“Smart Agriculture” Information Technology and Agriculture Cross-Discipline Research and Development

Dear Colleagues,

Our goal is to explore and support the evolution of emerging digital technology applications in agriculture and biology, including but not limited to agriculture, data collection, data mining, bioinformatics, genomics and phenomics, as well as applications of machine learning and artificial intelligence.

The development of a community to support this goal requires the cross linking and integration of multiple sources of agricultural research across 3S technologies (remote sensing—RS, geographic information systems—GIS, global positioning systems—GPS). This provides a basis for the detection of crop pathogens, weeds and pests (insects) using multi-spectrum techniques and the exploitation of remote sensing technology to create and analyze multiple heterogeneous-structured data sets, which enables effective cross-linking and phenomic classification. It is essential to study growth models of plants/crops and utilize expert support to develop production and smart management decision systems to achieve real-time, quantified, and precise decisions.

Topics of high interest include the capture and curation of biological “big data,”  research on multi-spectrum analysis, the assembly of complex genetic sequencing fragments, and structural gene predictions coupled with intermediate structures to predict phenotypes. In this context, novel data structures are required to capture predictive structures in the path from genome type to phenotype, together with new techniques to capture identify the regularity of biological data.

Finally, multiple-sources-based monitoring and decision making for plants, water, and nutrients are required, with a research focus on the utilization of remote sensing and drone sensing to compute and predict plant water usage. This will lead to the development of precision models of crop water/nutrient management systems and form the foundation for the digitalization of agricultural water/nutrient applications.

Prof. Dr. Jian Zhang
Prof. Dr. Randy G. Goebel
Prof. Dr. Zhihai Wu
Guest Editors

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