2015
DOI: 10.1016/j.scienta.2014.12.037
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Detecting maturity of persimmon fruit based on image processing technique

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Cited by 114 publications
(46 citation statements)
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“…Therefore, the NP kept the desirable sensory characteristics of persimmons compared with the WCr and CB, contributing to a greater consumer liking of the fruits during an extended period. Mohammadi et al (2015) found that sensory quality was associated with the degree of maturity of persimmon fruits, as verified in the present study. In addition, Chitarra & Chitarra (2005) reported increased acceptance of ripe fruits, because, in this stage, their color, odor, flavor, and texture changes, making them suitable for consumption.…”
Section: Resultssupporting
confidence: 90%
“…Therefore, the NP kept the desirable sensory characteristics of persimmons compared with the WCr and CB, contributing to a greater consumer liking of the fruits during an extended period. Mohammadi et al (2015) found that sensory quality was associated with the degree of maturity of persimmon fruits, as verified in the present study. In addition, Chitarra & Chitarra (2005) reported increased acceptance of ripe fruits, because, in this stage, their color, odor, flavor, and texture changes, making them suitable for consumption.…”
Section: Resultssupporting
confidence: 90%
“…The use of classification systems based on RGB model to identify the maturation degree has been successful in the analysis of palm fruits in general (Zhang et al, 2014;Mohammadi et al, 2015). However, in some cases where the colorimetric variation between stages is subtle, the RGB model may present difficulties in distinguishing maturation stages being influenced by the intensity of incident light (Hudzari et al, 2010).…”
Section: Resultsmentioning
confidence: 99%
“…The color is a widely used parameter in the selection and harvesting of fruits as it is a direct indicator of quality and maturation stage presenting relation with physical and chemical attributes (Choong et al, 2006;Pu et al, 2015). Colorimetric characteristics such as hue (Tan et al, 2010;Wisutiamonku et al, 2015) and red, green and blue intensity (Mohammadi et al, 2015;Gomes Júnior et al, 2017) present important results in the identification on different stages on various fruits ripening.…”
Section: Introductionmentioning
confidence: 99%
“…The overall accuracy of the system obtained is 90.24%. Classification performed using LDA and QDA, the accuracy level is higher in the case of QDA [21] In [31] define Mango fruit maturity detection is done using its external color. Special species mangos "Langdo" had the same color in its life span.…”
Section: Maturity Identificationmentioning
confidence: 99%