Utilization of color parameters to estimate moisture content and nutrient levels of peanut leaves

dc.contributor.authorKeskin, Muharrem
dc.contributor.authorKaranlık, Sema
dc.contributor.authorGörücü Keskin, Serap
dc.contributor.authorSoysal, Yurtsever
dc.date.accessioned2019-07-16T15:54:56Z
dc.date.available2019-07-16T15:54:56Z
dc.date.issued2013
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractLeaf nutrient levels are traditionally quantified by laboratory chemical analysis, which is time-consuming and requires intensive labor and investment. The objective of this study was to predict the moisture content (MC) and nutrient content of peanut leaves from color parameters (CIE Lab) using a chromameter. This method is faster and requires less labor and investment compared to laboratory chemical analysis. Fifty peanut leaf samples were collected from a commercial peanut field. The samples were analyzed for MC, N, P, K, Ca, Mg, Fe, Mn, Zn, and Cu concentrations after color parameters were acquired by chromameter. A positive and high correlation was found between MC and brightness (L*; r = 0.91) and MC and yellowness (b*; r = 0.95). The results show the possibility of predicting the MC of peanut leaves from color data (R2 = 0.88). A strong relationship was also observed between the measured and predicted levels of P and K based on the PLS2 regression model (R2 = 0.88 and R2 = 0.90, respectively). P and K concentrations of peanut leaves can be predicted from the color parameters to within approximately ±0.03% and ±0.15%, respectively. In contrast to MC, P, and K, concentrations of N, Mg, Mn, Zn, and Cu had only moderate correlation, and Fe concentration had the lowest correlation with color parameters (|r| ≤ 0.27).en_US
dc.description.abstractLeaf nutrient levels are traditionally quantified by laboratory chemical analysis, which is time-consuming and requires intensive labor and investment. The objective of this study was to predict the moisture content (MC) and nutrient content of peanut leaves from color parameters (CIE Lab) using a chromameter. This method is faster and requires less labor and investment compared to laboratory chemical analysis. Fifty peanut leaf samples were collected from a commercial peanut field. The samples were analyzed for MC, N, P, K, Ca, Mg, Fe, Mn, Zn, and Cu concentrations after color parameters were acquired by chromameter. A positive and high correlation was found between MC and brightness (L*; r = 0.91) and MC and yellowness (b*; r = 0.95). The results show the possibility of predicting the MC of peanut leaves from color data (R2 = 0.88). A strong relationship was also observed between the measured and predicted levels of P and K based on the PLS2 regression model (R2 = 0.88 and R2 = 0.90, respectively). P and K concentrations of peanut leaves can be predicted from the color parameters to within approximately ±0.03% and ±0.15%, respectively. In contrast to MC, P, and K, concentrations of N, Mg, Mn, Zn, and Cu had only moderate correlation, and Fe concentration had the lowest correlation with color parameters (|r| ≤ 0.27).en_US
dc.identifier.endpage612en_US
dc.identifier.issn1300-011x
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-84883385653en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage604en_US
dc.identifier.urihttps://trdizin.gov.tr/publication/paper/detail/TVRRM09UVTFOUT09
dc.identifier.urihttps://hdl.handle.net/20.500.12483/1928
dc.identifier.volume37en_US
dc.identifier.wosWOS:000323825400011en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofTurkish Journal of Agriculture and Forestryen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US]
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectOrman Mühendisliğien_US
dc.titleUtilization of color parameters to estimate moisture content and nutrient levels of peanut leavesen_US
dc.typeArticleen_US

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