Ying Zhang

National Engineering Research Center for Information Technology in Agriculture

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Shenghao Gu

Beijing Academy of Agricultural and Forestry Sciences

Yuke Lin

Chongqing University

Xinyu Guo

China Agricultural University

Weiliang Wen

National Engineering Research Center for Information Technology in Agriculture

Yingpu Li

First Affiliated Hospital of Harbin Medical University

Jinglu Wang

Microsoft Research Asia (China)

Jianjun Du

National Engineering Research Center for Information Technology in Agriculture

Yunan Zhu

Harbin Medical University

Zehao Li

Henan University of Technology

Jin Xu

Chongqing Academy of Chinese Materia Medica

Cooperative Institutions

Harbin Medical University

Third Affiliated Hospital of Harbin Medical University

National Engineering Research Center for Information Technology in Agriculture

Beijing Academy of Agricultural and Forestry Sciences

China Agricultural University

First Affiliated Hospital of Zhengzhou University

Huazhong Agricultural University

Northwest A&F University

Digital Science (United States)

Center for Information Technology

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Research on Precision Cultivation of Digital Multimedia Crop Based on Predictive Computational Intelligence Technology

Advances in Multimedia (2021)

Yuke Lin Ying Zhang

With the intersection and integration of modern crop cultivation and emerging disciplines, crop cultivation management is moving from traditional modeling and standardization to quantitative and intelligent direction. Crop precision cultivation technology is to apply system science and information technology to crop cultivation and digitally design information perception of the objects and processes involved in crop cultivation, dynamic simulation, so as to realize the quantification and accuracy of crop cultivation management. With the integration and intersection of modern digital multimedia crop cultivation and emerging disciplines, digital multimedia crop cultivation tends to gradually implement the quantitative and intelligent development, replacing the traditional scale and standardization. The technology of digital multimedia crop cultivation is to use science and information technology in digital multimedia crops to achieve the quantitative and precise characteristics of digital multimedia crop cultivation. The advancement of digital multimedia crop cultivation technology has greatly improved the management and benefits of the entire agricultural industry and has played a positive role in the development of agricultural information and modernity.

10.1155/2021/2864009

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Citations (1)

Standard Framework Construction of Technology and Equipment for Big Data in Crop Phenomics

Engineering (2024)

Weiliang Wen Shenghao Gu Ying Zhang Wanneng Yang Xinyu Guo

Crop phenomics has rapidly progressed in recent years due to the growing need for crop functional genomics, digital breeding, and smart cultivation. Despite this advancement, the lack of standards for the creation and usage of crop phenomics technology and equipment has become a bottleneck, limiting the industry's high-quality development. This paper begins with an overview of the crop phenotyping industry and presents an industrial mapping of technology and equipment for big data in crop phenomics. It analyzes the necessity and current state of constructing a standard framework for crop phenotyping. Furthermore, this paper proposes the intended organizational structure and goals of the standard framework. It details the essentials of the standard framework in the research and development of hardware and equipment, data acquisition, and the storage and management of crop phenotyping data. Finally, it discusses promoting the construction and evaluation of the standard framework, aiming to provide ideas for developing a high-quality standard framework for crop phenotyping.

Phenomics

10.1016/j.eng.2024.06.001

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Citations (2)

Breeding Experience and Enlightenment on Lowline Breed

Journal of Yellow Cattle Science (2003)

Ying Zhang

Lowline is a specialized beef breed bred in Australian, which is a small and early-mature type beef breed. Lowline origined from Angus, with a commonly used technical method for nearly 30 years, main body sizes of Lowline are just 60%～70% of those in Angus. Breeding process and breed characteristics of Lowline are introduced in this article , and experience we can get from Lowline breeding are that special breeding aims, sustainable breeding measures, combined with beef production, and so on, all of these will be valuable for beef breeding in China.

Beef Cattle

Selective breeding

Animal Breeding

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A bibliometric study of the intellectual base and global research hotspots for single-cell sequencing [2009–2022] in breast cancer

Heliyon (2024)

Shan Liu Xudong Li Ying Zhang Yuhan Deng Zehao Li

BackgroundBreast cancer is the most widespread malignant tumor worldwide. Single-cell sequencing technology offers novel insights and methods to understand the onset, progression, and treatment of tumors. Nevertheless, there is currently an absence of a thorough and unbiased report on the comprehensive research status of single-cell sequencing in breast cancer. This study seeks to summarize and quantify the dynamics and trends of research on breast cancer single-cell sequencing by bibliometric analysis.MethodsResearch articles and reviews related to breast cancer single-cell sequencing were selected from the WoSCC database. Visualization of data regarding countries, institutions, authors, references, and keywords was performed by CiteSpace and VOSviewer software.Results583 articles and reviews were analyzed in this study. The quantity of publications related to breast cancer single-cell sequencing has been increasing annually. These studies originate from 302 institutions in 46 countries, with YMAX S WICHA producing the most publications and WANG Y being the most cited author. Nature Communications is the most researched journal, while Nature holds the highest number of citations. These journals predominantly cover topics in the molecular/biological/immunological fields. Moreover, an analysis of reference and keyword bursts revealed that current research trends in this area are primarily centered on "clonal evolution," "tumor microenvironment," and "immunotherapy."ConclusionBreast cancer single-cell sequencing is a rapidly growing area of scientific interest. Future research requires more frequent and in-depth collaborations among countries, institutions, and authors. Furthermore, "clonal evolution," "tumor microenvironment," and "immunotherapy" are likely to become major focal points in upcoming research on breast cancer single-cell sequencing.

10.1016/j.heliyon.2024.e33219

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Citations (1)

Identification Method of Citrus Aurantium Diseases and Pests Based on Deep Convolutional Neural Network

Computational Intelligence and Neuroscience (2022)

Yuke Lin Jin Xu Ying Zhang

The traditional identification methods of Citrus aurantium diseases and pests are prone to convergence during the running process, resulting in low accuracy of identification. To this end, this study reviews the newest methods for the identification of Citrus aurantium diseases and pests based on a deep convolutional neural network (DCNN). The initial images of Citrus aurantium leaves are collected by hardware equipment and then preprocessed using the techniques of cropping, enhancement, and morphological transformation. By using the neural network to divide the disease spots of Citrus aurantium images, accurate recognition results are obtained through feature matching. The comparative experimental results show that, compared with the traditional recognition method, the recognition rate of the proposed method has increased by about 11.9%, indicating its better performance. The proposed method can overcome the interference of the external environment to a certain extent and can provide reference data for the prevention and control of Citrus aurantium diseases and pests.

Identification

Feature (linguistics)

10.1155/2022/7012399

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Citations (11)

Crop Phenomics: Current Status and Perspectives

Frontiers in Plant Science (2019)

Chunjiang Zhao Ying Zhang Jianjun Du Xinyu Guo Weiliang Wen

Reliable, automatic, multifunctional, and high-throughput phenotypic technologies are increasingly considered important tools for rapid advancement of genetic gain in breeding programs. With the rapid development in high-throughput phenotyping technologies, research in this area is entering a new era called 'phenomics.' The crop phenotyping community not only needs to build a multi-domain, multi-level, and multi-scale crop phenotyping big database, but also to research technical systems for phenotypic traits identification and develop bioinformatics technologies for information extraction from the overwhelming amounts of omics data. Here, we provide an overview of crop phenomics research, focusing on two parts, from phenotypic data collection through various sensors to phenomics analysis. Finally, we discussed the challenges and prospective of crop phenomics in order to provide suggestions to develop new methods of mining genes associated with important agronomic traits, and propose new intelligent solutions for precision breeding.

Phenomics

10.3389/fpls.2019.00714

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Citations (316)