Research Program 4

Project 4 Smart Decision Support and Tracking Systems for Sustainable Agriculture

Institution: SUNUM Sabancı University Nanotechnology Research and Application Center

Project 4.1  Development of Hyperspectral Monitoring and Decision Support Systems for Sustainable Agriculture

Project 4.1 Summary:

Spectral detection techniques can be used to ascertain an agricultural product's water requirements, stress levels, and fertilizer needs. These diagnostic techniques could be applied more quickly and widely using hyperspectral cameras. Hyperspectral imaging makes it possible to map and continuously monitor the presence or absence of demands in various fields, including those for water, pesticides, herbicides, and fertilizer. By employing such techniques, intelligent farming applications significantly improve the amount and quality of produce and the effective use of water and energy resources. Furthermore, plant breeding and agricultural development studies increasingly rely on high-throughput plant phenotyping. The technique of image-based phenotyping is notable for its ability to drastically cut down on the expenses, duration, and labour of extensive screening trials while still permitting non-destructive analytical examinations.

The proposed research aims to create portable hyperspectral camera systems that can cover the spectral ranges needed for agricultural applications and have high spectral resolution (350–1050 and 400–1700 nm), making them appropriate for automation systems and drones. A hyperspectral optical system that has been created may be used to monitor greenhouses, specific agricultural products, and agricultural land. The project aims to provide artificial intelligence that can enhance decision-making regarding plant stress and nutritional requirements in agricultural production in addition to hyperspectral imaging technology.

Project 4.2  Development of a Portable Raman Spectroscopy Prototype for Pesticide Monitoring

Project 4.2 Summary:

Pesticides are chemicals commonly used in agriculture to prevent the formation of harmful organisms such as insects, pests, viruses, and fungi, thereby increasing agricultural productivity. With the increasing world population and changing climate conditions, the use of pesticides has become widespread. Improper pesticide use can lead to residues, posing a threat to human health and environmental safety. Therefore, food authorities expect pesticide residues in agricultural products to be within specified maximum values. Indiscriminate use of banned chemicals can negatively affect the export potential of countries with significant markets in exporting fresh vegetables and fruits. Hence, it is crucial to regularly and accurately monitor pesticides to raise awareness among producers and prevent unnecessary pesticide use.

In this context, the project aims to develop a prototype of a Raman spectroscopy (RS) system enhanced with plasmonic nanostructures capable of generating signals with high sensitivity suitable for field use in pesticide monitoring. High-efficiency diffraction gratings will be produced for use in the Raman spectroscopy prototype using nano-fabrication methods, and unique plasmonic nano surfaces that enhance signals (Surface-Enhanced Raman Spectroscopy, SERS) will be developed to increase signal intensity. The Raman molecular fingerprints of identified pesticide groups will be compiled into a database using the developed plasmonic nano surfaces. Spectrum information obtained under different conditions from each reference pesticide or pesticide-containing sample will be processed using artificial intelligence and deep learning techniques to create an algorithm that distinguishes different pesticides based on spectral peaks. The goal is to spectrally separate and quantitatively analyze at least 10 different pesticides using the proposed prototype, with an expected overlap of at least 85% between RS prototype performance data and standard method data. Furthermore, the project is aligned with the "From Farm to Table: Sustainable Food Systems" theme and in harmony with the "Green Deal" protocol. It is expected to accelerate the transfer of interim and final outputs to other environmental, food, pharmaceutical, and agricultural applications.