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        Pollen performance modelling with an artificial neural network on commercial stone fruit cultivars

        Sultan Filiz Güçlü,Ziya Öncü,Fatma Koyuncu 한국원예학회 2020 Horticulture, Environment, and Biotechnology Vol.61 No.1

        Pollen tube growth and pollen germination percentage are key factors for successful fruit set. Pollen performance is critical for the production and breeding of flowering plants and in agricultural systems in terms of fruit development. This study was carried out to predict pollen tube growth and pollen germination percentage in four stone fruits species (cherry (Prunus avium), apricot (Prunus armeniaca), plum (Prunus domestica), and peach (Prunus persica)) using a neural network. For this purpose, we measured pollen tube length and pollen germination rates under in vitro conditions. For the in vitro test, pollen grains of four stone fruit cultivars were sown in three different media and incubated at seven different temperatures for four incubation periods. A layered neural network was used for estimating the pollen germination rate and pollen tube length related to the in vitro condition. This study suggests a method for estimating the pollen germination rate and pollen tube length using artificial neural networks. The performed artificial neural networks produced an efficient prediction from in vitro data. The determination coefficients obtained between the observed and predicted data sets are 0.86 (for germination rate) and 0.81 (for tube length), indicating an accurate estimation of the in vitro data. In our case, the network that produced the best result had a 4:9:2 architecture.

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        Decolorisation of aqueous crystal violet solution by a new nanoporous carbon: Equilibrium and kinetic approach

        Fuat Gu¨ zel,Hasan Sayg˘ılı,Gu¨ lbahar Akkaya Sayg˘ılı,Filiz Koyuncu 한국공업화학회 2014 Journal of Industrial and Engineering Chemistry Vol.20 No.5

        A new nanoporous carbon from tomato paste waste (TWNC) was prepared. The surface area, total pore volume, average pore diameter of TWNC was found as 722.17 m2 g-1, 0.476 cm3 g-1 and 2.644 nm, respectively. The effects of solution pH, adsorbent dose, initial concentration, ionic strength, contact time, and temperature were studied. Adsorption kinetics was found to be best represented by the pseudo second order model. Isotherm data were fitted well to the both Langmuir and Freundlich models. Maximum adsorption capacity was found as 68.97 mg g-1 at 50 ℃. Thermodynamic parameters showed that the process was spontaneous and endothermic.

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