Search for: All records

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. 

By influencing soil organic carbon (SOC), cover crops play a key role in shaping soil health and hence the system's long‐term sustainability. However, the magnitude by which cover crops impacts SOC depends on multiple factors, including soil type, climate, crop rotation, tillage type, cover crop growth, and years under management. To elucidate how these multiple factors influence the relative impact of cover crops on SOC, we conducted a meta‐analysis on the impacts of cover crops within rotations that included corn (Zea maysL.) on SOC accumulation. Information on climatic conditions, soil characteristics, management, and cover crop performance was extracted, resulting in 198 paired comparisons from 61 peer‐reviewed studies. Over the course of each study, cover crops on average increased SOC by 7.3% (95% CI, 4.9%–9.6%). Furthermore, the impact of cover crop–induced increases in percent change SOC was evaluated across soil textures, cover crop types, crop rotations, biomass amounts, cover crop durations, tillage practices, and climatic zones. Our results suggest that current cover crop–based corn production systems are sequestering 5.5 million Mg of SOC per year in the United States and have the potential to sequester 175 million Mg SOC per year globally. These findings can be used to improve carbon footprint calculations and develop science‐based policy recommendations. Taken altogether, cover cropping is a promising strategy to sequester atmospheric C and hence make corn production systems more resilient to changing climates. 

Extreme weather events have cost lives and financial losses across the United States. Moreover, they are expected to increase in frequency, and this will exacerbate their impact on vulnerable sectors such as agriculture. But how farmers could adapt to extreme weather events by adopting different conservation practices has received slight attention in the literature. This study examines how farmers' perceptions of drought and flooding influence their decisions to implement conservation practices in their conventional crop fields. Out of the 350 farmer responses we received, fewer than half indicated a likelihood to adopt no-tillage/reduced tillage (43%), cover crops (40%), crop diversification (37%), and integrated crop-livestock grazing (29%). Using this data and a multivariate probit modeling framework, we show that farmers’ decisions can be partly explained by their perception of drought but not by their perception of flooding. Specifically, the perceived number of drought years significantly increases the likelihood of adopting no-tillage/reduced tillage and diversified cropping in the future. However, the number of drought years is not significantly associated with the use of cover crops and integrated crop-livestock grazing. These results suggest that the effects of extreme weather events on adoption of conservation practices as adaptive measures vary across different practices. Therefore, adaptation policies that make use of conservation practices must be tailored to farmers’ needs and priorities to be effective. 

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.