TY  - JOUR
TT  - Data mining aproach for prediction of fruit color properties
AU  - Demir, Bünyamin
AU  - Gürbüz, Feyza
AU  - Eski, İkbal
AU  - Kuş, Zeynel Abidin
PY  - 2018
DA  - January
DO  - 10.17097/ataunizfd.365231
JF  - Atatürk Üniversitesi Ziraat Fakültesi Dergisi
PB  - Ataturk University
WT  - DergiPark
SN  - 1300-9036
SP  - 37
EP  - 43
VL  - 49
IS  - 1
KW  - Elma
KW  - hue açısı
KW  - L*a*b*
KW  - renk uzayı
N2  - Color is an important feature that dictates the quality and consumer preferences of many fresh fruits andvegetables. In color measurement of fruits, the CIE L*a*b* color space is widely used since it is a uniform color scale. In thisstudy, raw data for the color features of apple varieties were divided into two parts as test and train data in the first stage, analyseswere performed on train data and tests were performed on test data. The rules obtained by applying the Find laws algorithm wereused to estimate the color index (CI), hue angle (h *) and Chroma (C *) values. In the second stage, raw data were classified byStrict and Liberal options of cluster analysis. Find Laws algorithm was applied to each cluster and 7 different prediction ruleswere obtained for CI, h*and C* parameters. R2values of the rules were compared and the rules with the most accurate outcomeswere identified.:
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UR  - https://doi.org/10.17097/ataunizfd.365231
L1  - https://dergipark.org.tr/en/download/article-file/402289
ER  -