Empirical reduction of rind effect on rind and flesh absorbance for evaluation of durian maturity using near infrared spectroscopy

Phuangsombut, Kaewkarn; Phuangsombut, Arthit; Talabnark, Ariyanan; Terdwongworakul, Anupun

doi:10.1016/j.postharvbio.2018.04.004

Cited by 12 publications

(1 citation statement)

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“…The NIRS inspection technology for agricultural products utilizes the absorption and transform of spectrum energy to perform qualitative and quantitative analyses on the compositions of agricultural products. Currently, many efforts have been done on the applications of this technology on agricultural products such as apples, cherries, bananas, grapes, peppers, and paddy rice [11][12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Assessment and Feasibility Study of Lemon Ripening Using X-ray Image of Information Visualization

et al. 2021

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Digital radiography (DR) is a mature technology and has been broadly used in medical diagnosis. Currently, it’s also used for fruit quality inspection in the market. This purpose of the study is to conduct non-destructive experiments for visual comparisons of digital radiography images, further construct visualized grayscale image analysis technology, and analyze the changes in lemon quality and ripening using quantitative statistical methods. The materials used for the experiments were three lemons of different ripening. A general medical X-ray DR system for was used in this study for 2D digital radiography. The medical X-ray DR images were created based on the Digital Imaging and Communications in Medicine (DICOM) standard. Photometric interpretation of monochrome was applied to create multi-layered grayscale images. Then quantitative analyses and comparisons were performed with image matrix structures and grayscale pixel values in the tissues using visualization techniques and statistical methods. After layer segmentation on the radiological images, the correlations between the lemon structures and tissue changes were assessed by using the Kruskal–Wallis test. The results showed that the p values for lemon, fiber, and pulp were all under 0.05, while the peel layer did not exhibit significant change. The pulp layer is the best region for statistical analyses to determine the lemon ripening. In conclusion, this study can provide a solid reference for future quality classification in the agricultural market. The research findings can be referenced for developing computing techniques applied to agricultural inspection, expanding the scope of application of the medical DR technology.

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