A novel non-destructive detection of deteriorative dried longan fruits using machine learning algorithms based on low field nuclear magnetic resonance

Fu, Yu; Wang, Yu; Lin, Wei; Deng, Yue; Sun, Hongli; Yang, Yu; Lan, Yanling; Cai, Haoyang; Sun, Qun

doi:10.1007/s11694-021-01190-4

Cited by 9 publications

(2 citation statements)

References 35 publications

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“…Quantitative analysis of fat content [38,39] Transverse relaxation and magnetic resonance imaging were measured Shrimp Testing of dryness and quality [40] Combined with deep learning neural network (DLNN) algorithm, lateral relaxation time was measured Longan Distinguishing between healthy fruit and defective fruit [41] US It is composed of ultrasonic pulse generator, special ultrasonic transmitting and receiving transducer, digital oscilloscope, and computer…”

Section: Tuna and Beefmentioning

confidence: 99%

“…The results demonstrated that the technique was a quick and non-destructive way to guarantee the quality of seafood. Fu et al [ 41 ] developed a novel non-destructive testing system based on low-field nuclear magnetic resonance (NMR) and deep learning neural network (DLNN) algorithms. Based on LF-NMR and MRI, the system characterized the water boundary state and distribution in dried longan fruit.…”

Section: Nuclear Magnetic Resonance (Nmr) Detection Equipmentmentioning

confidence: 99%

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Intelligent System/Equipment for Quality Deterioration Detection of Fresh Food: Recent Advances and Application

Wang,

Zhang,

Jiang

et al. 2024

Foods

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The quality of fresh foods tends to deteriorate rapidly during harvesting, storage, and transportation. Intelligent detection equipment is designed to monitor and ensure product quality in the supply chain, measure appropriate food quality parameters in real time, and thus minimize quality degradation and potential financial losses. Through various available tracking devices, consumers can obtain actionable information about fresh food products. This paper reviews the recent progress in intelligent detection equipment for sensing the quality deterioration of fresh foods, including computer vision equipment, electronic nose, smart colorimetric films, hyperspectral imaging (HSI), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), ultrasonic non-destructive testing, and intelligent tracing equipment. These devices offer the advantages of high speed, non-destructive operation, precision, and high sensitivity.

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