Legume Genomics and Genetics 2024, Vol.15, No.6, 303-314 http://cropscipublisher.com/index.php/lgg 306 periods (Datta et al., 2017). Effective identification and understanding of these common weeds are crucial for developing targeted management strategies. Figure 1 General diagram showing the key elements of the simulation model, displaying howE. davidii competes with soybean over a crop season (Adopted from Molinari et al., 2022) Image caption: On the left, a thermal time scale used to guide the weed life-cycle development is shown. A thermal and chronological time scale for crop-growth development is displayed at the base of the diagram. At the top, the fallow and crop cycle are schematized, including the most important indexes. The weed life cycle is represented in a simple way by the most representative stages (Ws,t): dormant and quiescent seeds in the seed bank; cotyledonal (cotyledons); early vegetative (2 to 4 true leaves); advanced vegetative (6 true leaves to branching); and reproductive (flowering and fruiting) (Adopted from Molinari et al., 2022) 4.2 Integrated weed management approaches Integrated Weed Management (IWM) combines multiple strategies to control weed populations while minimizing environmental impact and maintaining crop yield. Key components of IWM in soybean include Cultural practices: Adjusting row spacing and seeding rates can enhance crop competitiveness against weeds. Narrow row spacing and higher seeding densities promote early canopy closure, which suppresses weed growth by limiting light availability (Datta et al., 2017; Arsenijevic et al., 2021). Mechanical control: Techniques such as rotary hoeing and between-row cultivation can reduce weed biomass significantly. These methods can be combined with reduced herbicide applications to maintain effective weed control while minimizing chemical inputs. Chemical control: The use of pre-emergence (PRE) herbicides, such as flumioxazin, metribuzin, and pyroxasulfone, can delay weed emergence and reduce competition. However, the timing and selection of herbicides must be carefully managed to avoid negative impacts on crop yield (Sikka et al., 2013). Cover crops: Interseeding cover crops after soybean establishment can provide additional weed suppression. However, it is essential to select cover crops that do not compete with the soybean itself (Datta et al., 2017). Decision support Systems: Simulation models can aid in evaluating different IWM strategies by predicting outcomes such as crop yield, weed competition, and economic returns. These models help in making informed decisions about the most effective and sustainable weed management practices (Molinari et al., 2022). 4.3 Effects of weed competition on soybean yield Weed competition is a major limiting factor for soybean yield. Studies have shown that weed infestation can lead to yield losses ranging from 53% to 56% if not managed appropriately (Daramola, 2020). The critical period for
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