Bt Research 2025, Vol.16, No.6, 234-241 http://microbescipublisher.com/index.php/bt 236 crops are grown has changed and whether the degree of pest infestation has worsened (Hughes and Andersson, 2017; Blanquart, 2019). However, the effects of these assessment methods may not be the same on different crops and different pests. How to unify the standards and how to interpret the data are quite tricky in actual operation. 3.2 Population genetics underlying resistance development Why are some pests becoming increasingly "indestructible"? The problem might lie in their genes. Under the long-term cultivation of Bt crops, some originally rare resistance genes (such as those controlling toxin receptors or metabolic detoxification) will gradually accumulate (Toprak et al., 2011; Furusawa et al., 2018). However, there are exceptions - some resistance alleles are retained even without the selection pressure of Bt due to the compensation mechanism generated during the population adaptation process (Yu et al., 2025). This makes the evolution of resistance not develop in a single line, but is interwoven and influenced by multiple factors such as mutation rate, gene flow and adaptation cost. Understanding these mechanisms from a genetic perspective does indeed help us determine whether resistance will spread and at what rate. 3.3 Resistance dynamics prediction models and decision-making support To truly intervene in the spread of resistance in advance, it is difficult to be thorough merely by relying on experience. Many teams have attempted to combine mathematical modeling with actual data to simulate the path of resistance development. These models incorporate variables such as mutation sources, selective stress intensity, refuge strategies, and pest migration patterns to assist in designing planting strategies for Bt crops and even the timing of policy intervention (Figure 1) (Spohn et al., 2019). Of course, it doesn't mean that the model can precisely calculate when resistance will occur. After all, there are too many uncontrollable factors such as genetic superiority and environmental changes. However, when combined with the existing observational data, the reference value of the model is still quite significant (Hughes and Andersson, 2017; Blanquart, 2019). For adversarial management, these simulation tools have become increasingly important "auxiliary brains". Figure 1 Mutational profiles of 38 AMP-resistant lines (Adopted from Spohn et al., 2019) 4 Molecular and Biotechnological Approaches to Delay or Overcome Resistance 4.1 Gene pyramiding strategies: stacking multiple Bt genes When it comes to dealing with pests, relying on just one type of Bt toxin is often not sufficient. Over time, pests will always be able to "figure out the pattern" and develop resistance. But what if multiple Bt genes are combined into one crop? This is what is called the "gene pyramid" strategy. Different Bt proteins act on different targets. It is
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