Appraisal of Three Proximal Sensing Systems to Estimate Macronutrient Contents of Detached Soybean Leaves

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dc.authoridSEKERLI, Yunus Emre/0000-0002-7954-8268
dc.authoridSehri, Mustafa/0000-0003-3687-8942
dc.contributor.authorKeskin, Muharrem
dc.contributor.authorSay, Sait M.
dc.contributor.authorSekerli, Yunus Emre
dc.contributor.authorSehri, Mustafa
dc.date.accessioned2024-09-18T20:08:21Z
dc.date.available2024-09-18T20:08:21Z
dc.date.issued2021
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractOverapplication of fertilizers is common and may lead to plant toxicity and pollution of water resources in agriculture. A practical method is needed to estimate nutrient stress quickly, easily, and economically for a sustainable management. This study dealt with the prediction of leaf moisture content (MC) and macronutrient contents including nitrogen (N), phosphorus (P), and potassium (K) of soybean leaves using three different optical instruments of chromameter, chlorophyll meter and fluorometer. Forty-five leaf samples from a commercial soybean field were obtained. Color parameters (L*, a*, b*), SPAD (soil plant analysis development) values and quantum yield (QY) values were quantified for each leaf sample. Leaf and soil samples were analyzed using standard leaf and soil chemical analysis procedures. Correlation analysis, principal component analysis (PCA) and partial least square regression (PLSR) were used for data analysis. High correlation was found between two color parameters (L* and b*) with MC and macronutrient contents (r >= 0.65) and also, among SPAD, QY, MC, and macronutrient contents (r >= 0.70). The prediction models were evaluated based on the RMSEP (root mean square error of prediction) and R (2) (coefficient of determination) values. The results showed that soybean leaf N content can be estimated using all three optical instruments with chromameter giving slightly better results (RMSEP = 0.23%, R (2) = 0.80). Concerning the MC, chlorophyll meter gave slightly better prediction performance (RMSEP = 2.69%, R (2) = 0.73) than the other two instruments. Hence, results suggest that these three optical instruments can be used to assess the macronutrient contents of soybean leaves quickly, easily, and economically.en_US
dc.identifier.doi10.1080/00103624.2021.1900862
dc.identifier.endpage1953en_US
dc.identifier.issn0010-3624
dc.identifier.issn1532-2416
dc.identifier.issue16en_US
dc.identifier.scopus2-s2.0-85103272802en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1943en_US
dc.identifier.urihttps://doi.org/10.1080/00103624.2021.1900862
dc.identifier.urihttps://hdl.handle.net/20.500.12483/8791
dc.identifier.volume52en_US
dc.identifier.wosWOS:000634126400001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.ispartofCommunications in Soil Science and Plant Analysisen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectChlorophyll meteren_US
dc.subjectchromameteren_US
dc.subjectfluorometeren_US
dc.subjectsoybean leafen_US
dc.subjectmoistureen_US
dc.subjectnutrient stressen_US
dc.titleAppraisal of Three Proximal Sensing Systems to Estimate Macronutrient Contents of Detached Soybean Leavesen_US
dc.typeArticleen_US

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