Several examples in the history of biology show how technological advances facilitated fundamental discoveries in biology. The development and application of imaging techniques in plant sciences represent such an example that is currently unfolding. By using image analysis, spatially resolved information can be obtained that allows for the exploration of new questions in the fields. Also, when applied in for example crop surveillance, quality control, or management, these techniques make real-time decisions possible, often based on non-destructive measurements. In some cases, a reduction in time and labor could also arise and translate into cost savings.
The research topic seeks to highlight innovative ways imaging techniques are being explored within plant science as well as ways these techniques are being developed and utilized to solve problems in agriculture and beyond. Submissions that reflect the application within plant science of approaches involving any type of imaging data are welcome. This could for example be field data captured by use of unmanned aerial vehicle (UAV)-based imaging technologies or laboratory data from any type of microscopy, such as for example light microscopy, fluorescence microscopy, or microspectroscopy involving infrared or Raman spectroscopy. Furthermore, the application of existing data analysis methods as well as the development of new ones to address specific questions or problems within the field are also welcome, for example the use of methods based on artificial intelligence and machine learning solutions to maximize the information obtained by multispectral imaging.
Several examples in the history of biology show how technological advances facilitated fundamental discoveries in biology. The development and application of imaging techniques in plant sciences represent such an example that is currently unfolding. By using image analysis, spatially resolved information can be obtained that allows for the exploration of new questions in the fields. Also, when applied in for example crop surveillance, quality control, or management, these techniques make real-time decisions possible, often based on non-destructive measurements. In some cases, a reduction in time and labor could also arise and translate into cost savings.
The research topic seeks to highlight innovative ways imaging techniques are being explored within plant science as well as ways these techniques are being developed and utilized to solve problems in agriculture and beyond. Submissions that reflect the application within plant science of approaches involving any type of imaging data are welcome. This could for example be field data captured by use of unmanned aerial vehicle (UAV)-based imaging technologies or laboratory data from any type of microscopy, such as for example light microscopy, fluorescence microscopy, or microspectroscopy involving infrared or Raman spectroscopy. Furthermore, the application of existing data analysis methods as well as the development of new ones to address specific questions or problems within the field are also welcome, for example the use of methods based on artificial intelligence and machine learning solutions to maximize the information obtained by multispectral imaging.
