Güve-Alev Optimizasyon Algoritması Kullanarak Pleurotus cornucopiae var. citrinopileatus Mantarı Ekstraksiyon Koşullarının Optimizasyonu

Bu çalışmanın amacı, Pleurotus cornucopiae var. citrinopileatus mantarı ekstraksiyon koşullarının yapay zekâ metotlarıyla optimize edilmesidir. Bu amaç doğrultusunda %0, 30, 60, 90 etanol oranı kullanılarak, 1, 2 ve 4 mg/mL ekstrakt konsantrasyonunda elde edilen ekstraktların, 1,2, 3, 4,2 ve 6 pH koşullarındaki antioksidan aktiviteleri mevcut bir deneysel çalışmadan elde edilmiştir. Ekstraksiyon koşullarının modellenmesi Yapay Sinir Ağları (YSA) ile yapılmış ve Güve-Alev Optimizasyon (GAO) algoritması kullanılarak optimize edilmiştir. En iyi tahmin modelini elde etmek için farklı gizli nöron sayıları denenmiş ve en uygun gizli nöron sayısı 5 olarak bulunmuştur. Elde edilen bu modelin hata karelerinin ortalaması ve ortalama mutlak yüzde hatası tüm veri seti için sırasıyla 1,79 ve %3,24 olarak bulunmuştur. Optimizasyon süreci sonrasında maksimum antioksidan aktivite %56,76 olarak bulunmuştur ve bu sonucu elde etmek için optimum ekstraksiyon parametreleri %66,34 etanol oranı, 4 mg/mL ekstrakt konsantrasyonu ve 2,36 pH olarak belirlenmiştir. Bu çalışma, YSA ve GAO algoritmasının birlikte kullanılması ile ekstraksiyon koşullarının optimizasyonunda zaman, emek ve maliyetverimliliği sağlandığını ortaya koymuştur

Optimization of cnc operating parameters to minimize surface roughness of Pinus sylvestris using integrated artificial neural network and genetic algorithm

The surface roughness of wood is affected by the processing conditions and the material structure. So, optimization of operation parameters is very crucial to have minimum surface roughness. In this study, modeling and optimization of surface roughness (Ra) of Scotch pine (Pinus sylvestris) was investigated. Firstly, the samples were cut under different conditions 8 mm, 9 mm and 11mm depth of cut and 12 mm, 14 mm and 16 mm axial depth of cut) in computer numerical control (CNC) machine, and then surface roughness (Ra) values of samples were calculated. Then a prediction model of surface roughness was developed using artificial neural networks (ANN). Optimization process was carried out to reach minimum surface roughness of wood samples by the genetic algorithm (GA) method. MAPE value of the ANN model was found lower than 4,0 %. The optimum CNC operation parameters were 1874,5 rad/s, 3,0 m/min feed rate, 9,7 mm depth of cut and 12 mm for axial depth of cut for minimum surface roughness. As a result of study, surface roughness of Scotch pine wood can be modeled and optimized using integrated ANN and GA methods by saving time and cost

Possibility of using lichen and mistletoe extracts as potential natural wood preservative

Increasing environmental pressures on toxic chemical wood preservatives lead to the development of natural and environmentally friendly wood preservatives. In this study, using possibilities of lichen (Usnea filipendula) and leaves of mistletoe (Viscum album) as potential natural wood preservative were researched. Impregnation procedure was applied at four different concentration levels and with two different extraction methods (hot water and methanol). The concentration levels were arranged as 3%, 5%, 10%, 15% for hot water and as 3.75%, 6.25%, 12.5%, 18.75% for methanol. The treatment procedure has been applied according to the ASTM D 1413 (1988) standard test method. The fungal decay test has been done according to the EN 113 (1996) standard test method using a brown rot fungus, Coniophora puteana for both treated test and untreated control samples. The best results were obtained at the highest concentration level of the solutions. However, the weight losses in treated test specimen have not met the standard requirements. Nevertheless, it can be assumed that both natural extracts provide promising protection performance

Combining artificial neural network and moth-flame optimization algorithm for optimization of ultrasound-assisted and microwave-assisted extraction parameters: Bark of Pinus brutia

In this study, the extraction parameters of Pinus brutia bark were optimized using a hybrid artificial intelligence technique. Firstly, the bark samples were extracted by ultrasound-assisted extraction and microwave-assisted extraction which are defined as ‘green’ extraction methods at different conditions. The selected extraction parameters for ultrasound-assisted extraction were 0:100; 20:80; 40:60; 80:20 (%) ethanol: water ratios; 40 ºC, 60 °C extraction temperatures and 5 min, 10 min, 15 min, 20 min extraction times and for microwave-assisted extraction were 90, 180, 360, 600, 900 (W) microwave power, 0:100; 20:80; 40:60; 60:40; 80:20 (%) ethanol: water ratios. Then Stiasny number, condensed tannin content and reducing sugar content of all extracts were determined. Next, the prediction models were developed for each studied parameter using Artificial Neural Network. Finally, the extraction parameters were optimized using Moth-Flame Optimization Algorithm. After that optimization process, while the extraction time was the same (5 min), the ethanol: water ratio and extraction temperature values differed for the optimization of all studied assays of ultrasound-assisted extraction. Also, microwave power and ethanol: water ratio variables were found in different values for each assay of microwave-assisted extraction. The results showed that the Artificial Neural Network and Moth-Flame Optimization could be a novel and powerful hybrid approach to optimize the extraction parameters of Pinus brutia barks with saving time, cost, chemical and effort

Primjena umjetne neuronske mreže za predviđanje utjecaja dodatka parafina na upojnost vode i debljinsko bubrenje MDF-a

In this study, water absorption and thickness swelling values of medium density fiberboard (MDF) were modelled by artificial neural networks (ANN). MDF panels were produced with different rates of paraffin (0.0-control, 0.5, 1 and 1.5 %) at different press temperatures (170 and 190 °C). After conditioning of MDF, water absorption (WA) and thickness swelling (TS) of samples were carried out at specific intervals within 24 hours. Then, the data obtained from these experiment were modelled using ANN. Paraffin addition rate, press temperature and immersion time in water were used as the input parameters, while WA and TS values of MDF were used as the output parameters. After training of ANN, it was found that correlation coefficients (R) were close to 1 for training, validation, test and all data set. Mean absolute percentage error (MAPE) and mean square error (MSE) were determined as 2.94 % and 0.57, respectively, for all data sets. As a result of this study, the use of proposed ANN model may be recommended to predict the water absorption and thickness swelling of panels instead of complex and time-consuming studies such as empirical formulas.U istraživanju je modelirana upojnost vode i debljinsko bubrenje ploče vlaknatice srednje gustoće (MDF ploče) uz pomoć umjetnih neuronskih mreža (ANN-a). MDF ploče proizvedene su uz dodatak različitih količina parafi na (0,0 – kontrola, 0,5; 1 i 1,5 %) pri različitim temperaturama prešanja (170 i 190 °C). Nakon kondicioniranja MDF ploče, mjerena je upojnost vode (WA) i debljinsko bubrenje (TS) uzoraka u određenim intervalima unutar 24 sata. Zatim su ti podatci modelirani uz pomoć ANN-a. Kao ulazni parametri poslužili su količina parafi na, temperatura prešanja i trajanje namakanja uzoraka u vodi, dok su WA i TS vrijednosti MDF ploče korištene kao izlazni parametri. Nakon provedbe ANN-a utvrđeno je da su koeficijenti korelacije (R) za provedbu, validaciju, ispitivanje i sve skupove podataka blizu 1. Srednja apsolutna pogreška (MAPE) i srednja kvadratna pogreška (MSE) za sve su skupove podataka iznosile 2,94 % i 0,57. Kao rezultat ovog istraživanja može se preporučiti uporaba predloženog ANN modela za predviđanje upojnosti vode i debljinskog bubrenja ploča umjesto složenih i dugotrajnih studija poput empirijskih formula

Total phenolics, tannin contents, antioxidant properties, protein and sensory analysis of Pleurotus ostreatus, Pleurotus citrinopileatus and Pleurotus djamor cultivated on different sawdusts

In mushroom cultivation, it is important to be aware of the impact of the growing substrate. This study investigated the cultivation of various oyster mushrooms, including Pleurotus ostreatus, Pleurotus citrinopileatus, and Pleurotus djamor, on different types of wood sawdust. Total phenolic content, condensed tannins, antioxidant activity by ferric reducing antioxidant power assay, protein and sensory evaluations were performed in cultivated oyster mushrooms. Wood sawdust of Fagus orientalis (oriental beech), Alnus glutinosa (alder), Castanea sativa (chestnut), and Juglans regia (walnut) were used as substrate for studied mushroom type, separately. Because champignon (Agaricus bisporus) was the most consumed mushroom, it was used as control sample. Methanolic extracts of dried mushrooms were used to measure bioactive characteristics. Pleurotus ostreatus samples cultivated in Alnus glutinosa (alder) sawdust substrate had the highest antioxidant activity. The lowest antioxidant activity values were found in Pleurotus djamor cultivated in Juglans regia (walnut) wood sawdust substrate. The highest protein content was measured in Agaricus bisporus as 13,84 %. The other highest protein concentration was found in Pleurotus ostreatus cultivated in Alnus glutinosa (alder) sawdust substrate, at 13,75 %. The lowest protein concentration belonged to Pleurotus citrinopileatus cultivated in Fagus orientalis (oriental beech) sawdust substrate as 9,86 %. While Agaricus bisporus and Pleurotus ostreatus had the highest overall appreciation score, Pleurotus citrinopileatus had the lowest. It has been observed that the substrate content has an important impact on chemical and sensory properties of the oyster mushrooms.  This study provides knowledge on the chemical and sensory characteristics of three different Pleurotus mushroom species cultivated on different composts

Biological Activities of Ethanol Extracts of <i>Hericium erinaceus</i> Obtained as a Result of Optimization Analysis

Mushrooms are one of the indispensable elements of human diets. Edible mushrooms stand out with their aroma and nutritional properties. In this study, some biological activities of the wild edible mushroom Hericium erinaceus were determined. In this context, firstly, the most suitable extraction conditions of the fungus in terms of biological activity were determined. First, 64 different experiments were performed with the Soxhlet device under 40–70 °C extraction temperature, 3–9 h extraction time, and 0.5–2 mg/mL extraction conditions. As a result, a total antioxidant status (TAS) analysis was performed, and the extraction conditions were optimized so that the objective function was the maximum TAS value. The data obtained from the experimental study were modeled with artificial neural networks (ANNs), one of the artificial intelligence methods, and optimized with a genetic algorithm (GA). All subsequent tests were performed using the extract obtained under optimum extraction conditions. The antioxidant capacity of the mushroom was assessed using Rel assay kits and the DPPH and FRAP techniques. The agar dilution method was used to measure the antimicrobial activity. The anti-Alzheimer activity was assessed based on the activities of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). The antiproliferative activity was assessed against the A549 cancer cell line. The total phenolic content was measured using the Folin–Ciocalteu reagent. The measurement of total flavonoids was conducted using the aluminum chloride test. LC-MS/MS equipment was used to screen for the presence of standard chemicals. The optimum extraction conditions were found to be a 60.667 °C temperature, 7.833 h, and 1.98 mg/mL. It was determined that the mushroom has high antioxidant potential. It was determined that the substance was successful at combating common bacterial and fungal strains when used at dosages ranging from 25 to 200 µg/mL. The high antiproliferative effect of the substance was attributed to its heightened concentration. The anti-AChE value was found to be 13.85 μg/mL, while the anti-BChE value was confirmed to be 28.00 μg/mL. The phenolic analysis of the mushroom revealed the presence of 13 chemicals. This investigation found that H. erinaceus exhibits robust biological activity when extracted under appropriate circumstances

Türkiye’den Toplanan Bazı Yabani Mantarların Antimikrobiyal ve Anti-Quorum Sensing (Çoğunluğu Algılama) Aktiviteleri

msufbdYabani mantarlar, tıbbi özellikleri nedeniyleçok eski tarihten beri bilinen, ormanların önemli bir parçasıdır. Bu çalışmada, Karadeniz bölgesinden toplananbazı yabani mantarların (Amanitarubescens, Russula delica, Lactarius sp.) anti mikrobiyal ve anti-quorumsensing (çoğunluğu algılama) aktiviteleri incelenmiştir. Mantar ekstraktları süper kritik akışkanekstraksiyonu metodu ile hazırlanmıştır. Ekstraktların antimikrobiyalpotansiyelleri Staphylococcus aureusATCC 25923, Escherichia coli ATCC25922, Enterococcus faecalis ATCC29212, Pseudomonas aeruginosa ATCC27853, Klebsiella pneumoniae ATCC13883, Proteus mirabilis ATCC 7002, Listeria monocytogenes ATCC 43251 and Candida albicans ATCC 10231mikroorganizmalarına karşı agar kuyucuk difüzyon yöntemiyle test edilmiştir.Anti-quorum sensing (çoğunluğu algılama) aktivite ise Chromobacterium violaceum ATCC 12472 bakterisi üzerinde testedilmiştir. Sonuçlar, Amanita rubescensmantar ekstraktının Staphylococcusaureus' u inhibe ettiğini, Amanitarubescens ve Lactarius ssp. ekstraktlarının Chromobacterium violaceum a karşı anti-quorum sensing (çoğunluğualgılama) aktiviteye sahip olduğunu göstermiştir.Wild mushrooms are an important part of foreststhat have been known since the early history for their excellent medicinalproperties. In this study, anti-microbial and anti-quorum sensing activities ofsome wild mushrooms (Amanita rubescens, Russula delica, Lactarius sp.) collected from the Black Sea regionin Turkey were investigated. Mushroom extracts were prepared by supercriticalfluid extraction method. Antimicrobial potential of extracts was tested by agarwell diffusion method against Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922, Enterococcus faecalis ATCC 29212, Pseudomonas aeruginosa ATCC 27853, Klebsiella pneumoniae ATCC 13883, Proteus mirabilis ATCC 7002, Listeria monocytogenes ATCC43251 and Candida albicans ATCC10231. Anti-quorum sensing activity was tested on Chromobacterium violaceum ATCC 12472 bacteria.  The results revealed that Amanita rubescens showed an inhibitory effect against Staphylococcusaureus and Amanita rubescens and Lactariussp. extracts showed anti-quorum sensing activity against Chromobacteriumviolaceum.34769

Possibility of using lichen and mistletoe extracts as potential natural wood preservative

Increasing environmental pressures on toxic chemical wood preservatives lead to the development of natural and environmentally friendly wood preservatives. In this study, using possibilities of lichen (Usnea filipendula) and leaves of mistletoe (Viscum album) as potential natural wood preservative were researched. Impregnation procedure was applied at four different concentration levels and with two different extraction methods (hot water and methanol). The concentration levels were arranged as 3%, 5%, 10%, 15% for hot water and as 3.75%, 6.25%, 12.5%, 18.75% for methanol. The treatment procedure has been applied according to the ASTM D 1413 (1988) standard test method. The fungal decay test has been done according to the EN 113 (1996) standard test method using a brown rot fungus, Coniophora puteana for both treated test and untreated control samples. The best results were obtained at the highest concentration level of the solutions. However, the weight losses in treated test specimen have not met the standard requirements. Nevertheless, it can be assumed that both natural extracts provide promising protection performance