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Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) more...

Refrigerated transport equipment is increasing rapidly with the development of the cold chain in China. High energy consumption of refrigerated trucks can often occur correspondingly in recent years. In most cases, the envelope material of the transport equipment can be improved to reduce energy consumption. Alternatively, the heat transfer mechanism can be widely expected to significantly promote the energy efficiency of refrigerated equipment in a short term. Particularly, the heat load of cold chain transportation can originate mainly from the air-convection heat exchange and the solar radiation heat. In this study, the radiative cooling coating was developed and applied to the external surface of the cold chain incubator. The paint material was also characterized by the white homogeneous liquid with a relatively high resistance to impact, adhesion, acid, alkali, and artificial aging. A series of tests were then carried out to evaluate the performance of radiative cooling coatings on the thermal insulation of the cold chain incubator. The test results show that the solar radiation heat gain of the incubator decreased significantly using radiation cooling coating. Specifically, the average temperature of the outside surface of the insulation box decreased by 0.7-6.9 ℃ with an average decrease rate of 10.0% than before. The maximum decrease rate of the peak temperature was 17.3 ℃, decreasing over 28.5%. The average temperature of the inner surface also decreased by 3.6-5.5 ℃. The peak temperature of the inside surface decreased by 15.0% and the average temperature of the inside surface decreased by 11.2%. The average temperature of the central air inside the box decreased by 10.0%. At the same time, the uniform distribution of the temperature field inside the insulated box greatly contributed to the cooling performance of the final quality of the food. The temperature range decreased by 30.2%-30.7% using the radiative cooling coating, where the variance of the temperature field decreased by 26.3%-29.9%, indicating the uniform temperature field of the internal box. Energy consumption analysis showed that the cold chain incubator with the radiation cooling coatings was reduced the annual heat leakage by 44.3 kW·h, and the carbon emissions by 17.3-51.8 kg., compared with the original. Specifically, there was a total reduced heat leakage of 212.3 kW·h from the incubator coated with the radiation cooling paint, when the thickness of the box envelope increased from 40 to 100 mm. The total heat leakage rate decreased gradually with the increase of coating thickness. Additionally, the color of the coating was an important indicator of the optical properties of the paint. An excellent insulation property was achieved in the insulated boxes with the white radiant cooling paint, where the total annual heat leakage decreased by 22.4%, compared with the dark coffee colored paints with high solar absorption ratios. The finding can provide new ideas for the energy-saving application of cold chain transportation equipment, particularly for agricultural facilities with the heat insulation requirements, such as grain, cold storage, and oil tanks. [ABSTRACT FROM AUTHOR] more...

The number of spikes per unit area is a key yield component for cereal crops such as wheat, which is popularly used in wheat research for crop improvement. With the fast maturity of smartphone imaging hardware and recent advances in image processing and lightweight deep learning techniques, it is possible to acquire high-resolution images using a smartphone camera, followed by the analysis of wheat spikes per unit area through pre-trained artificial intelligence algorithms. Then, by combining detected spike number with variety-based spikelet number and grain weight, it is feasible to carry out a near real-time estimation of yield potential for a given wheat variety in the field. This AI-driven approach becomes more powerful when a range of varieties are included in the training datasets, enabling an effective and valuable approach for yield-related studies in breeding, cultivation, and agricultural production. In this study, we present a novel smartphone-based software application that combines smartphone imaging, lightweight and embedded deep learning, with yield prediction algorithms and applied the software to wheat cultivation experiments. This open-source Android application is called YieldQuant-Mobile (YQ-M), which was developed to measure a key yield trait (i.e. spikes per unit area) and then estimate yield based on the trait. Through YQ-M and smartphones, we standardized the in-field imaging of wheat plots, streamlined the detection of spikes per unit area and the prediction of yield, without a prerequisite of in-field WiFi or mobile network. In this article, we introduce the YQ-M in detail, including: 1) the data acquisition designed to standardize the collection of wheat images from an overhead perspective using Android smartphones; 2) the data pre-processing of the acquired image to reduce the computational time for image analysis; 3) the extraction of wheat spike features through deep learning (i.e. YOLOV4) and transfer learning; 4) the application of TensorFlow.lite to transform the trained model into a lightweight MobileNetV2-YOLOV4 model, so that wheat spike detection can be operated on an Android smartphone; 5) finally, the establishment of a mobile phone database to incorporate historic datasets of key yield components collected from different wheat varieties into YQ-M using Android SDK and SQLite. Additionally, to ensure that our work could reach the broader research community, we developed a Graphical User Interface (GUI) for YQ-M, which contains: 1) the spike detection module that identifies the number of wheat spikes from a smartphone image; 2) the yield prediction module that invokes near real-time yield prediction using detected spike numbers and related parameters such as wheat varieties, place of production, accumulated temperature, and unit area. During our research, we have tested YQ-M with 80 representative varieties (240 1 m² plots, three replicates) selected from the main wheat producing areas in China. The computed accuracy, recall, average accuracy, and F1-score for the learning model are 84.43%, 91.05%, 91.96%, and 0.88, respectively. The coefficient of determination between YQ-M predicted yield values and post-harvest manual yield measurement is 0.839 (n=80 varieties, P<0.05; Root Mean Square Error=17.641 g/m²). The results suggest that YQ-M presented here has a high accuracy in the detection of wheat spikes per unit area and can produce a consistent yield prediction for the selected wheat varieties under complex field conditions. Furthermore, YQ-M can be easily accessed and expanded to incorporate new varieties and crop species, indicating the usability and extendibility of the software application. Hence, we believe that YQ-M is likely to provide a step change in our abilities to analyze yield-related components for different wheat varieties, a low-cost, accessible, and reliable approach that can contribute to smart breeding, cultivation and, potentially, agricultural production. [ABSTRACT FROM AUTHOR] more...

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) more...

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) more...

Copyright of Southwest China Journal of Agricultural Sciences is the property of Editorial Department of Southwest China Journal of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) more...

Copyright of Tourism Tribune / Lvyou Xuekan is the property of Tourism Institute of Beijing Union University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) more...