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The cultivation of sugarcane (Saccharum officinarum L.) in the face of climate change requires robust strategies for managing pests, diseases, and weeds. This systematic review exposes critical deficiencies in current practices and underscores the need for climate-adaptive strategies. Climate change differentially influences pest behaviour, disease progression, and weed growth across various regions, yet the lack of region-specific responses impairs effective management. The review emphasizes the necessity for localized approaches that consider specific climatic conditions and the development of predictive models to anticipate pest and disease outbreaks. These models include Decision Support Systems (DSS), Support Vector Machines (SVM), Susceptible-Exposed-Infectious-Recovered (SEIR) models, Geographic Information Systems (GIS), Species Distribution Models (SDMs), Agricultural Production Systems sIMulator (APSIM), and Integrated Pest Management (IPM). Crucial strategies encompass integrated pest and disease management, adaptive breeding, precision agriculture, and ongoing innovation. Precision agriculture technologies, such as remote sensing and drones, enable early detection and prompt interventions. By adopting these adaptive measures and addressing existing research gaps, the sugarcane industry can bolster its resilience and maintain productivity amidst evolving climatic conditions.Systematic review registrationhttps://www.bmj.com/content/372/bmj.n71.
The cultivation of sugarcane (Saccharum officinarum L.) in the face of climate change requires robust strategies for managing pests, diseases, and weeds. This systematic review exposes critical deficiencies in current practices and underscores the need for climate-adaptive strategies. Climate change differentially influences pest behaviour, disease progression, and weed growth across various regions, yet the lack of region-specific responses impairs effective management. The review emphasizes the necessity for localized approaches that consider specific climatic conditions and the development of predictive models to anticipate pest and disease outbreaks. These models include Decision Support Systems (DSS), Support Vector Machines (SVM), Susceptible-Exposed-Infectious-Recovered (SEIR) models, Geographic Information Systems (GIS), Species Distribution Models (SDMs), Agricultural Production Systems sIMulator (APSIM), and Integrated Pest Management (IPM). Crucial strategies encompass integrated pest and disease management, adaptive breeding, precision agriculture, and ongoing innovation. Precision agriculture technologies, such as remote sensing and drones, enable early detection and prompt interventions. By adopting these adaptive measures and addressing existing research gaps, the sugarcane industry can bolster its resilience and maintain productivity amidst evolving climatic conditions.Systematic review registrationhttps://www.bmj.com/content/372/bmj.n71.
Adoption of diverse weed management practices is viewed as essential for slowing the spread of herbicide-resistant (HR) weeds. Yet, adoption of diverse tactics has remained low, while there has been explosive growth of resistant weeds. This study analyzes U.S.-farm-level data to identify factors affecting adoption of diverse weed management practices. This study uses directed acyclic graphs (DAGs) to consider how practice adoption is influenced by different causal pathways between farmer and farm characteristics and farmer awareness of and concern over HR weeds. This study then uses multiple regression analysis to estimate the direct and indirect pathways that influence practice adoption. Respondents relied more heavily on herbicide-based weed control methods than on mechanical or cultural methods. Concern over herbicide resistance increased the number of practices farmers adopted and the percentage of acres where farmers implemented these practices. Practice adoption was negatively associated with increasing levels of farmer risk aversion. Technological optimism—belief that new herbicides would soon be developed to counter HR weeds—discouraged diverse herbicide use practices that combat resistance, but encouraged use of some non-chemical weed control methods. Perceived weed dispersal externalities (from weed mobility) led to more diverse weed management, running counter to hypotheses that greater mobility reduces incentives for individual resistance management.
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