C. Marschner, Isabella Colucci, Rebecca S. Stup, Anna S. Westbrook, C. Brunharo, A. DiTommaso, M. Mesgaran
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引用次数: 0
Abstract
Understanding the timing of weed emergence is crucial to effective management. Management practices implemented too early may fail to completely control late-emerging seedlings, whereas management practices implemented too late will suffer from low efficacy. Weed emergence times reflect biological factors, such as seed dormancy and germination requirements, as well as environmental conditions. We conducted a systematic review of studies that developed models to predict weed emergence temporal patterns. We screened 1,854 studies, 98 of which were included in the final dataset. Most included studies were conducted in North America (51) or Europe (30). A wide variety of weed species (102) and families (21) were included, and many studies modeled several weeds. Grass weeds (Poaceae) were modeled most frequently (83 instances). Most weeds (40%) had base temperature T
b
values between 0 to 5 C and 38% had base water potential ψ
b
ranging from -1.0 to -0.5 MPa. Most studies used empirical parametric models, such as Weibull (40%) or Gompertz (30%) models. Non-parametric and mechanistic models were also represented. Models varied in their biological and environmental data requirements. In general, empirical parametric models based on hydrothermal time (i.e., time above base temperature and water potential thresholds) represented a good balance between ease of use and prediction accuracy. Soft computing approaches such as artificial neural networks demonstrated substantial potential in situations with complex emergence patterns and limited data availability, although they can be susceptible to overfitting. Our study also demonstrated variability in model performance and limited generalizability across species and regions. This finding underscores the need for context-specific and well-validated weed emergence models to inform management, especially in the context of climate change.
期刊介绍:
Weed Science publishes original research and scholarship in the form of peer-reviewed articles focused on fundamental research directly related to all aspects of weed science in agricultural systems. Topics for Weed Science include:
- the biology and ecology of weeds in agricultural, forestry, aquatic, turf, recreational, rights-of-way and other settings, genetics of weeds
- herbicide resistance, chemistry, biochemistry, physiology and molecular action of herbicides and plant growth regulators used to manage undesirable vegetation
- ecology of cropping and other agricultural systems as they relate to weed management
- biological and ecological aspects of weed control tools including biological agents, and herbicide resistant crops
- effect of weed management on soil, air and water.