Matches in SemOpenAlex for { <https://semopenalex.org/work/W3100841132> ?p ?o ?g. }
Showing items 1 to 99 of
99
with 100 items per page.
- W3100841132 endingPage "3175" @default.
- W3100841132 startingPage "3165" @default.
- W3100841132 abstract "Abstract BACKGROUND This paper proposes a novel method to improve accuracy and efficiency in detecting the quality of blueberry fruit, taking advantage of deep learning in classification tasks. We first collected ‘Tifblue’ blueberries at seven different stages of maturity (10–70 days after full bloom) and measured the pigments of the blueberry skin and the total sugar and the total acid of the pulp. We then established a skin pigment contents prediction network (SPCPN), based on the correlation between the pigments and blueberry pictures, and also a fruit intrinsic qualities prediction network (FIQPN), based on the correlation between the pigments and fruit qualities. Finally, the SPCPN and FIQPN were consolidated into the blueberry quality parameters prediction network (BQPPN). RESULTS The results showed that the anthocyanins in the blueberry skin were significantly correlated with the total sugar, total acid, and sugar / acid ratio of the fruit. After verification, the results also indicated that, for the prediction of anthocyanins, chlorophyll, and the anthocyanin / chlorophyll ratio, the SPCPN network model was found to achieve higher R 2 (RMSE) values of 0.969 (0.139), 0.955 (0.005), 0.967 (15.4), respectively. The FIQPN network model was also able to evaluate the value of total sugar (R 2 = 0.940, RMSE = 4.905), total acid (R 2 = 0.930, RMSE = 2.034), and the sugar / acid ratio (R2 = 0.973, RMSE = 0.580). CONCLUSION The above results indicated the potential for utilizing deep learning technology to predict the quality indicators of blueberry before harvesting. © 2020 Society of Chemical Industry" @default.
- W3100841132 created "2020-11-23" @default.
- W3100841132 creator A5003334032 @default.
- W3100841132 creator A5010777120 @default.
- W3100841132 creator A5037001679 @default.
- W3100841132 creator A5040929667 @default.
- W3100841132 creator A5073591730 @default.
- W3100841132 date "2020-12-11" @default.
- W3100841132 modified "2023-09-30" @default.
- W3100841132 title "Non‐destructive detection of blueberry skin pigments and intrinsic fruit qualities based on deep learning" @default.
- W3100841132 cites W1536680647 @default.
- W3100841132 cites W1969733293 @default.
- W3100841132 cites W1970088622 @default.
- W3100841132 cites W1983051554 @default.
- W3100841132 cites W2002029344 @default.
- W3100841132 cites W2016685826 @default.
- W3100841132 cites W2025099310 @default.
- W3100841132 cites W2043108780 @default.
- W3100841132 cites W2061343288 @default.
- W3100841132 cites W2065621095 @default.
- W3100841132 cites W2068547742 @default.
- W3100841132 cites W2068620099 @default.
- W3100841132 cites W2079779343 @default.
- W3100841132 cites W2093816871 @default.
- W3100841132 cites W2131726990 @default.
- W3100841132 cites W2141588759 @default.
- W3100841132 cites W2142271007 @default.
- W3100841132 cites W2153653466 @default.
- W3100841132 cites W2194775991 @default.
- W3100841132 cites W2275995274 @default.
- W3100841132 cites W2302793367 @default.
- W3100841132 cites W2461607357 @default.
- W3100841132 cites W2569272946 @default.
- W3100841132 cites W2899248844 @default.
- W3100841132 cites W2913815864 @default.
- W3100841132 cites W4256282399 @default.
- W3100841132 doi "https://doi.org/10.1002/jsfa.10945" @default.
- W3100841132 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33211339" @default.
- W3100841132 hasPublicationYear "2020" @default.
- W3100841132 type Work @default.
- W3100841132 sameAs 3100841132 @default.
- W3100841132 citedByCount "7" @default.
- W3100841132 countsByYear W31008411322021 @default.
- W3100841132 countsByYear W31008411322022 @default.
- W3100841132 countsByYear W31008411322023 @default.
- W3100841132 crossrefType "journal-article" @default.
- W3100841132 hasAuthorship W3100841132A5003334032 @default.
- W3100841132 hasAuthorship W3100841132A5010777120 @default.
- W3100841132 hasAuthorship W3100841132A5037001679 @default.
- W3100841132 hasAuthorship W3100841132A5040929667 @default.
- W3100841132 hasAuthorship W3100841132A5073591730 @default.
- W3100841132 hasConcept C105795698 @default.
- W3100841132 hasConcept C139945424 @default.
- W3100841132 hasConcept C144027150 @default.
- W3100841132 hasConcept C178790620 @default.
- W3100841132 hasConcept C185592680 @default.
- W3100841132 hasConcept C2776373379 @default.
- W3100841132 hasConcept C2777108408 @default.
- W3100841132 hasConcept C2778945092 @default.
- W3100841132 hasConcept C31903555 @default.
- W3100841132 hasConcept C33923547 @default.
- W3100841132 hasConcept C59822182 @default.
- W3100841132 hasConcept C64584667 @default.
- W3100841132 hasConcept C86803240 @default.
- W3100841132 hasConceptScore W3100841132C105795698 @default.
- W3100841132 hasConceptScore W3100841132C139945424 @default.
- W3100841132 hasConceptScore W3100841132C144027150 @default.
- W3100841132 hasConceptScore W3100841132C178790620 @default.
- W3100841132 hasConceptScore W3100841132C185592680 @default.
- W3100841132 hasConceptScore W3100841132C2776373379 @default.
- W3100841132 hasConceptScore W3100841132C2777108408 @default.
- W3100841132 hasConceptScore W3100841132C2778945092 @default.
- W3100841132 hasConceptScore W3100841132C31903555 @default.
- W3100841132 hasConceptScore W3100841132C33923547 @default.
- W3100841132 hasConceptScore W3100841132C59822182 @default.
- W3100841132 hasConceptScore W3100841132C64584667 @default.
- W3100841132 hasConceptScore W3100841132C86803240 @default.
- W3100841132 hasFunder F4320309870 @default.
- W3100841132 hasIssue "8" @default.
- W3100841132 hasLocation W31008411321 @default.
- W3100841132 hasOpenAccess W3100841132 @default.
- W3100841132 hasPrimaryLocation W31008411321 @default.
- W3100841132 hasRelatedWork W217052226 @default.
- W3100841132 hasRelatedWork W2174129936 @default.
- W3100841132 hasRelatedWork W2312114828 @default.
- W3100841132 hasRelatedWork W2352894057 @default.
- W3100841132 hasRelatedWork W2359634080 @default.
- W3100841132 hasRelatedWork W2363102867 @default.
- W3100841132 hasRelatedWork W2380066957 @default.
- W3100841132 hasRelatedWork W2385629635 @default.
- W3100841132 hasRelatedWork W2391361307 @default.
- W3100841132 hasRelatedWork W2767973484 @default.
- W3100841132 hasVolume "101" @default.
- W3100841132 isParatext "false" @default.
- W3100841132 isRetracted "false" @default.
- W3100841132 magId "3100841132" @default.
- W3100841132 workType "article" @default.