Cold-storage containers are widely used in cold-chain logistics transportation due to their energy saving, environmental protection, and low operating cost. The uniformity of temperature distribution is significant in agricultural-product storage and transportation. This paper explored temperature distribution in the container by numerical simulation, which included ventilation velocity and the fan location. Numerical model/numerical simulation showed good agreement with experimental data in terms of temporal and spatial air temperature distribution. Results showed that the cooling rate improved as velocity increased, and temperature at 45 min was the lowest, when velocity was 16 m/s. Temperature-distribution uniformity in the compartment became worse with the increase in ventilation velocity, but its lowest temperature decreased with a velocity increase. With regard to fan energy consumption, the cooling rate of the cooling module, and temperature-field distribution in the product area, velocity of 12 m/s was best. Temperature standard deviation and nonuniformity coefficient in the container were 0.87 and 2.1, respectively, when fans were located in the top four corners of the container. Compared with before, the average temperature in the box was decreased by 0.12 °C, and the inhomogeneity coefficient decreased by more than twofold. The results of this paper provide a better understanding of temperature distribution in cold-storage containers, which helps to optimize their structure and parameters.

(1) Background: Forklifts are used widely in factories, but it shows the problem of large uncertainties when using an RGB-D sensor to recognize and locate pallets in warehouse environments. To enhance the flexibility of current autonomous forklifts in unstructured environments, the improved labeled template matching algorithm was proposed to recognize pallets. (2) Methods: The algorithm comprises four steps: (i) classifying each pixel of a color image with the color feature and obtaining the category matrix; (ii) building a labeled template containing the goods, pallet, and ground category information; (iii) compressing and matching the category matrix and template to determine the region of the pallet; and (iv) extracting the pallet pose from information in respect of the pallet feet. (3) Results: The results show that the proposed algorithm is robust against environmental influences and obstacles and that it can precisely recognize and segment multiple pallets in a warehouse with a 92.6% detection rate. The time consumptions were 72.44, 85.45, 117.63, and 182.84 ms for detection distances of 1000, 2000, 3000, and 4000 mm, respectively. (4) Conclusions: Both static and dynamic experiments were conducted, and the results demonstrate that the detection accuracy is directly related to the detection angle and distance.

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.

(1) Background: With the development of cold chain logistics in recent years, the demand for refrigerated display cases has greatly increased in the home and commercial markets. However, the difference of temperature and humidity between each layer of refrigerated display cabinet is great, which affects the health of consumers. In order to reduce the temperature difference for each layer in a cabinet and to improve the temperature uniformity inside the cabinet, an open-hole shelf is designed according to the principle of aerodynamics. (2) Methods: The influence of different shelf aperture ratios on the periodic temperature fluctuation, average temperature, temperature non-uniformity coefficient, and temperature maintenance coefficient inside the cabinet is studied by means of experiments with pork. (3) Results: The results show that when the aperture ratio increases from 0% to 90%, the average maximum temperature in a single cycle in the cabinet shows a trend of first decreasing and then increasing. The minimum temperature difference in the cabinet is 4.3 °C, and the corresponding aperture ratio is 25%. (4) Conclusions: The results show that 25% is the optimal aperture ratio for a shelf in the refrigerated display cabinet. The results provide a better reference for optimization of the structure and temperature in an open refrigerated display cabinet.