Rice is a staple grain crop extensively cultivated in Fujian Province, China. This study examined the impact of high-temperature stress on rice yield and its components, focusing on four representative rice varieties, including early and middle rice grown in Fujian Province. Results indicate significant yield losses, with the most severe reduction of 60.8% observed during the flowering stage of early rice and over 40% during the meiosis and flowering stages of middle rice. High-temperature stress primarily affects early rice yield more at the flowering stage than at the grain-filling stage, whereas in middle rice, it is more severe at the meiosis stage than at the flowering stage. Leveraging historical climatic data spanning the past 20 years, a simulation model for high-temperature stress on rice yield was developed to assess disaster-induced yield loss rates, aiming to enhance prevention and disaster damage assessment for rice under high-temperature stress. Application of the model to four rice planting sites in Fujian Province revealed contrasting temporal changes between loss rates and meteorological yield, with middle rice experiencing more severe damage than early rice. The model’s effectiveness is validated by the strong correspondence between yield loss rate and meteorological yield across different regions, highlighting its robust simulation capabilities.

This study investigated how nitrogen fertilizer management influences the yield and grain quality of two rice cultivars, Nanjing 9108 (a late-maturing medium japonica) and Ming 1 Youzhenzhan (a three-line indica hybrid). Three field experiments were conducted to assess different nitrogen application strategies, including total nitrogen reduction, panicle-stage nitrogen reduction, and substitution of chemical fertilizer with compound fertilizer. The experiments analyzed changes in rice nitrogen uptake and transport efficiency, yield and its components, and quality and its components under different nitrogen application treatments, and fitted a function based on the effect of total nitrogen fertilizer on quality. Taking into account four quality indicators and ensuring yield reduction is less than 30%, replacing 100% chemical fertilizer with compound fertilizer in Nanjing 9108 was the optimal strategy for significantly improving quality. Reducing panicle fertilizer by 50% or omitting it also significantly improved quality. Replacing chemical fertilizers with 50% compound fertilizer also maintained nutritional quality. Reducing total nitrogen fertilizer by 25% in Ming 1 Youzhenzhan was the optimal strategy for significantly enhancing quality. Replacing chemical fertilizer with 100% compound fertilizer significantly improved quality. Reducing panicle fertilizer by 50% and substituting 50% of chemical fertilizer with compound fertilizer also significantly improved quality. Taking into account the synergistic effects of nitrogen application measures on rice yield and quality, the performance of the two rice varieties is not identical. The results showed that nitrogen fertilizer management significantly affected both yield and quality, with responses varying between the two varieties. But the two varieties can ensure optimal quality under yield conditions by reducing panicle fertilizer application by 50% and replacing chemical fertilizers with compound fertilizers.

Leaf inclination angle (LIA) is a key trait affecting crop canopy structure and photosynthetic efficiency, but its accurate measurement is challenging due

Multi-view 3D reconstruction has been widely applied in plant phenotyping, but the complex canopy structure of rice plants poses significant challenges for reconstruction accuracy, completene7ss, and efficiency. In this study, we developed an optimized workflow for 3D reconstruction of rice using the self-developed Metatlas V1 multi-view imaging platform combined with the COLMAP + OpenMVS pipeline. A CBAM-UNet-based image segmentation model was used to extract plant regions from complex backgrounds, outperforming thresholding, U-Net, and U-Net++, and increasing the number of reconstructed points. Camera configuration optimization was performed by systematically combining equidistant and greedy strategies, resulting in an optimal six-camera setup (#2, #3, #4, #6, #7, and #8, corresponding to −30°, −15°, 0°, +30°, +45°, and +60° relative to the horizontal viewpoint), which provided complementary views of the canopy inner structure and stem base. This configuration reduced the average nearest-neighbor distance to 0.037–0.066 cm across different varieties and growth stages compared with the full 11-camera setup, retained 73–76% of the points, and decreased reconstruction duration by approximately 70–80%. The strong agreement between point-cloud-derived and manually measured plant height and canopy width ( R ² = 0.989 and 0.946, respectively) supported the accuracy of the point-cloud-derived phenotypic measurements. Overall, integrating image segmentation with camera-configuration optimization offers an accurate and efficient solution for high-throughput 3D phenotyping of rice using Metatlas V1, balancing reconstruction accuracy, point-cloud completeness, and computational efficiency, and may provide a methodological reference for camera-configuration design in other rotational multi-view phenotyping platforms.