Accurate litchi identification is of great significance for orchard yield estimations. Litchi in natural scenes have large differences in scale and are occluded by leaves, reducing the accuracy of litchi detection models. Adopting traditional horizontal bounding boxes will introduce a large amount of background and overlap with adjacent frames, resulting in a reduced litchi detection accuracy. Therefore, this study innovatively introduces the use of the rotation detection box model to explore its capabilities in scenarios with occlusion and small targets. First, a dataset on litchi rotation detection in natural scenes is constructed. Secondly, three improvement modules based on YOLOv8n are proposed: a transformer module is introduced after the C2f module of the eighth layer of the backbone network, an ECA attention module is added to the neck network to improve the feature extraction of the backbone network, and a 160 × 160 scale detection head is introduced to enhance small target detection. The test results show that, compared to the traditional YOLOv8n model, the proposed model improves the precision rate, the recall rate, and the mAP by 11.7%, 5.4%, and 7.3%, respectively. In addition, four state-of-the-art mainstream detection backbone networks, namely, MobileNetv3-small, MobileNetv3-large, ShuffleNetv2, and GhostNet, are studied for comparison with the performance of the proposed model. The model proposed in this article exhibits a better performance on the litchi dataset, with the precision, recall, and mAP reaching 84.6%, 68.6%, and 79.4%, respectively. This research can provide a reference for litchi yield estimations in complex orchard environments.

(1) Background: The thermal environment in a pregnant sow piggery is affected by physical parameters such as air temperature, relative humidity, and airflow velocity. However, it is challenging to conduct experimental studies due to the high cost. (2) Methods: Computational fluid dynamics (CFD) was used to study the distribution characteristics of airflow in a pregnant sow piggery with centralized ventilation. (3) Results: The results show that the maximum difference between the simulated and experimental temperature was less than 1.54 °C, and the simulated and tested relative humidity difference was less than 10% RH. Incorporation of a middle air outlet is beneficial for increasing the uniformity of temperature distribution, as studied by comparing the temperature and humidity uniformity coefficient of the two air outlet locations, but the uniformity of humidity distribution will be reduced. With an increase in velocity, the temperature shows a downward trend and the relative humidity shows an upward trend. (4) Conclusions: The most suitable position for the outlet is the middle, with an associated airflow velocity of 0.5 m/s. This study revealed the variation in flow field distribution and air distribution in the pregnant sow piggery as a consequence of changes in ventilation structure, which has certain significance as a reference for the optimization of airflow in intensive pregnant sow piggeries.