Triticeae Genomics and Genetics, 2025, Vol.16, No.3, 110-119 http://cropscipublisher.com/index.php/tgg 112 2.3 Limitations of controlled-environment studies vs. field-based evaluations No matter how realistic the drought simulation in the laboratory is, it can never imitate the "temper" in the fields. Studies under controlled conditions have indeed provided us with a considerable understanding of the drought response mechanism. However, once it comes to real fields, variables such as wind, rain, soil structure, and even insects and microorganisms complicate matters (Sallam et al., 2019). So, relying solely on laboratory data is not enough. To truly determine whether a variety is drought-tolerant or not, it is still necessary to observe its performance in the field. The performance of QTL and specific traits is more convincing in real-world contexts (Pantha et al., 2024). Of course, field experiments are not easy either. They are not only time-consuming and labor-intensive, but also easily disturbed by weather or other uncontrollable factors. So, at present, it seems that combining controlled research with field assessment might be a comprehensive and practical approach. 3 Principles of QTL Mapping under Field Conditions 3.1 Approaches to phenotyping drought-related traits in natural environments In the field research of the wheat tribe, to figure out which traits are related to drought resistance, the first step is actually to measure clearly whether they are growing well or not. Traits such as yield, plant height, panicle emergence time and root length usually need to be measured repeatedly. They should be examined in different years and different plots. Only in this way is it possible to catch those variations that "evade drought manifestations" (Xu et al., 2023). Especially for some more sensitive physiological indicators, such as leaf water content, chlorophyll level, canopy temperature, and whether the leaves are curled, these indicators must be measured at key developmental stages. To minimize the interference brought by the field environment as much as possible, the experimental design is generally made into repetitive plots and a unified observation standard is adopted. Nowadays, high-throughput phenotypic platforms-such as SPAD meters for measuring chlorophyll or soil column methods for observing roots-are increasingly being used to enhance the efficiency and accuracy of detection. These methods are not complicated, but in complex field environments, they can help us more clearly "see" those subtle genetic differences. 3.2 Statistical models and experimental designs for QTL detection in the field In the field research of the wheat tribe, to figure out which traits are related to drought resistance, the first step is actually to measure clearly whether they are growing well or not. Traits such as yield, plant height, panicle emergence time and root length usually need to be measured repeatedly. They should be examined in different years and different plots. Only in this way is it possible to catch those variations that "evade drought manifestations" (Xu et al., 2023). Especially for some more sensitive physiological indicators, such as leaf water content, chlorophyll level, canopy temperature, and whether the leaves are curled, these indicators must be measured at key developmental stages. To minimize the interference brought by the field environment as much as possible, the experimental design is generally made into repetitive plots and a unified observation standard is adopted. Nowadays, high-throughput phenotypic platforms-such as SPAD meters for measuring chlorophyll or soil column methods for observing roots-are increasingly being used to enhance the efficiency and accuracy of detection. These methods are not complicated, but in complex field environments, they can help us more clearly "see" those subtle genetic differences. 3.3 Challenges in environmental heterogeneity and genotype-by-environment interactions Ultimately, there are too many variables in the field environment, which is precisely the most headache-inducing aspect for QTL positioning. Even if you design it thoroughly, as long as there are differences in weather, soil and management methods, the originally "visible" genetic effects may be obscured (Milner et al., 2016). Moreover, the interaction between G and E is also quite common. Some QTLS are quite obvious in one place but become "silent" in a different environment (Su et al., 2018). To deal with these interferences, researchers usually choose a strategy of multi-point repetition, large sample size, and long-term tracking, and combine it with more robust statistical models to strip the "noise" out of the signal as much as possible. Although there are many challenges, to screen out truly drought-tolerant QTLS with breeding value, it still depends on solid field testing.
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