Field Crop 2025, Vol.8, No.3, 126-138 http://cropscipublisher.com/index.php/fc 131 water use efficiency increased instead. For instance, in a certain mung bean variety, the Pn only dropped by 15%, while in the control variety, it decreased by over 30% (Zhang and Shi, 2018). In terms of osmotic regulation, the proline and soluble sugar content of drought-tolerant varieties have significantly increased. For instance, the proline content of the soybean "Four Grains Yellow" has risen by more than three times, indicating that its ability to regulate osmosis is stronger. In the antioxidant system, the activities of SOD and POD in drought-tolerant varieties are relatively high, while the increase in MDA is not significant. However, for sensitive varieties like Heinong 44, the MDA content is more than twice as much as before, and the enzyme activity keeps dropping (Ahmad et al., 2022). In terms of root systems, drought-tolerant ones generally have deeper roots, more fine roots, higher root trunk weight and root-crown ratio, and some can even maintain a decent number of root nodules (Vadez et al., 2008). Overall, drought-resistant varieties do perform better in water retention, photosynthesis, osmotic regulation, antioxidation, and root water absorption. This should also be the reason why their yields are more stable. 4.3 High-throughput and remote sensing phenotypic data acquisition Traditionally, although physiological data can be obtained through manual measurement, the timeliness and spatial representativeness are not very satisfactory. So this time we used some remote sensing and high-throughput methods to assist in monitoring. For instance, for soybeans and peanuts, we use drones to conduct multi-spectral flights every two weeks from emergence to grain formation, extracting NDVI and moisture index, which are then used to calculate leaf area and water content. It was found that the NDVI of drought-tolerant varieties was 10% to 20% higher than that of sensitive varieties under drought conditions, and the decline in leaf area index was also less, approximately 10%, while sensitive varieties might have a decrease of more than 30% (Balota and Oakes, 2017). In addition, infrared thermal imaging shows that the canopy temperature of drought-tolerant varieties is actually 1 to 2 degrees higher, indicating that their stomata close more promptly and save water. In Gansu Province, we also used a high-throughput platform to quickly test the leaves and root systems of some soybeans. From the perspective of fluorescence parameters, the Fv/Fm of drought-resistant varieties decreased less, and the photosystem was less damaged. Root scanning is indeed much faster than manual measurement. Overall, these remote sensing and high-throughput results are basically consistent with those measured manually, and they have a larger coverage. Preliminary analysis shows that NDVI and yield are still positively correlated (r≈0.7), indicating that it is somewhat helpful for estimating yields under drought conditions (Carvalho et al., 2015). However, we mainly rely on manual measurement, and remote sensing only plays an auxiliary verification role. 5 Data Analysis and Statistical Methods 5.1 Analysis methods for output stability and adaptability To clarify whether the yields of different varieties are stable and their adaptability is strong, we conducted variance analysis and stability assessment on the yield data of multiple experimental sites over two years. In fact, the impact of the environment is even greater than that of the variety itself, accounting for more than half of the variations. For instance, in the case of soybeans, location differences account for 55.3%, while genotypes themselves make up less than 6%. However, the interaction between varieties and the environment is also quite obvious, accounting for about 38%. This indicates that although the environment is dominant, it is also very important that varieties perform differently in different places (Firew et al., 2019). We used the AMMI model and the GGE bigraph to analyze this interaction, and the results were quite intuitive: the pilot was roughly divided into two groups, and the best-performing varieties in each group were not the same. For instance, "Xu 9416-8" had the highest yield in one group, while "Liu Dou 108" performed better in another group. In terms of stability, the main parameters examined were CV%, regression coefficient bi and σ²_d. A small CV indicates a stable yield. A bi close to 1 is considered a variety with wide adaptability. A CV less than 1 May be more resilient to adverse conditions, but it is not outstanding under high water and fertilizer conditions. A CV greater than 1 is suitable for high-yield environments, but it is prone to yield decline when encountering drought. Like "Handou 13", which has a small σ²_d and bi close to 1, it is a type that is both high-yielding and stable.
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