Unveiling targeted spatial metabolome of rice seed at the dough stage using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry imaging

Zhao, Yao; Hu, Jitao; Zhang, Yilin; Tao, Han; Li, Linying; He, Yuqing; Zhang, Xueying; Zhang, Chi; Hong, Gaojie

doi:10.1016/j.foodres.2023.113578

Cited by 4 publications

(1 citation statement)

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“…Y. Zhao, Hu, et al. (2023) employed MALDI‐MSI to uncover the spatial distribution of freely soluble sugars (glucose, fructose, sucrose, and maltose) and other small molecule metabolites in rice seeds at the dough stage. They also constructed a colocalization phylogenetic tree, providing insights into the nutritional differences between brown rice and white rice and offering guidance for a healthy diet.…”

Section: Application Of Msi In Food Analysismentioning

confidence: 99%

Revolutionizing food science with mass spectrometry imaging: A comprehensive review of applications and challenges

Shen,

Wang,

Wang

et al. 2024

Comp Rev Food Sci Food Safe

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Food science encounters increasing complexity and challenges, necessitating more efficient, accurate, and sensitive analytical techniques. Mass spectrometry imaging (MSI) emerges as a revolutionary tool, offering more molecular‐level insights. This review delves into MSI's applications and challenges in food science. It introduces MSI principles and instruments such as matrix‐assisted laser desorption/ionization, desorption electrospray ionization, secondary ion mass spectrometry, and laser ablation inductively coupled plasma mass spectrometry, highlighting their application in chemical composition analysis, variety identification, authenticity assessment, endogenous substance, exogenous contaminant and residue analysis, quality control, and process monitoring in food processing and food storage. Despite its potential, MSI faces hurdles such as the complexity and cost of instrumentation, complexity in sample preparation, limited analytical capabilities, and lack of standardization of MSI for food samples. While MSI has a wide range of applications in food analysis and can provide more comprehensive and accurate analytical results, challenges persist, demanding further research and solutions. The future development directions include miniaturization of imaging devices, high‐resolution and high‐speed MSI, multiomics and multimodal data fusion, as well as the application of data analysis and artificial intelligence. These findings and conclusions provide valuable references and insights for the field of food science and offer theoretical and methodological support for further research and practice in food science.

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Section: Application Of Msi In Food Analysismentioning

confidence: 99%