Linking Agronomic and Knowledge Barriers to Adoption of Conservation Practices for Nitrogen Management

Khalsa, Sat Darshan S.; Rudnick, Jessica; Lubell, Mark; Sears, Molly; Brown, Patrick H.

doi:10.3389/fagro.2022.915378

Cited by 4 publications

(7 citation statements)

References 76 publications

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“…The San Joaquin Delta and County Water Quality Coalition and East San Joaquin Water Quality Coalition in the North San Joaquin Valley, whose memberships includes over 7900 members, and the Southern San Joaquin Valley Management Practice Evaluation Program representing Water Quality Coalitions in the Southern San Joaquin Valley, whose membership is made up of over 10,700 members, were selected as regional partners for this survey effort. A description of the sampling approach was first described by Khalsa et al [9] and summarized herein. A total of 16 in-person meetings were attended from January to April in 2017 and 2018, including 7 meetings in 2017 and 9 meetings in 2018.…”

Section: Survey Approachmentioning

confidence: 99%

“…The appropriate combination of these practices to achieve desired mitigation and adaptation goals will vary across agricultural contexts and conditions [7,8] and require different degrees of investment and behavior changes by farmers [9,10]. Some management practices are more accessible (i.e., familiar, require less investment or system change), while others remain novel and more challenging to implement (i.e., costly, information-intensive, require operational transformation).…”

Section: Introductionmentioning

confidence: 99%

“…This exploratory paper aims to better understand the characteristics that distinguish High, Moderate, and Low adopters of climate-smart agriculture practices, leveraging survey data from 952 farmers across three regional water quality coalitions and diverse cropping systems in the Central Valley of California as a case study. The data presented and analyzed in this paper come from a larger research project focused on understanding farmers' adoption of diverse suites of conservation practices, which focused on farmers' be-havioral motivations, barriers to adoption, access to information sources, and attitudes and beliefs regarding agricultural impacts on the environment [9,10,19]. This paper uniquely focuses on respondents' adoption of four climate-smart practices including the mitigation practices of N budgeting and split fertilizer application and the adaptation practices of cover cropping and the use of organic matter amendments.…”

Section: Introductionmentioning

confidence: 99%

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Farmer Adoption of Climate-Smart Practices Is Driven by Farm Characteristics, Information Sources, and Practice Benefits and Challenges

Johnson¹,

Almaraz

Rudnick

et al. 2023

Sustainability

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Agriculture plays an important role in mitigation and adaptation to climate change. Yet, advances in climate-smart agriculture require a better understanding of farmer adoption. This exploratory paper uncovered differences that distinguish High, Moderate, and Low adopters of climate-smart practices. Our study utilized 952 in-person surveys of California farmers with a focus on mitigation and adaptation practices, along with farm characteristics, information sources, and practice benefits and challenges. Specifically, farmers with larger parcels were more likely to be High adopters, and farmers with access to only one water source were more likely to be Low adopters. There was no significant difference found between Moderate and High adopters’ use of any information sources. The ranking of different information sources changed between groups. Furthermore, there was no significant difference in the rate of Moderate and High adopters’ consideration of practice benefits. All groups identified practice uncertainty as the greatest challenge, with a significant difference between Moderate and High adopters. Our results demonstrate where differences occur between farmer adopter groups and by extension provide insights into where to target outreach efforts to promote the adoption of climate-smart practices in California agriculture.

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Section: Survey Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Farmer Adoption of Climate-Smart Practices Is Driven by Farm Characteristics, Information Sources, and Practice Benefits and Challenges

Johnson¹,

Almaraz

Rudnick

et al. 2023

Sustainability

Self Cite

View full text Add to dashboard Cite

show abstract

“…Additionally, five short questions about characteristics of the respondent's farm operation were also included in order to characterize adoption by crop type, farm size, and irrigation system. The data set offers granularity on barriers to adoption at a practice-specific level, but is limited by lack of data on farmer demographic or socio-behavioral characteristics (see Khalsa et al [2022] for more details on survey methods and respondent demographics). We collected 950 usable responses in total, constituting an approximate 35% response rate of meeting attendees.…”

Section: Use Of Nitrogen (N) Fertilizers Is a Distinguishing Characte...mentioning

confidence: 99%

Understanding barriers to adoption of sustainable nitrogen management practices in California

Rudnick

Khalsa

Lubell

et al. 2023

Journal of Soil and Water Conservation

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Achieving sustainability in agricultural nitrogen (N) management relies on farmers' decisions to reduce fertilizer inputs and adopt conservation management practices. Understanding the drivers and barriers to farmers' adoption of improved N management practices is critical to developing effective management and policy approaches on this intractable challenge. Existing research on farmer behavior has assumed that any barrier to adoption will result in lower practice adoption rates, without fully understanding how barriers may vary across different management practices, farm and farmer types, and stages of adoption. By leveraging two farmer survey data sets (total n > 1,900), this study diagnoses key barriers to adoption across 11 different N management practices and a large diversity of farmer and farm types across the California Central Valley. We find resource constraints, technical knowledge, and uncertainty emerge as key barrier types that differentially affect farmers at various stages of adoption. On a practice-by-practice basis, uncertainty barriers appear greatest for nonadopters of a practice, whereas practice adopters are more likely to report resource barriers. Across management practices at the farm level, farmers with higher self-reported conservation orientations are more likely to report being affected by all barrier types, as compared to their peers with lower self-reported conservation orientations. Our findings demonstrate that barriers to adoption are more complex than simply the factors that predict lower adoption, as both adopters and nonadopters experience barriers. Furthermore, factors that typically predict higher adoption, such as conservation motivation, do not insulate a farmer from facing barriers to adoption. We consider how adopters are likely to go through a learning process while moving from considering to fully implementing a new practice, during which different barriers to behavior change may be encountered. We argue that interventions intended to motivate farmer adoption of improved management practices need to take more nuanced approaches to understanding how barriers to adoption are likely to vary across stages of adoption, farm and farmer type, and specific management practices.

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“…In the last two decades, the total acreage of almond orchards in California doubled and became the state’s second largest agricultural commodity. The continued expansion of water and fertilizer-intensive tree crops, coupled with climate change, poses a threat to the long-term sustainability of almond industry, despite ongoing research and outreach efforts focused on tree crops ( Khalsa et al., 2022 ). Excessive groundwater pumping especially during drought years, for example, has caused a significant drop of aquifer’s water depths in Central Valley ( Fulton et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Tree-level almond yield estimation from high resolution aerial imagery with convolutional neural network

Tang

Sadowski²,

Chen³

et al. 2023

Front. Plant Sci.

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IntroductionEstimating and understanding the yield variability within an individual field is critical for precision agriculture resource management of high value tree crops. Recent advancements in sensor technologies and machine learning make it possible to monitor orchards at very high spatial resolution and estimate yield at individual tree level.MethodsThis study evaluates the potential of utilizing deep learning methods to predict tree-level almond yield with multi-spectral imagery. We focused on an almond orchard with the ‘Independence’ cultivar in California, where individual tree harvesting and yield monitoring was conducted for ~2,000 trees and summer aerial imagery at 30cm was acquired for four spectral bands in 2021. We developed a Convolutional Neural Network (CNN) model with a spatial attention module to take the multi-spectral reflectance imagery directly for almond fresh weight estimation at the tree level.ResultsThe deep learning model was shown to predict the tree level yield very well, with a R2 of 0.96 (±0.002) and Normalized Root Mean Square Error (NRMSE) of 6.6% (±0.2%), based on 5-fold cross validation. The CNN estimation captured well the patterns of yield variation between orchard rows, along the transects, and from tree to tree, when compared to the harvest data. The reflectance at the red edge band was found to play the most important role in the CNN yield estimation.DiscussionThis study demonstrates the significant improvement of deep learning over traditional linear regression and machine learning methods for accurate and robust tree level yield estimation, highlighting the potential for data-driven site-specific resource management to ensure agriculture sustainability.

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Linking Agronomic and Knowledge Barriers to Adoption of Conservation Practices for Nitrogen Management

Cited by 4 publications

References 76 publications

Farmer Adoption of Climate-Smart Practices Is Driven by Farm Characteristics, Information Sources, and Practice Benefits and Challenges

Farmer Adoption of Climate-Smart Practices Is Driven by Farm Characteristics, Information Sources, and Practice Benefits and Challenges

Understanding barriers to adoption of sustainable nitrogen management practices in California

Tree-level almond yield estimation from high resolution aerial imagery with convolutional neural network

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