Field Crop 2025, Vol.8, No.4, 176-186 http://cropscipublisher.com/index.php/fc 180 Combinations such as water-scarce irrigation combined with foliar iron spraying, or simultaneous irrigation with the recommended amount of fertilizer, often result in higher chlorophyll content, smoother stomatal conductance, and an overall improvement in metabolic levels. Not only that, protein synthesis is also more active, and ultimately good results can be seen in both yield and nutrient absorption. If asked why it is so obvious, many people attribute it to the changes in root vitality and the rhizosphere environment. 5.2 Fertigation techniques for synchronized nutrient-water delivery In drip irrigation or underground irrigation systems, water and nutrients are precisely delivered to the roots at the same time. This "synchronous operation" is very effective for soybeans. Compared with the old-fashioned methods of spreading fertilizer or flooding, this approach is more economical and efficient. For instance, even a moderate amount of nitrogen fertilizer (such as 20 to 40 kilograms per hectare), combined with underground irrigation, can increase soybean yields by over 80% compared to the control group without irrigation or application. Studies have found that in intercropping systems and water-scarce areas, as long as the field water holding capacity is controlled at 80% and combined with a reasonable amount of nitrogen fertilizer, both yield and water and fertilizer utilization rate can reach a good level (Dou et al., 2022; Dwivedi et al., 2020; Hyuk et al., 2023; Luo et al., 2023). Of course, this approach must also be based on "precise matching"; otherwise, over-injection will be counterproductive. 5.3 Risks of nutrient leaching and runoff under over-irrigation Excessive irrigation is an old problem. When the water goes down, the fertilizer follows, especially the nitrate. Once it flows out of the root zone, not only will plants fail to absorb it, but it may also pollute water bodies and waste resources in vain. A considerable number of field experiments and percolation instrument monitoring data have indicated that the amount of nitrogen loss significantly increases under high irrigation rates or heavy rain weather, and this loss varies from year to year, greatly influenced by management methods (Lee et al., 2017; Li et al., 2018; Azad et al., 2020). Coarse-grained soil is particularly prone to problems. Although drip irrigation or an optimized irrigation plan can reduce some losses, if fertilization is too vigorous or irrigation control is inadequate, phosphorus and potassium may still be carried away. So, it's not that you can't irrigate, but the key is not to overdo it or apply too much. To ensure production, you must first preserve the nutrients in the soil. 6 Advances in Precision Agriculture Tools for Soybean 6.1 Remote sensing and UAVs for monitoring crop water and nutrient status Whether farmland is short of water or not and whether plants have sufficient nutrients can no longer be judged solely by human eyes. Nowadays, satellites, hyperspectral and multispectral sensors, and even small unmanned aerial vehicles can all come in handy. These remote sensing technologies can provide a lot of key data, such as vegetation index, chlorophyll content, soil moisture status, crop maturity, etc. Through these data, managers can identify problems earlier and intervene earlier. Among them, the flexibility of drones is particularly worth mentioning. It is not as weather-restricted as satellites and has a lower cost, making it more suitable for precise field management. Whether it is to identify local areas lacking water or fertilizer or to demarcate different management zones, targeted fertilization or irrigation becomes easier to achieve (Sishodia et al., 2020; Omia et al., 2023; Sangeetha et al., 2024). Of course, data alone is not enough. When multi-source remote sensing information is combined with advanced data analysis methods, the accuracy of output prediction is significantly improved, and management decisions become more confident (Lu et al., 2024; Shi et al., 2024). 6.2 Decision support systems and AI-based irrigation-fertilization scheduling Not everyone can understand those sensor data, nor does everyone have the time to keep an eye on the weather and soil changes every day. At this point, decision support systems (DSS) and artificial intelligence (AI) become particularly practical. They can automatically integrate data sent back by remote sensing, field records and various sensors to help users "make judgments". Compared with traditional models, AI, especially deep learning frameworks, is better at handling disordered and multi-variable time series data. For example, how the output changes and when it is more appropriate to apply fertilizer or water can all be predicted by the model (Singh, 2024; Mehedi et al., 2024). Many DSS are still Web platforms. Farmers only need to log in to generate variable
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