issues and pest-related issues (particularly black beetle) were the most commonly identified barriers to improving pasture performance. Keywords: farmer confidence, farmer satisfaction, information sources, pasture renewal.

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Convenience Sample of On-Farm Research Cooperators Representative of Wisconsin Farmers

Weed Technology ◽

10.1614/wt-08-083.1 ◽

2009 ◽

Vol 23 (2) ◽

pp. 300-307 ◽

Cited By ~ 4

Author(s):

Edward C. Luschei ◽

Clarissa M. Hammond ◽

Chris M. Boerboom ◽

Pete J. Nowak

Keyword(s):

Weed Management ◽

Selection Criteria ◽

Community Dynamics ◽

Multivariate Analyses ◽

Theoretical Argument ◽

Convenience Sample ◽

Research Areas ◽

On Farm ◽

Unknown Bias ◽

Management Behaviors

Researchers interested in describing or understanding agroecological systems have many reasons to consider on-farm research. Yet, despite the inherent realism and pedagogical value of on-farm studies, recruiting cooperators can be difficult and this difficulty can result in so-called “convenience samples” containing a potentially large and unknown bias. There is often no formal justification for claiming that on-farm research results can be extrapolated to farms beyond those participating in the study. In some sufficiently well-understood research areas, models may be able to correct for potential bias; however, no theoretical argument is as persuasive as a direct comparison between a randomized and a convenience sample. In a 30-cooperator on-farm study investigating weed community dynamics across the state of Wisconsin, we distributed a written survey probing farmer weed management behaviors and attitudes. The survey contained 59 questions that overlapped a large, randomized survey of farmer corn pest management behavior. We compared 187 respondents from the larger survey with the 18 respondents from our on-farm study. For dichotomous response questions, we found no difference in response rate for 80% of the questions (α = 0.2, β > 0.5). Differences between the two groups were logically connected to the selection criteria used to recruit cooperators in the on-farm study. Similarly, comparisons of nondichotomous response questions did not differ for 80% of the questions (α = 0.05, β > 0.9). Exploratory multivariate analyses failed to reveal differences that might have been hidden from the marginal analyses. We argue that our findings support the notion that the convenience samples often associated with on-farm research may be representative of the more general class of farms, despite lack of bias protection provided by truly randomized designs.

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On-farm evaluation of an improved rice variety and integrated weed management techniques for improving the productivity of deepwater rice

International Rice Research Notes ◽

10.3860/irrn.v34i0.1066 ◽

2009 ◽

Vol 34 (0) ◽

Author(s):

S Saha

Keyword(s):

Weed Management ◽

Rice Variety ◽

Integrated Weed Management ◽

Deepwater Rice ◽

Management Techniques ◽

On Farm

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An online decision support tool to evaluate ecological weed management strategies

Weed Science ◽

10.1017/wsc.2019.21 ◽

2019 ◽

Vol 67 (4) ◽

pp. 463-473

Author(s):

Douglas Bessette ◽

Robyn Wilson ◽

Christian Beaudrie ◽

Clayton Schroeder

Keyword(s):

Decision Support ◽

Soil Quality ◽

Weed Management ◽

Decision Support Tool ◽

The United States ◽

Support Tool ◽

Organic Farmers ◽

Ecological Weed Management ◽

On Farm

AbstractWeeds remain the most commonly cited concern of organic farmers. Without the benefit of synthetic herbicides, organic farmers must rely on a host of ecological weed management (EWM) practices to control weeds. Despite EWM’s ability to improve soil quality, the perceived rate of integrated EWM strategy adoption remains low. This low adoption is likely a result of the complexity in designing and evaluating EWM strategies, the tendency for outreach to focus on the risks of EWM strategies rather than their benefits, and a lack of quantitative measures linking the performance of EWM strategies to farmers’ on-farm objectives and practices. Here we report on the development and deployment of an easy-to-use online decision support tool (DST) that aids organic farmers in identifying their on-farm objectives, characterizing the performance of their practices, and evaluating EWM strategies recommended by an expert advisory panel. Informed by the principles of structured decision making, the DST uses multiple choice tasks to help farmers evaluate the short- and long-term trade-offs of EWM strategies, while also focusing their attention on their most important objectives. We then invited organic farmers across the United States, in particular those whose email addresses were registered on the USDA’s Organic Research Integrity Database, to engage the DST online. Results show considerable movement in participants’ (n = 45) preferences from practices focused on reducing weeding costs and labor in the short term to EWM strategies focused on improving soil quality in the long term. Indeed, nearly half of those farmers (48%) who initially ranked a strategy composed of their current practices highest ultimately preferred a better-performing EWM strategy focused on eliminating the weed seedbank over 5 yr.

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Identifying Barriers to Implementing Pain Management for Piglet Castration: A Focus Group of Swine Veterinarians

Animals ◽

10.3390/ani10071202 ◽

2020 ◽

Vol 10 (7) ◽

pp. 1202 ◽

Cited By ~ 1

Author(s):

Brooklyn Wagner ◽

Kenneth Royal ◽

Rachel Park ◽

Monique Pairis-Garcia

Keyword(s):

Decision Making ◽

Pain Management ◽

Focus Group ◽

Production Systems ◽

The United States ◽

Swine Production ◽

Factors Influencing ◽

Audio Recordings ◽

On Farm ◽

And Training

Surgical castration is a painful husbandry procedure performed on piglets in the United States (US) to improve meat quality. Veterinarians play a crucial role in developing pain management protocols. However, providing pain management for castration is not common practice in US swine production systems. Therefore, the objective of the present study is to identify factors influencing swine veterinarian decision-making in regard to pain management protocols for piglet castration using focus group methodologies. Swine veterinarians (n = 21) were recruited to participate in one of three focus groups. Audio recordings were transcribed verbatim and analyzed by two independent coders who identified three areas of focus, including (1) the lack of approved products validated for efficacy, (2) economic limitations and challenges, and (3) deficient guidelines and training for veterinarians to develop protocols. Although participating veterinarians acknowledged the importance of pain management from an animal welfare standpoint, these barriers must be addressed to ensure that castration pain can be successfully mitigated on-farm.

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Spatial analysis of yield monitor data: case studies of on-farm trials and farm management decision making

Precision Agriculture ◽

10.1007/s11119-008-9072-2 ◽

2008 ◽

Vol 9 (5) ◽

pp. 269-283 ◽

Cited By ~ 26

Author(s):

Terry W. Griffin ◽

Craig L. Dobbins ◽

Tony J. Vyn ◽

Raymond J. G. M. Florax ◽

James M. Lowenberg-DeBoer

Keyword(s):

Decision Making ◽

Spatial Analysis ◽

Case Studies ◽

Farm Management ◽

Management Decision ◽

Yield Monitor ◽

Management Decision Making ◽

On Farm ◽

Monitor Data

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Self identified research needs of New York organic farmers

American Journal of Alternative Agriculture ◽

10.1017/s0889189300001740 ◽

1987 ◽

Vol 2 (3) ◽

pp. 107-113 ◽

Cited By ~ 15

Author(s):

Brian P. Baker ◽

Douglas B. Smith

Keyword(s):

New York ◽

Weed Management ◽

New York State ◽

Organic Production ◽

Extension Agents ◽

Insect Management ◽

Farm Work ◽

Organic Farmers ◽

Insufficient Time ◽

On Farm

AbstractA survey of organic farmers in New York State identified problems in need of university research. Weed management was the most frequently mentioned problem by far, identified as significant by two-thirds of the organic farmers. Only a few other problems were listed as significant, including insufficient time for farm work, lack of markets, low prices, and lack of appropriate tools. These were cited by more than a third of the farmers. Drought, insect management, and a lack of a dependable supply of labor were cited by about one-third of the respondents. The survey also examined organic farmers' information sources. They do not use conventional sources of agricultural information, such as the extension service and conventional agricultural media, as much as books, magazines, and newsletters on organic f arming, other organic f armers, and on-farm experiments. Many respondents noted that local extension agents did not know very much about non-chemical solutions to organic production problems. They considered University Extension to be accessible, but not very useful in solving problems specific to organic farming, and had many suggestions to improve Land Grant research in organic agriculture.

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Risk-Efficiency Criteria for Evaluating Economics of Herbicide-Based Weed Management Systems in Corn

Weed Technology ◽

10.1614/wt-03-152r2 ◽

2004 ◽

Vol 18 (3) ◽

pp. 687-697 ◽

Cited By ~ 4

Author(s):

Thomas R. Hoverstad ◽

Jeffrey L. Gunsolus ◽

Gregg A. Johnson ◽

Robert P. King

Keyword(s):

Decision Making ◽

Weed Control ◽

Stochastic Dominance ◽

Weed Management ◽

Crop Production ◽

Management Systems ◽

Management Decision ◽

Pass System ◽

Application Systems ◽

Mean Variance

Evaluation of economic outcome associated with a given weed management system is an important component in the decision-making process within crop production systems. The objective of this research was to investigate how risk-efficiency criteria could be used to improve herbicide-based weed management decision making, assuming different risk preferences among growers. Data were obtained from existing weed management trials in corn conducted at the University of Minnesota Southern Research and Outreach Center at Waseca. Weed control treatments represented a range of practices including one-pass soil-applied, one-pass postemergence, and sequential combinations of soil and postemergence herbicide application systems. Analysis of risk efficiency across 23 herbicide-based weed control treatments was determined with the mean variance and stochastic dominance techniques. We show how these techniques can result in different outcomes for the decision maker, depending on risk attitudes. For example, mean variance and stochastic dominance techniques are used to evaluate risk associated with one- vs. two-pass herbicide treatments with and without cultivation. Based on these analyses, it appears that a one-pass system is preferred by a risk-averse grower. However, we argue that this may not be the best option considering potential changes in weed emergence patterns, application timing concerns, etc. The techniques for economic analysis of weed control data outlined in this article will help growers match herbicide-based weed management systems to their own production philosophies based on economic risk.

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