Jiayuan Shao

Mr. Jiayuan Shao

College of Agricultural Engineering, Shanxi Agricultural University, Shanxi, China
orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 October 2023 in Agriculture
Verified
Journal Article
Open access
PDF file
HLHaopu Li
Haopu Li
HLHaoming Li
Haoming Li
BLBugao Li
Bugao Li
JSJiayuan Shao
Jiayuan Shao
YSYanBo Song
YanBo Song
ZLZhenyu Liu
Zhenyu Liu
Efficiently managing temperature and humidity in a pig house is crucial for enhancing animal welfare. This research endeavors to develop an intelligent temperature and humidity control system grounded in a three-way decision and clustering algorithm. To establish and validate the effectiveness of this intelligent system, experiments were conducted to compare its performance against a naturally ventilated pig house without any control system. Additionally, comparisons were made with a threshold-based control system to evaluate the duration of temperature anomalies. The experimental findings demonstrate a substantial improvement in temperature regulation within the experimental pig house. Over a 24 h period, the minimum temperature increased by 4 °C, while the maximum temperature decreased by 8 °C, approaching the desired range. Moreover, the average air humidity decreased from 73.4% to 68.2%. In summary, this study presents a precision-driven intelligent control strategy for optimizing temperature and humidity management in pig housing facilities.

4 July 2023 in Sustainability
Verified
Journal Article
Open access
PDF file
FJFan Jiao
Fan Jiao
LNLili Nie
Lili Nie
JSJiayuan Shao
Jiayuan Shao
瑛王瑛 王
瑛 王
YDYihan Du
Yihan Du
ZLZhenyu Liu
Zhenyu Liu
Water scarcity is a significant global problem. Considerable water resources are consumed in the production of livestock and poultry products, thus posing a huge challenge to global freshwater resources. Sheep meat has the second highest water footprint among livestock meat products. Furthermore, as the demand for sheep meat increases on a year by year basis, water consumption continues to rise as a result. In order to make better informed decisions around water management, it is necessary to estimate the water footprint of animal husbandry. This study offers a comprehensive overview of the water footprint of sheep in Northern China. It analyzes the water footprint of feed production and virtual water using CROPWAT, based on the water footprint of sheep and goats in Shanxi under different production systems and feed components. The water footprint was calculated to be 6.03 m3/kg for sheep and 5.05 m3/kg for goats, respectively. Therefore, the water footprint of three farming modes, including grazing mixed and industrial in the Shanxi region was slightly higher than what other experts have evaluated for China. These data provide crucial information that can help reduce water resource consumption in animal husbandry and contribute to the development of sustainable strategies.

20 August 2023 in Processes
Verified
Journal Article
Open access
PDF file
JSJiayuan Shao
Jiayuan Shao
FJFan Jiao
Fan Jiao
LNLili Nie
Lili Nie
瑛王瑛 王
瑛 王
YDYihan Du
Yihan Du
ZLZhenyu Liu
Zhenyu Liu
Vacuum freeze-dried products exhibit properties characteristic of porous media, rendering them superior in both drying and rehydration capabilities. However, the process of sublimation drying is constrained by its substantial time and energy costs. To comprehensively grasp its technological process and identify the optimal process parameters, the cellular automata method was employed for sublimation process simulation. Carrot slices, measuring 10 mm in thickness and 40 mm in radius, were selected for both simulation and experimentation. The sublimation process was characterized using a two-dimensional heat and mass transfer equation, inclusive of a dusty gas model. Additionally, a cellular automaton model was applied to simulate the mass transfer process, temperature, and moisture content changes in the sublimation drying stage. Then, the accuracy of the model was verified through experimentation. There was a remarkable alignment between simulation and experimental outcomes, with determination coefficients R2 of 99.4% for moisture content and 97.6% for temperature variations.