Field Crop 2025, Vol.8, No.5, 213-221 http://cropscipublisher.com/index.php/fc 217 5.2 Irrigation model optimization based on soil moisture and weather data The traditional judgment of irrigation timing often relies on experience, but it is inadequate in responding to extreme weather. Nowadays, irrigation models can integrate data from soil moisture, weather forecasts and the physiological state of crops to more accurately predict the optimal time and amount of irrigation. It is worth mentioning that machine learning and reinforcement learning algorithms have been introduced into such systems. Compared with the previous models based on fixed rules, they perform better in terms of adaptability and prediction accuracy. This algorithm is not only adaptable to the temperature or humidity changes of the day, but also can learn the reaction characteristics of different plots over a long period of time, providing managers with more reliable decision-making basis (Bounajra et al., 2024; Madhuri et al., 2024; Chen et al., 2025). 5.3 Real-time monitoring of heat stress using remote sensing and UAVs Heat stress is not always visible. Sometimes the surface of the cotton field is calm, but in fact, the plants have long been "weak from the heat". It is difficult to detect problems in the first place by manual field patrol, especially when the area is large, it is easier to miss anomalies. However, remote sensing and unmanned aerial vehicles are different. After they fly around once, data such as canopy temperature, soil moisture and plant growth conditions are all available, and they are all high-definition images. In some cases, the system has already identified the "early signals" of heat stress even before a human response. However, merely monitoring is not enough. Once it can be integrated with the precise irrigation system, water will follow the field that is most "hot" first. This approach is more economical and effective than watering the entire field in a one-size-fits-all manner. Especially in years when heat waves are becoming increasingly common, this approach is indeed crucial for maintaining production (Morchid et al., 2024; Shaikh and Bansod, 2024). 6 Case Studies: Field Practices for Managing Drought and Heat Stress 6.1 Precision water-saving cultivation models in arid cotton areas of Northwest China Insufficient water is not a new problem in cotton-growing areas like Xinjiang. Farmers have long been accustomed to being thrifty under limited conditions. So-called precise water conservation did not have a mature model from the very beginning; most of the time, it was a case of feeling one's way forward. Operations like delaying the first irrigation and allowing plants to adapt to a brief drought during the seedling stage may seem simple, but they are indeed useful for enhancing resistance. Studies have simulated that as long as irrigation is properly arranged, water conservation can approach 57%, while production is not significantly affected (Wang et al., 2023; Lin et al., 2024). Of course, the issue of water is often accompanied by insufficient heat. Therefore, many places have tried to switch to early-maturing and cold-tolerant cotton varieties, and at the same time appropriately adjust the sowing time, hoping to find a more stable balance point in the context of both water and temperature shortages (Zhang et al., 2024). 6.2 Management strategies for heat stress adaptation in hot and dry cotton regions of India Some cotton-growing areas in India are so hot that it's hard to breathe. Coupled with frequent droughts, the pressure on crops can be imagined. Faced with this situation, agricultural management has also begun to make adjustments. For instance, plastic film mulching is used to lock in moisture and lower the temperature, while foliar spraying of antioxidants such as proline or betaine helps crops alleviate the damage caused by high temperatures. Meanwhile, by rationally supplementing nutrients, the physiological state of plants can also be stabilized to a certain extent (Aiswarya et al., 2025). Of course, if these measures are not combined with the drought-resistant varieties selected and bred, their effects will be limited. Research shows that when the two are combined, both fiber quality and yield loss can be significantly controlled (EL Sabagh et al., 2020). 6.3 Integrated application of smart monitoring and stress-resilient breeding in the Southern U.S. cotton belt In the major cotton-growing areas of the southern United States, the days of relying on "experience-based farming" are gradually passing. Nowadays, there may be many soil moisture sensors hidden in the plots, and the drones flying in the air are not just taking photos - they are collecting real-time data on temperature, humidity and crop conditions (Khalequzzaman et al., 2023). However, relying solely on these "eyes" is not enough. Some growers also combine plant growth regulators, such as methylpiperium, to adjust the growth rhythm of cotton and
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