Shixin Li

Shixin Li


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

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

Representative Publications

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13 January 2023 in Journal of Electronic Materials
Verified
Journal Article
Closed access
PDF file
HZHengchao Zhang
Hengchao Zhang
YLYarou Li
Yarou Li
YZYupan Zhang
Yupan Zhang
JWJunfeng Wu
Junfeng Wu
SLShixin Li
Shixin Li
LLLanlan Li
Lanlan Li

14 February 2019 in Applied Sciences
Verified
Journal Article
Open access
PDF file
QGQingqian Guo
Qingqian Guo
RCRuipeng Chen
Ruipeng Chen
LMLiuzheng Ma
Liuzheng Ma
HSHaifeng Sun
Haifeng Sun
MWMengmeng Weng
Mengmeng Weng
Jiandong HuJiandong Hu
Jiandong Hu
Corn stalk lodging, which involves the breakage of the stalk below the ear following either bad weather, insect infestation or stormy rain, usually leads to harvest loss, increased harvesting time and higher drying costs. The objective of this study was to develop a method that can classify corn stalk lodging resistance. This method, which employed the maximum equivalent force exerted on a corn stalk, corresponding stalk agronomic traits, and the singular value decomposition (SVD) algorithm, showed that the five corn varieties with different stalk lodging resistance from two planting densities of 60,000 plants/ha and 75,000 plants/ha can be effectively classified. A customized device was designed to measure the equivalent forces. Three factors, including the planting density, the stalk diameter, and the maximum equivalent force with comprehensive contributions of −0.4603, 0.4196 and 0.4068, which are related to principal components, play an important role in the classification of corn stalk lodging resistance. The results showed that the corn stalk lodging resistance decreased with increase in planting density; however, with the increase in stalk diameter and maximum equivalent force, the lodging resistance significantly increased. Corn breeders can develop higher lodging resistance-based corn varieties by using this approach.

10 April 2023 in Journal of Materials Science
Verified
Journal Article
Closed access
PDF file
HZHengchao Zhang
Hengchao Zhang
YLYarou Li
Yarou Li
YZYupan Zhang
Yupan Zhang
JWJunfeng Wu
Junfeng Wu
JHJiandong Hu
Jiandong Hu
LLLanlan Li
Lanlan Li

Verified
Conference Paper
Open access
PDF file
Syed Muhammad Zaigham Abbas NaqviSyed Muhammad Zaigham Abbas Naqvi
Syed Muhammad Zaigham Abbas Naqvi
Shoaib Rashid SaleemShoaib Rashid Saleem
Shoaib Rashid Saleem
MTMuhammad Naveed Tahir
Muhammad Naveed Tahir
SLShixin Li
Shixin Li
Saddam HussainSaddam Hussain
Saddam Hussain
MAMuhammad Awais
Muhammad Awais
Smart farming and precision agriculture rely on the different components of IoT, such as sensors, drones, and robotic devices. IoT in agriculture is the network of interconnected devices that corresponds in real time, simultaneously, to gather, analyze, and transfer the data, which, ultimately, generate a decision to be taken by the farmer. The availability of the 4G/3G does not support the precision practices in real time due to the bandwidth, connectivity, and the speed of data-transfer issues. Further, 5G technology in the agricultural sector has put its greater influence in real-time monitoring, unmanned aerial vehicles, virtual consultation and predictive maintenance, artificially intelligent robotics, and data analytics and cloud repositories. Conclusively, the speed, connectivity, scalability and processing power, and limitations can be overcome with the availability of 5G structures.

25 November 2023 in Journal of Materials Science
Verified
Journal Article
Closed access
PDF file
YLYarou Li
Yarou Li
JWJunfeng Wu
Junfeng Wu
HZHengchao Zhang
Hengchao Zhang
JHJiandong Hu
Jiandong Hu
SLShixin Li
Shixin Li
LLLanlan Li
Lanlan Li