Tarla Bitkileri Bölümü Koleksiyonu

Bu koleksiyon için kalıcı URI

https://hdl.handle.net/20.500.12428/2750

Listeleniyor 1 - 20 / 36

Farklı Biçim Uygulamalarına Bazı Sorgum Sudanotu Melezi Çeşitlerinin Agronomik Özellikleri ile Otunun Enerji Değerlerindeki Değişimlerin İncelenmesi
(Çanakkale Onsekiz Mart Üniversitesi, 2024) Özsüer, Münir Sadi; Alatürk, Fırat
Bu çalışma sorgum sudanotu melezi (SSM) çeşitlerinde (Nutri Honey ve Nutrima) farklı hasat uygulamalarına bağlı olarak toprak üstü ve toprak altı biomass üretimi ile yaprak ve sapların enerji içeriklerinin belirlenmesi amacıyla 2020-2021 yıllarında Çanakkale Onsekiz Mart Üniversitesi Ziraat Fakültesi araştırma alanında yürütülmüştür. Bölünmüş parseller deneme desenine göre 4 tekrarlamalı olarak kurulan araştırmada ana parselleri çeşitler (Nutri Honey ve Nutrima), alt parselleri ise biçim yükseklikleri (bitki boyu 30, 60, 90, 120, 150 cm olduğunda ve fizyolojik olum döneminde hasat) oluşturmuştur. Araştırmada bitkilerle ilgili olarak yeşil ot verimi, yaprak, sap ve salkım oranları, kök miktarı, yaprak ve sap kısımlarına ait TSBM, ME, NE ve SE değerleri incelenmiştir. Toplam yeşil ot verimleri biçimdeki bitki boyunun artışına bağlı olarak artmıştır. Nutri Honey çeşidinin toplam yeşil ot üretimi (7323.0 kg da-1) Nutrima’ya (7019.3 kg da-1) göre daha yüksek olmuştur. Bitkide büyümeye bağlı olarak yaprak oranları düşerken, sap ve salkım oranlarında artışlar olmuştur. Bitkilerde boy uzaması ile kök üretimi arasında olumlu ilişki olduğu ve boy uzunluğu arttıkça üretilen kök miktarının da arttığı tespit edilmiştir. Yaprakların TSBM içerikleri saplara göre %4.82, ME içerikleri %5.63, NE içerikleri %5.43 ve SE içerikleri %4.84 daha yüksek olmuştur. Yapılan çalışmanın sonunda benzer ekolojilerde kaba yem kaynağı olarak her iki sorgum sudanotu melezi çeşitlerinin yetiştirilmesi ve 150 cm bitki boyuna ulaştıktan sonra hasat edilerek yetiştirme döneminde iki kere verim alınması önerilmektedir.
Evaluation of the opacity and protein quality of maize kernels by image analysis
(Maydica-Ist Sper Cerealicoltur, 2025) Üçkan, Kerem; Şentürk, Nilay; Uydaş, Melike; Kahrıman, Fatih
The protein content and quality in maize significantly influence grain quality, driving global efforts to develop high-protein-quality genotypes. Opacity serves as a key phenotypic selection criterion in these efforts due to its relationship with essential amino acid content. This study investigates the differentiation of opaque maize kernels using computer-aided software and explores the relationship between opacity levels and color spaces (RGB, HSV, Lab). Seed samples from 10 maize genotypes (1000 seeds) with varying opacity levels were imaged on a light table in embryo-up and embryo-down orientations. Particle analysis and thresholding performed in R determined opacity levels and provided numerical data for RGB, HSV, and Lab color spaces. Protein, lysine, and tryptophan contents were analyzed through reference methods. Correlation and regression analyses assessed relationships between opacity levels (visual and image-processed) and biochemical components, and color space channels. Protein content ranged from 6.66% to 11.62%, lysine from 0.266% to 0.450%, and tryptophan from 0.034% to 0.092% among opacity groups. Relationships between visual and image-processed opacity levels showed R2 = 0.57 (embryo-up) and R2 = 0.65 (embryo-down). Notably, channels of the HSV color space correlated with lysine and tryptophan contents. This study demonstrates that image processing effectively evaluates opacity levels and protein quality in maize using color space data, offering a promising tool for phenotypic selection.
Discrimination accuracy of haploid and diploid maize seeds using NIR spectroscopy coupled with different machine learning algorithms and data pretreatment methods
(Taylor & Francis Inc, 2025) Kahrıman, Fatih; Polat, Adem; Tiryaki, Ali Murat; Eskizeybek, Volkan; Fidan, Sertuğ; Songur, Umut
Spectral data collected at the single seed level allows determination of the biochemical content of the seed sample, as well as to identify the seed class. NIR (Near Infrared) spectroscopy provides a more precise method for differentiating haploid and diploid seeds in maize than traditional visual examination. In this study, classification models that can be used in the separation of haploid and diploid maize seeds were developed using spectra collected between 900-1700 nm from a single maize seed. In the study, 427 diploid and 311 haploid samples obtained by crossing 10 donor materials and 3 inducer lines and separated by eye according to the Navajo marker were used. Spectral measurements were conducted over the wavelength range of 900 to 1700 nm for each sample. The robust PCA (Principal Component Analysis) method was used to detect spectral outliers. Spectral data were treated with none, FD (First Derivative), SD (Second Derivative), SNV (Standard Normal Variate), and their binary combinations. Logistic Regression, Support Vector Machine with a linear kernel (SVM-C), Random Forest, and XGBoost methods were employed as machine learning techniques. The performance of the developed machine learning models was assessed using metrics such as Sensitivity, Specificity, Recall, F1-Score, and Accuracy. The Boosting method demonstrated the best performance with 94.9% accuracy, 95.1% sensitivity, 94% specificity, and an F1 Score of 96%, particularly when using raw reflectance data. These results obtained from raw data show that high accuracy can be achieved in classification models without requiring additional preprocessing steps. D2 preprocessing was found to be unsuitable for intact seed spectra, whereas SNV and D1 applications improved the classification success of other modeling techniques. The study revealed that the Boosting-Raw combination is a powerful and feasible method for classifying haploid and diploid samples.
Effects of Drip Irrigations with Different Irrigation Intervals and Levels on Nutritional Traits of Paddy Cultivars
(MDPI, 2025) Çiftci, Beyza; Kardeş, Yusuf Murat; Varol, İhsan Serkan; Taş, İsmail; Akçura, Sevim; Coşkun, Yalçın; Karaman, Kevser; Akçura, Mevlüt
Rice serves as the primary food source for the majority of the world's population. In terms of irrigation water, the highest volume of irrigation water is utilized in paddy irrigation. Excessive water use causes both waste of limited water resources and various environmental problems. The drip irrigation method with high water use efficiency will reduce both the need for irrigation water and the environmental footprint of paddy production. This study was conducted to investigate the effects of two different irrigation intervals (2 and 4 days) and four irrigation levels (150%, 125%, 100%, and 75% of evaporation from a Class-A pan) on the nutritional traits of three different paddy cultivars (Ronaldo, Baldo, and Osmanc & imath;k). Increasing irrigation intervals and decreasing irrigation levels reduced the nutritional properties (protein, oil, starch) of the rice grains. In addition, increasing irrigation levels also increased the phytic acid and dietary fiber contents. The highest protein (7.14%) and total starch (87.10%) contents were obtained from the 150% irrigation treatments. The highest amylose content (20.74%) was obtained from the 75% irrigation treatment. In general, it was found that irrigation levels should be applied at 125% and 150% to increase the mineral content of rice grains. Although water deficits decreased the nutritional properties of the paddy cultivars, drip irrigation at an appropriate level did not have any negative effects on nutritional traits.
A Study on the Integration of In Vitro Methods with In Vivo Double Haploid Technique in Maize (Zea mays L.)
(2024) Yüksel, Nur; Kahrıman, Fatih
The in vivo doubled haploid technique in maize breeding significantly reduces the time required for developing homozygous lines, offering advantages in terms of both time and cost. Although this technique enables the development of lines much faster than traditional breeding methods, ongoing research aims to further shorten the development process through alternative approaches. In this context, significant efforts have been devoted to integrating in vitro methods with in vivo doubled haploid technique. This study aimed to investigate the potential of combining in vivo and in vitro techniques for the rapid development of homozygous maize lines. A total of 10 local populations and 3 inducer lines (CIM2GTAIL-P2, ADAIL-1, STOCK-6) were used as experimental material. The study was conducted in two phases under field and laboratory conditions. During the first phase, induction crosses were performed in 2022, and the haploid induction rates of donor genotypes were found to range from 1.29% to 7.12%, as determined using the Navajo marker. In the laboratory phase, immature embryo culture was employed for both direct and indirect regeneration using samples collected 18–20 days after induction crossing. Haploid status of the samples obtained through direct regeneration was confirmed using the Feulgen chromosome staining method. Four of the donor materials (DON3, DON4, DON6, DON7) yielded successful results in tissue culture studies. Explants were taken from immature embryos to CHU medium for callus formation and then these calli were transferred to Murashige and Skoog medium for the formation of somatic embryos. This approach enabled the production of 3 to 6 calluses per immature embryo, depending on the donor genotype. The results of this study indicate that integrating immature embryo culture as an in vitro method into the in vivo doubled haploid technique can offer benefits in terms of both time efficiency and an increased number of developed materials.
Azotla gübrelemenin bazı ekmeklik buğday çeşitlerinin verimi ve kalitesine etkileri
(Ankara Üniversitesi Ziraat Fakültesi, 2008) Öztürk, İrfan; Gökkuş, Ahmet
Trakya’da ağırlıklı olarak buğday yetiştirildiği için her yıl değişik yollarla bölgeye farklı buğday çeşitleri girmektedir. Ekilen çeşit sayısının fazla olması ister istemez bazı sorunları (düşük verim ve kalite, hastalık, soğuk ve kurağa az dayanıklılık gibi) da beraberinde getirmektedir. Bu yüzden araştırmada yöreye en uygun çeşit ve azot dozunun belirlenmesi hedeflenmiştir. Deneme Trakya Tarımsal Araştırma Enstitüsü’nün deneme tarlasında 2003/2004 ve 2004/2005 yetiştirme yıllarında yürütülmüştür. Araştırma tesadüf bloklarında bölünmüş parseller deneme desenine göre 4 tekerrürlü olarak kurulmuştur. Ana parsellere çeşitler (Gelibolu, Pehlivan, Turan-2000, Kate A-1 ve Golia), alt parsellere azot dozları (0, 4, 8, 12 ve 16 kg/da) yerleştirilmiştir. Azotun 1/3’ü ekim öncesi, 1/3’ü kardeşlenme ve 1/3’ü sapa kalkma döneminde verilmiştir. Denemenin ilk yılında çeşitler ve azot dozları arasında önemli fark olmamıştır. İkinci yılda Kate A-1 ve Turan-2000 daha yüksek tane verimine (539.9±35.1 ve 537.0±39.8 kg/da) sahip olmuşlardır. Bu yılda verilen azotun artışı ile tane verimi de artarak en yüksek azot uygulamasından (16 kg/da) en yüksek verim (616.1±23.4 kg/da) alınmıştır. Azotla gübreleme unun kalite özelliklerini (glüten miktarı ve sedimantasyon değerini) yükseltmiştir. Bu etki çeşitlere ve yıllara göre 8-16 kg/da azot dozuna kadar sürmüştür. Genel olarak Golia ve Gelibolu çeşitlerinden elde edilen unun ekmeklik kalitesi diğer çeşitlerden biraz daha yüksek olmuştur. Tane verimi ve un kalitesi birlikte ele alındığında, yöre için Gelibolu çeşidi tavsiye edilebilir niteliktedir.
SelectWave: A graphical user interface for wavelength selection and spectral data analysis
(Elsevier B.V., 2021) Kahrıman, Fatih; Liland, Kristian Hovde
Studies on the determination of chemical compounds with different spectroscopy devices have become a hot topic in the scientific literature. A wide variety of programs are used to develop quantitative calibration models via different chemometric techniques in the scientific studies. However, there is a limited number of free and user-friendly software for creating quantitative determination models based on multivariate data analyses. In this study, we aimed to transform functions from R packages, which are widely used in spectral data analysis, into a free application accessible via the web. The application (SelectWave) has four sub-menus including data input, pre-analysis, post-analysis and about tabs. Data for dependent and independent variables should be loaded as calibration and validation sets separately. The pre-analysis tab includes four derivative functions and five pretreatment algorithms for spectral data analysis. Wavelength selection is possible with filter methods Variable Importance on Projections (VIP), Selectivity Ratio (SR), significance Multivariate Correlation (sMC) and minimum Redundancy Maximum Relevance (mRMR), and PLS based wrapper methods Interval Partial Least Squares (iPLS), Genetic Algorithm (GA), Iterative Predictor Weighing (IPW) and Uninformative Variable Elimination (UVE) under the post analysis tab. During the data modeling phase, the application provides Partial Least Squares Regression (PLSR) and Support Vector Machines (SVM) regression to the user. External validation can be performed using separate test set data. After the modeling process, evaluation statistics can be seen on the screen and automatically saved as a csv file under the user's working directory. The results of the variable selection can be inspected visually in the user interface. The developed application was tested on a personal computer (Intel Core i3, 4 GB RAM, ×64 processor, Microsoft Windows 10 Home) using spectral data from amylopectin analyses of maize flour samples (n = 200) and on a more powerful computer using various data sets. The application is aimed at researchers who want to develop a multivariate quantitative calibration model with data obtained from any spectral device.
Discrimination of water stress in pepper using thermography and leaf turgor pressure probe techniques
(Elsevier B.V., 2021) Çamoğlu, Gökhan; Demirel, Kürşad; Kahrıman, Fatih; Akçal, Arda; Nar, Hakan; Boran, Ahmet; Eroğlu, İlker; Genç, Levent
The use of technology is spreading rapidly in modern agriculture with remote sensing and sensor technologies becoming more important. The objective of this study is to investigate the possibilities of determining the water stress level and irrigation time in peppers using leaf pressure probes based on turgor pressure and thermography techniques. An experiment consisting of four different irrigation treatments (100%, 75%, 50% and 25%) was conducted in Canakkale province, Turkey in the 2017–2018 summer growing seasons. During this seasons, leaf turgor pressure (Pp) and soil moisture levels were recorded in real time by a remote monitoring system. Thermographic measurements were taken before each irrigation. Data were analyzed using the analysis of variance and regression tree methods. Results show that both Pp and thermal data significantly differed according to water stress. Pp values decreased partially after irrigation and increased until the next irrigation. However, it was observed that it is not enough to decide the irrigation time using results obtained from graphical readings only. Models including meteorological features strengthen the decision-making models. According to the classification and regression tree analysis, it was revealed that there is a potential to separate the treatments, especially in models including thermal indices. Leaf turgor pressure data and thermal indices, which are plant-based monitoring techniques, have the potential to be used in determining irrigation time and distinguishing water stress in the pepper plant. However, there is a need for more studies especially in laboratory conditions, to understand the mechanisms in plants and how environmental conditions affect the responses of Pp probes.
Plant-based monitoring techniques to detect yield and physiological responses in water-stressed pepper
(Elsevier B.V., 2024) Çamoğlu, Gökhan; Demirel, Kürşad; Kahrıman, Fatih; Akçal, Arda; Nar, Hakan
Today, the use of sensors and imaging techniques, which are used to obtain information about plants and soil in smart irrigation systems, is rapidly becoming widespread. This study aimed to investigate the usability of leaf turgor pressure and thermal images from plant-based monitoring techniques to detect water stress and the irrigation time of pepper (Capsicum annuum L. cv. “California Wonder”) and to determine their relationship with physiological traits in Canakkale/Türkiye in 2017 and 2018. The four irrigation treatments (100%, 75%, 50%, and 25%) were applied in the experiment. Leaf turgor pressure (Pp), thermal images and physiological measurements were carried out during the growing season. Soil moisture and Pp were monitored in real time by remote. Thermal and physiological measurements were made before each irrigation. As a result of the study, the average evapotranspiration (ETc) was 697 mm, and the yield value was 83.7 t ha−1 under non-stress conditions. Depending on the decrease in ETc, yield values also decreased significantly. Leaf water potential and stomatal conductivity values were statistically different in all irrigation treatments. The change in the activity of catalase (CAT) due to water stress was greater than that of superoxide dismutase (SOD). In this case, it can be said that other physiological traits are more successful than SOD in distinguishing water stress. According to the regression models, significant relationships were determined between both the indices calculated from the thermal images and Pp, yield, and physiological traits. The predictive ability of Pp values has been strengthened with the addition of meteorological properties to the model in general. The highest correlation (R2 =0.63) was between Pp + meteorological properties and CAT. All the regression models between physiological traits and indices calculated from thermal images were statistically significant. The highest R2 values were obtained in August. In this month, the highest correlations were between Crop Water Stress Index (CWSIp) and leaf water potential / stomatal conductivity (R2 =0.91), IGp and stomatal conductivity (R2 =0.80). The predictive power of CWSIp was higher than Stomatal Conductivity Index (IGp). The experiment illustrated that Pp and temperature data, which are plant-based monitoring methods, have the potential to detect water stress in peppers.
Effects of Irrigation Levels on Biochemical Traits of Popcorn Kernels
(Springer Science and Business Media Deutschland GmbH, 2023) Kaplan, Mahmut; Taş, İsmail; Ciftci, Beyza; Varol, İhsan Serkan; Akçura, Sevim
Popcorn, directly consumed as foodstuff, is among the most popular products. Biochemical quality traits of popcorn may exhibit significant variations based on growing conditions. Number of studies about the irrigation-dependent changes in biochemical traits of popcorn kernels is quite limited. This study was conducted to determine the effects of different irrigation levels (50%, 75%, 100% and 125% of depleted water from the field capacity) on protein characteristics (crude protein and pepsin protein digestibility), starch characteristics (total starch, resistant and non-resistant starch, amylose-amylopectin content), oil and fatty acids and mineral contents of popcorn kernels. Experimental results were assessed through variance and biplot analyses. Irrigation levels had highly significant effects on biochemical traits of popcorn kernels. Irrigations increased kernel protein and starch contents and decreased dietary fiber and amylose contents. Linoleic acid contents increased and oleic acid contents decreased with increasing irrigation levels. The greatest palmitic and stearic acid contents were obtained from I100 treatments. Na and Fe contents increased with increasing irrigation levels. The greatest Mg and Zn contents were obtained from I100 irrigation level and the greatest Ca content was obtained from I75 irrigation level. In present biplots generated for visual assessment of the changes in investigated traits with irrigation levels, oleic acid, amylopectin and dietary fiber contents were placed into the same sector with I50 treatment; Zn, stearic acid, palmitic acid and Mg contents were placed into the same sector with I100 treatment; the other traits were placed into the same sector with I125 treatment. Two principle components (PC1 and PC2) explained 96.55 of total variation indicating significance of investigated traits based on irrigation levels. It was concluded based on present findings that biochemical traits, fatty acid composition and mineral contents of popcorn kernels could be improved through the use of different irrigation levels and irrigation levels should be arranged based on soil conditions to improve quality traits of popcorn kernels.
Prediction performance of NIR calibration models developed with different chemometric techniques to predict oil content in a single kernel of maize
(Elsevier B.V., 2023) Gürbüz, Büşra; Aras, Erkan; Güz, Abdurrahman Muhammed; Kahrıman, Fatih
Determining the biochemical content of intact seeds without damaging them provides significant advantages in plant breeding programs. Determination of oil content is one of the most tedious analyses at single kernel level among biochemical analyses. Near infrared reflectance (NIR) spectroscopy is one of the methods that can be an alternative to biochemical analyses in order to determine the oil content at the single seed level without damaging the sample. The aim of this study was to develop calibration models that will enable the determination of oil content in a single maize kernel by means of NIR spectroscopy and to compare the predictive power of the models developed using different chemometric techniques. A total of 500 seeds from 10 different genotypes that differ from each other in terms of oil content (from 1.11% to 10.9%) were used as experimental material. Spectral data were collected between 8333 and 4166 cm−1 on a desktop NIR device. Prediction models were constructed using partial least squares regression (PLSR) and support vector machines (SVM) methods. The model development process was carried out in the SelectWave (https://bafr.shinyapps.io/SelectWave/) application and models (n = 360) were created to determine oil content at single seed level by using 5 different pretreatments, 4 different derivative options, and 9 different wavelength selection methods. Model robustness was evaluated for the calibration samples (n = 341), external validation samples (n = 98), and test samples (n = 50). The most successful prediction result was obtained from the SVM model with the pretreatment combination of None+SVM+None (RMSECal=0.46, R2Cal=95.11, RPDCal=4.53, RMSEVal=0.78, R2Val=84.50, RPDVal = 2.55, RMSETest=0.83, R2Test=82.59, RPDTest = 2.42). Results showed that oil content in single kernel of maize could be correctly predicted by NIR calibration models based on SVM method coupling with the pretreatment of None+SVM+None combination.
Annual changes in biomass amount and feeding potential of shrubby rangelands in maquis formation
(PeerJ Inc., 2023) Alatürk, Fırat; Gökkuş, Ahmet; Ali, Baboo; Hanoğlu Oral, Hülya
Background. This study evaluated the extent to which the endemic herbaceous and woody species of shrubby rangelands met the roughage needs of grazing animals throughout the year. Methods. The biomass, botanical composition, and quality of hay were investigated in the shrubby rangelands in Pa,sakoy of the Ayvacik districts in canakkale over the course of a year. Plant samples were taken from the herbaceous species monthly and from the grazing parts of the shrubs in May and November. Results. The total amount of biomass (hay + shrub) in the rangeland was found to be 30.448 kg/ha. Shrubs made up 18.78% of the rangeland, while the annual species comprised 54.96%, and perennial herbs covered 26.26% of the total biomass. Crude protein (CP) ratios of herbaceous species decreased continuously from March (13.58%) to September (6.73%), and then increased. A similar change was also seen in pure ash (PA) ratios. The CP ratios in the shrub species were high in spring and decreased in autumn and there was an irregular variation in PA rates. Oak had the highest PA ratio during the spring, while thuja had the highest ratio in autumn, and Juniperus oxycedrus during the winter months. In herbaceous species, cell wall components (NDF, ADF, and ADL) reached their highest levels in summer and decreased in spring and winter. However, in shrubs, these components varied according to the species and were generally lowest in spring and then increased in autumn and winter. Here, it was determined that year-round grazing is a suitable grazing system in the shrubby rangelands of the Mediterranean zone, and animals are able to find fresh forage in the rangelands due to the presence of shrubs. However, since the contribution of shrubs to the total forage production is low, additional roughage should be provided, except in the spring when the production and quality of hay increase. These practices may contribute to better livestock management.
Changes in the essential oil content and composition of pelargonium graveolens l'her with different drying methods
(CSIC Consejo Superior de Investigaciones Cientificas, 2023) Akçura, Sevim; Çakmakcı, Ramazan; Ürüşan, Zeynep
In this study, the effect of various drying methods (fresh plant, shade-drying, sun-drying, and oven-drying at 30 and 60 °C) on the essential oil (EO) composition of rose-scented geranium were determined. Essential oil samples were extracted by hydrodistillation and analyzed byGC and GC-MS systems. The highest EO contents were obtained in the fresh plant (1.98%). followed by shade-drying (1.34 %) and oven-drying at 30 °C (1.20 %). The main components were citronellol (23.99-39.87%). gcraniol (4.15-17.09%). mcnthonc (4.48-8.34%). linalool (1.96-7.42%), P-caryophyllene (2.63-4.32%), geranyl tiglate (0.99-4.52%), citronellyl butyrate (0.53-5.31%) and cis-rose oxide (0.71-3.15%). The diying methods showed a marked impact on the constituents of the EO samples. The results demonstrat¬ed that drying the aerial parts of fresh geranium, and shade-drying and oven-drying at 30 CC were the best optimal methods to obtain the highest oil yield, and citronellol. geraniol, and linalool contents in the oil.
Assessment and Principles of Environmentally Sustainable Food and Agriculture Systems
(MDPI, 2023) Çakmakçı, Ramazan; Salık, Mehmet Ali; Çakmakçı, Songül
Feeding the world depends on protecting our valuable ecosystems and biodiversity. Currently, increasing public awareness of the problems posed by the current industrialized food system has resulted in increased support for the creative market for economically, socially, and ecologically sustainable food production systems and enhanced demands for variations in agricultural policies and regulations. In food production, the restoration and protection of ecosystems and sustainable food systems must be given priority, which requires a forward-looking rational management strategy and fundamental changes in patterns and practices of economic development, product, and production. Food systems should be redesigned to have a neutral and positive environmental impact, as well as ensure healthy nutrition and food safety, and low environmental impact strategies should become a priority. This review paper aims to discuss, build, guide and evaluate sustainable food systems, principles, and transition strategies such as agroecological, organic, biodynamic, regenerative, urban, and precision agriculture, which are imperative visions for the management of agriculture and food production. To this end, we analyzed the evolution of the established strategies to develop sustainable agriculture and food systems, and we created assessment of key sustainability issues related to food, environment, climate, and rural development priorities and resource use practices.
Quality and Nutritional Parameters of Food in Agri-Food Production Systems
(MDPI, 2023) Çakmakcı, Songül; Çakmakçı, Ramazan
Organic farming is a production system that avoids or largely excludes the use of synthetic agricultural inputs such as pesticides, growth regulators, highly soluble mineral fertilisers, supplements, preservatives, flavouring, aromatic substances and genetically modified organisms, and their products. This system aims to maintain and increase soil fertility and quality, and relies on systems such as crop rotation, polyculture, intercropping, ecosystem management, covering crops, legumes, organic and bio-fertilisers, mechanical cultivation and biological control methods. The present review summarises and evaluates research comparing the quality of traditionally, organically and conventionally produced foods. In some cases, although the results of the studies contradict each other, organically grown in vegetables, especially berries and fruits are slightly higher dry matter, minerals such as P, Ca, Mg, Fe and Zn, vitamin C, sugars, carotenoids, antioxidant activity, phenolic and flavonoid compounds. In addition, their sensory properties are more pleasant. The nutritional content, quality and safety of organic foods are acceptable if the recent trends are reviewed, tested and verified. Therefore, the aim of this review is to compile, describe and update scientific evidence and data on the quality, safety, bioactive compounds and nutritional and phytochemical quality of foods in traditional and organic fruit, vegetable and cereal production systems.
Ranking Districts of canakkale in Terms of Rangeland Quality by Fuzzy MCDM Methods
(Springer, 2023) Gökkuş, Zeynep; Şentürk, Sevil; Alatürk, Fırat
Due diligence of rangelands, which are among the renewable energy sources, is very important for improvement projects. In this study, it is proposed to use fuzzy multi-criteria decision-making (MCDM) methods as a supportive statistical approach in examining rangeland conditions. Among these methods, fuzzy AHP, TOPSIS and VIKOR are explained. Vegetation data of a rangeland condition determination project were examined by these methods. According to the results, the fuzzy MCDM methods provide effective support in determining the rangeland conditions numerically. For this reason, it is recommended to be used in similar studies.
Effects of irrigation intervals and irrigation levels on oil content and fatty acid composition of peanut cultivars
(AcademicPres, 2021) Akçura, Sevim; Taş, İsmail; Kökten, Kağan; Kaplan, Mahmut; Bengü, Aydin S.
Oil content and fatty acid composition are the most significant quality criteria of peanuts (Arachis hypogaea L.), and these parameters is greatly influenced by irrigation and fertilization practices. A study was conducted to investigate the effects of irrigation intervals and irrigation levels on oil content and fatty acid composition of peanuts, under sandy soil conditions in two consecutive years, using ‘Halisbey’, ‘NC-7’, and ‘Sultan’ peanut cultivars, commonly grown in Turkey. Irrigation levels were arranged based on total evaporation from Class-A pan, and irrigations were applied through drip lines. Irrigation intervals were set as two and four days, and irrigation levels were set as 50% (I50), 75% (I75), 100% (I100) and 125% (I125) of Class-A pan evaporations. Oil content, unsaturated fatty acids (oleic and linoleic acids), and saturated fatty acids (palmitic, myristic, arachidic, behenic and lignoceric acids) were determined. For oil content, treatments were identified as the most appropriate irrigation for a two-day irrigation interval of all cultivars, I100 for four-day irrigation interval of ‘Halisbey’ and ‘Sultan’ cultivars and I75 for four-day irrigation interval of ‘NC-7’ cultivar. Oleic, linoleic, and palmitic acids were the major fatty acids of peanuts. Cultivars exhibited different variations in these fatty acids based on irrigation intervals and irrigation levels. In general, oleic acid contents decreased, but linoleic and palmitic acid contents increased with increasing irrigation levels. The greatest oleic acid contents were obtained from two and four-day irrigation intervals of I50 treatments in ‘Halisbey’ and ‘NC-7’ cultivars and from two and four-day irrigation intervals of I75 treatments of the second year in ‘Sultan’ cultivar. Present findings revealed that for quality peanut production, both irrigation intervals and irrigation levels should be taken into consideration.
Chemical Composition of Essential Oils of Peppermint and Spearmint Dry Leaves and Their Allelopathic Effects on Wheat Species
(Har Krishan Bhalla and Sons, 2021) Turgut, Tanju; Coskun, Yalçin
This study was carried out to determine the chemical composition of essential oils of the spearmint and the peppermint dry leaves and their allelopathic effects on seed germination and seedling growth of different wheat species. The ratios of essential oil isolated by hydrodistillation were found to be 2.5 % and 2.0 % (w/w), respectively. The GC/MS analysis revealed that the peppermint essential oil contained 20 compounds, while spearmint essential oil incorporated 17 compounds. The main components in the spearmint essential oil were identified to be carvone (62.9 %) and limonene (8.2 %), while those of the peppermint essential oil was to be menthone (34.5 %) and menthol (41.4 %). The seed germination started to be negatively affected by 0.2 mu L of essential oil and the negative effect increased in parallel with the increase in essential oil dose. The reducing effect of the mint essential oils on seed germination was the lowest for Triticum spelta and the highest for T. aestivum. In the pot trial, the negative effect began to appear with 0.8 mu L of essential oil and increased with the higher doses. The effect of mint essential oils on root lengths and dry weights of single seedlings was the lowest for T. spelta and the highest for T. dicoccum. The estimated field application dose of the peppermint essential oil for the investigated wheat species was determined to be approximately 208 mL da(-1).
Ability of near infrared spectroscopy and chemometrics to measure the phytic acid content in maize flour
(Taylor and Francis Ltd., 2021) Şerment, Mehmet; Kahrıman, Fatih
Phytic acid is one of the important biochemical components in maize as in many plant species. Near infrared spectroscopy has a potential for determination of the phytic acid content in the maize grain. However, there are a limited number of studies on the determination of phytic acid in maize. Also, the effect of chemometric methods on the success of near infrared spectroscopy calibration models for phytic acid content has not been investigated sufficiently yet. To fill these gaps, we create a total of 360 different prediction models and evaluate the effect of chemometric methods on prediction robustness. To develop calibration models, 4 derivatives, 5 pretreatments, 9 wavelength selection methods were used, and partial least squares regression and support vector machines regression methods were applied. Model reliability was evaluated by external validation. Results revealed that spectral pretreatment and wavelength selection methods improve model prediction results. In general, support vector machines yielded more successful results than partial least squares models in detecting phytic acid. The best model was the combination of first derivative + standard normal variate + interval partial least squares combined with support vector regression. While creating calibration models for phytic acid detection, it was concluded that the use of appropriate chemometric methods increases the success of the model.
Classification of viable/non-viable seeds of specialty maize genotypes using spectral and image data plus morphological features
(Taylor and Francis Ltd., 2022) Yaman, Fatih; Kahrıman, Fatih
Seed viability is an important consideration for agricultural production. The number of studies on the measurement of seed viability in specialty maize genotypes via new approaches is limited. This study was carried out to determine the viability of the seeds (n = 950) of two specialty maize (high oil and high protein) populations using spectral measurements and imaging techniques. Spectral data from the seed embryos were collected between 1200 and 2400 nm. Image data were taken with 300 dpi resolution. From the collected images, red (R), green (G) and blue (B) [RGB] data were extracted, and morphological features (M) were also determined. Then, the seed samples were separated into two sets and the viability of the samples was determined using two different methods [standard germination (SG) test and triphenyl tetrazolium chloride (TTC) test]. Support Vector Machine (SVM), Random Forest (RF), and Classification and Regression Tree (CART) methods were used to develop the classification models (n = 36). Classification accuracy of the models was comparable for the SG test (0.56–0.91) and TTC test (0.53–0.85). However, the classification models based on TTC test results had higher sensitivity (0.86–0.99) than specificity values (0.07–0.74), which indicated that the viable seeds were more accurately identified than the non-viable seeds. The RF model, created using the NIR+M dataset, based on the SG test (sensitivity = 0.89, specificity = 0.94, accuracy = 0.91), was most effective for determination of the seed viability of specialty maize genotypes used in this study.

Güncel Gönderiler