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Quantitative detect...
Quantitative detection of apple watercore and soluble solids content by near infrared transmittance spectroscopy
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- Guo, Zhiming (author)
- Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Jiangsu, Peoples R China.
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- Wang, MingMing (author)
- Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Jiangsu, Peoples R China.
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- Agyekum, Akwasi Akomeah (author)
- Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Jiangsu, Peoples R China.
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- Wu, Jingzhu (author)
- Beijing Technol & Business Univ, Beijing Key Lab Big Data Technol Food Safety, Beijing 100048, Peoples R China.
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- Chen, Quansheng (author)
- Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Jiangsu, Peoples R China.
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- Zuo, Min (author)
- Beijing Technol & Business Univ, Natl Engn Lab Agriprod Qual Traceabil, Beijing 100048, Peoples R China.
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- El-Seedi, Hesham (author)
- Uppsala universitet,Farmakognosi
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- Tao, Feifei (author)
- Mississippi State Univ, Geosyst Res Inst, Bldg 1021, Stennis Space Ctr, MS 39529 USA.
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- Shi, Jiyong (author)
- Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Jiangsu, Peoples R China.
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- Ouyang, Qin (author)
- Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Jiangsu, Peoples R China.
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- Zou, Xiaobo (author)
- Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Jiangsu, Peoples R China.;Jiangsu Univ, High Tech Key Lab Agr Equipment & Intelligentizat, Zhenjiang 212013, Jiangsu, Peoples R China.
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Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Jiangsu, Peoples R China Beijing Technol & Business Univ, Beijing Key Lab Big Data Technol Food Safety, Beijing 100048, Peoples R China. (creator_code:org_t)
- ELSEVIER SCI LTD, 2020
- 2020
- English.
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In: Journal of Food Engineering. - : ELSEVIER SCI LTD. - 0260-8774 .- 1873-5770. ; 279
- Related links:
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https://www.scienced...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Near-infrared (NIR) spectroscopy as an emerging analytical technique was used for the first time to quantitatively detect the watercore degree and soluble solids content (SSC) in apple. To reduce the data processing time and meet the needs of practical application, the variable selection methods including synergy interval (SI), successive projections algorithm (SPA), genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) were used to identify the characteristic variables and simplify the models. The spectral variables closely related to the apple bioactive components were used for the establishment of the partial least squares (PLS) models. The predictive correlation coefficient (R-p), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) were used to estimate the performance of the models. The CARS-PLS models displayed the best prediction performance using 600-1000 nm spectra with R-p, RMSEP, and RPD values of 0.9562, 1.340% and 3.720 for apple watercore degree; 0.9808, 0.327 (o)Bx and 4.845 for apple SSC, respectively. These results demonstrate the potential of the NIR transmittance spectroscopy technology for quantitative detection of SSC and watercore degree in apple fruit.
Subject headings
- LANTBRUKSVETENSKAPER -- Lantbruksvetenskap, skogsbruk och fiske -- Livsmedelsvetenskap (hsv//swe)
- AGRICULTURAL SCIENCES -- Agriculture, Forestry and Fisheries -- Food Science (hsv//eng)
Keyword
- Watercore apple
- Soluble solids content
- NIR transmittance spectroscopy
- Quantitative detection
- Variable selection
- Chemometrics
Publication and Content Type
- ref (subject category)
- art (subject category)
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To the university's database
- By the author/editor
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Guo, Zhiming
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Wang, MingMing
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Agyekum, Akwasi ...
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Wu, Jingzhu
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Chen, Quansheng
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Zuo, Min
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show more...
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El-Seedi, Hesham
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Tao, Feifei
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Shi, Jiyong
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Ouyang, Qin
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Zou, Xiaobo
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show less...
- About the subject
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- AGRICULTURAL SCIENCES
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AGRICULTURAL SCI ...
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and Agriculture Fore ...
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and Food Science
- Articles in the publication
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Journal of Food ...
- By the university
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Uppsala University