Magnetic Resonance Imaging for short relaxation times applied to seed evaluation

Magnetic Resonance Imaging for short relaxation times applied to seed evaluation

 

*Julia Marcolan1, Agide Gimenez Marassi1, Rafael Mateus Alves2, Francisco Guilhien Gomes-Junior2, Alberto Tannús1

1 Universidade de São Paulo, Instituto de Física de São Carlos, Centro de Imagens e Espectroscopia por Ressonância Magnética São, Carlos, SP, Brazil
2 Universidade de São Paulo, Escola Superior de Agricultura “Luiz de Queiroz, Piracicaba, SP, Brazil

*juliamarcolan@usp.br

 

In 2021, the Global Domestic Product (GDP) share attributed to the agricultural sector increased by 8.36%, comprising 27.4% of the total Brazilian GDP. Moreover, Brazil ranks first globally in soybean seed production1. Seed quality is crucial for crop development, directly affecting productivity. However, current seed evaluation methods lack accurate and non-destructive identification of early-stage lesions. Magnetic Resonance Imaging (MRI) has been proposed to address this issue by enabling the observation of internal structures on a 3D scale. However, applying MRI to hard tissues such as seeds remains challenging due to water being confined to a bound phase, reducing water mobility and resulting in ultra-short relaxation times (T2 ~ 0.1 - 10 ms). Rapid signal encoding and acquisition are needed to produce images with short relaxation times, before signal decay2. Different techniques have been developed, including Fast Low Angle Shot (FLASH), Zero Echo Time (ZTE), and Sweep Imaging with Fourier Transformation (SWIFT), to produce high-resolution images for samples with short relaxation times.

Commercial equipment limits user autonomy in MRI Method implementation and adaptability, with manufacturer updates and maintenance posing issues over time. For instance, older equipment may not easily support the implementation of newer fast imaging techniques. To overcome it, the CIERMag Digital Magnetic Resonance Spectrometer (DMRS) addresses limitations in existing equipment, offering freedom in Method development. It uses Field-Programmable Gate Array (FPGA) technology with proprietary synthesized digital hardware subsystems. CIERMag also developed user control software using the Python Magnetic Resonance Framework (PyMR), and a proprietary programming language, the F Language3.

This research project aims to investigate the application of MRI and image segmentation techniques for evaluating mechanical injuries and damage inflicted on seeds by insects during field or storage conditions. To achieve this goal, ultra-short relaxation time image sequences are being implemented on the DMRS. Already implemented and in use in the DMRS using F language, the FLASH sequence along with a protocol for acquiring locator images across three orthogonal planes show preliminary results. Processing files were also developed for image reconstruction from sequence-obtained data. Images of soybean seeds with various damages were acquired using a commercial Bruker spectrometer and the FLASH sequence for comparison.

Acknowledgments: CAPES (88887.803866/2023-00) and NIH (sub-award IN006264802 1) for financial support.

References
1. Center for Advanced Studies in Applied Economics (Cepea). (n.d.). Agro GDP grows 8.36% in 2021; share in Brazilian GDP reaches 27.4%. Retrieved from https://www.cepea.esalq.usp.br/br/releases/pib-agro-cepea-pib-do-agro-cresce-8-36-em-2021-partici pacao-no-pib-brasileiro-chega-a-27-4.aspxh
2. Mastrogiacomo, S., et al. (2019). Magnetic resonance imaging of hard tissues and hard tissue engineered bio-substitutes. Molecular Imaging and Biology, 21, 1003-1019.
3. Pizetta, D. C. (2019). PyMR: A framework for programming magnetic resonance systems (Doctoral dissertation). Institute of Physics of São Carlos, University of São Paulo, São Carlos. doi:10.11606/T.76.2019.tde-06052019-103714.