Matches in SemOpenAlex for { <https://semopenalex.org/work/W1716451738> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W1716451738 endingPage "276" @default.
- W1716451738 startingPage "266" @default.
- W1716451738 abstract "An apple that is soft and lacks juiciness during consumption is characterized as a mealy fruit. Since mealiness in apple is considered as an undesirable quality parameter, this work aimed at developing classification models based on biospeckle imaging in order to recognize mealy from non-mealy apples. To evaluate the potential of biospeckle imaging in detection of mealiness, a total of 760 ‘Red Delicious’ apples were harvested. The 540 samples were stored under cold conditions for various time periods from 0 to 5 months. The remaining samples were kept at 20 °C and 95% relative humidity for 10–26 days. Biospeckle images of each apple were acquired at wavelengths of 680 and 780 nm, respectively. Biospeckle imaging was immediately followed by a confined compression test to measure fruit stiffness and juiciness. These parameters were used to categorize the samples into three classes called fresh, semi-mealy, and mealy. Results of clustering based on a self-organizing map showed that apple fruit are mealy when their stiffness and juiciness are less than 20 kN m−1 and 5 cm2, respectively. After classification of apples by destructive methods, time-historical speckle patterns were configured and biospeckle features such as the inertia moment, the absolute value of differences, and autocorrelation were extracted. Results showed that biospeckle activity for fresh samples was higher than semi-mealy and mealy. Finally, several neural network models were developed to classify apples. First, classification of apples into mealy and non-mealy classes was carried out, and then non-mealy apples were classified into fresh and semi-mealy classes. The best classification accuracy for fresh (81.7%) and semi-mealy (70.9%) apples were achieved at 780 nm. However, much better result (77.3% accuracy) for classification of mealy apples was observed at the wavelength of 680 nm." @default.
- W1716451738 created "2016-06-24" @default.
- W1716451738 creator A5025288449 @default.
- W1716451738 creator A5028123749 @default.
- W1716451738 creator A5049069387 @default.
- W1716451738 creator A5069715966 @default.
- W1716451738 creator A5075333376 @default.
- W1716451738 date "2016-02-01" @default.
- W1716451738 modified "2023-09-24" @default.
- W1716451738 title "Non-destructive identification of mealy apples using biospeckle imaging" @default.
- W1716451738 cites W1969757083 @default.
- W1716451738 cites W1972018632 @default.
- W1716451738 cites W1977280372 @default.
- W1716451738 cites W1988395609 @default.
- W1716451738 cites W1997234929 @default.
- W1716451738 cites W1998158680 @default.
- W1716451738 cites W2006110059 @default.
- W1716451738 cites W2006533863 @default.
- W1716451738 cites W2014956518 @default.
- W1716451738 cites W2016001035 @default.
- W1716451738 cites W2031753582 @default.
- W1716451738 cites W2034070347 @default.
- W1716451738 cites W2038934364 @default.
- W1716451738 cites W2040609939 @default.
- W1716451738 cites W2048428880 @default.
- W1716451738 cites W2053512934 @default.
- W1716451738 cites W2056314199 @default.
- W1716451738 cites W2066736828 @default.
- W1716451738 cites W2073219180 @default.
- W1716451738 cites W2077903554 @default.
- W1716451738 cites W2089224720 @default.
- W1716451738 cites W2121087324 @default.
- W1716451738 cites W2152384642 @default.
- W1716451738 cites W2161427324 @default.
- W1716451738 cites W2165624207 @default.
- W1716451738 doi "https://doi.org/10.1016/j.postharvbio.2015.09.001" @default.
- W1716451738 hasPublicationYear "2016" @default.
- W1716451738 type Work @default.
- W1716451738 sameAs 1716451738 @default.
- W1716451738 citedByCount "28" @default.
- W1716451738 countsByYear W17164517382016 @default.
- W1716451738 countsByYear W17164517382017 @default.
- W1716451738 countsByYear W17164517382018 @default.
- W1716451738 countsByYear W17164517382019 @default.
- W1716451738 countsByYear W17164517382020 @default.
- W1716451738 countsByYear W17164517382021 @default.
- W1716451738 countsByYear W17164517382022 @default.
- W1716451738 countsByYear W17164517382023 @default.
- W1716451738 crossrefType "journal-article" @default.
- W1716451738 hasAuthorship W1716451738A5025288449 @default.
- W1716451738 hasAuthorship W1716451738A5028123749 @default.
- W1716451738 hasAuthorship W1716451738A5049069387 @default.
- W1716451738 hasAuthorship W1716451738A5069715966 @default.
- W1716451738 hasAuthorship W1716451738A5075333376 @default.
- W1716451738 hasConcept C144027150 @default.
- W1716451738 hasConcept C86803240 @default.
- W1716451738 hasConceptScore W1716451738C144027150 @default.
- W1716451738 hasConceptScore W1716451738C86803240 @default.
- W1716451738 hasLocation W17164517381 @default.
- W1716451738 hasOpenAccess W1716451738 @default.
- W1716451738 hasPrimaryLocation W17164517381 @default.
- W1716451738 hasRelatedWork W1586861090 @default.
- W1716451738 hasRelatedWork W2085640057 @default.
- W1716451738 hasRelatedWork W2563426484 @default.
- W1716451738 hasRelatedWork W2803764782 @default.
- W1716451738 hasRelatedWork W2979010960 @default.
- W1716451738 hasRelatedWork W3101620726 @default.
- W1716451738 hasRelatedWork W3109291316 @default.
- W1716451738 hasRelatedWork W3158487713 @default.
- W1716451738 hasRelatedWork W2561379343 @default.
- W1716451738 hasRelatedWork W2965631298 @default.
- W1716451738 hasVolume "112" @default.
- W1716451738 isParatext "false" @default.
- W1716451738 isRetracted "false" @default.
- W1716451738 magId "1716451738" @default.
- W1716451738 workType "article" @default.