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In this work, a simulation of the climate change impact on the wheat grain storage process in Northwestern regions of Tunisia was investigated based on grain aeration systems. This simulation was conducted by implementing the software package called Zephyrus for a period from 2041 to 2070 during storage season from the 01st of July to the 30th of November. The model estimates grain moisture content, grain temperature, and dry matter loss. The results showed a significant potential of the Zypherus strategy to maintain the grain moisture content around 12.2± 0.2% w.b. and to reduce grain temperatures from 35°C to 24 ± 1.5°C inside the silo. Consequently, under these values, the wheat storage process is considered safe and preserves wheat quality during the simulated storage period. Moreover, the wheat dry loss matter was about 0.8% during the whole storage period for each simulated year (approximately 0.15% per month).

Colorimetry is of paramount importance to the agricultural industry. Colorimetry refers to the processing of agricultural products for consumer needs from a marketing point of view, and therefore the agricultural industry spends a lot of money and time classifying each product. In the past, agricultural professionals had to use program codes that are difficult to learn, and even the most basic image analysis for agricultural product classification required mastering different program libraries. Today, the LabVIEW platform offers a flexible, fast, easy-to-learn, and complete image analysis infrastructure with various useful modules. For this reason, in this study, a method analysis for color perception with a simple USB webcam and software developed for real-time color analysis on the LabVIEW platform is presented and its success in the basic color analysis is tried to be revealed. The basic application developed for this purpose in LabVIEW v2019 using NI Vision Development Module v19 and NI IMAQ v19 modules. The basic fact that is the LabVIEW application is the idea that LabVIEW can only be analyzed with expensive IEEE 1394, but it should be known that these analyzes can be done with USB webcams. For this purpose, the application includes a USB webcam driver that can be stacked seamlessly. USB Webcam and colorimeter measurement-based results of ƔR factors for each of RGB color channels are 1.161232, 0.506287, 0.432229; ƔG factors for each of RGB color channels are 0.519619, 1.025383, 1.201444; at last ƔB factors for each of RGB color channels are 0.600362, 0.714016, 1.413406, respectively.

This research is aimed to explore the efficacy and comparison of low-cost light sensor measurements for agricultural applications. For this reason, TSL2561, BH1750, and TEMT6000, low-cost light sensors have been used with various lighting regimes. Consequently, their efficiency has been tested for agricultural applications. These types of low-cost light sensors can be used in a range of applications in agriculture. For this reason, it is necessary to evaluate the calculation of light sources. The light calculation values of low-cost light sensors were statistically compared. Calibration results were also analyzed, so the reliability of low-cost light sensors was detected. Statistical analyses of light values have been presented in the results and discussion part of the paper as; the regression coefficient based on UNI-T UT382 vs. TSL2561 for the calibration was found as R-Sq 99,6%, R-Sq(adj) 99,5%, and S 10,18; for the calibration of UNI-T UT382 vs. BH1750 was found as R-Sq 100%, R-Sq(adj) 100% and S 2,73; at last for the calibration of UNI-T UT382 vs. TEMT6000 was found as R-Sq 99,2%, R-Sq(adj) 99,1% and S 14,71. After calibration, the regression coefficient based on UNI-T UT382 vs. TSL2561 for the light measurement was found as R-Sq 100%, R-Sq(adj) 100%, and S 2,21; the light measurement for UNI-T UT382 vs. BH1750 was found as R-Sq 100%, R-Sq(adj) 100% and S 1,09; also for the UNI-T UT382 vs. TEMT6000 was found as R-Sq 100%, R-Sq(adj) 100% and S 1,73. According to calibration and measurement results, the BH1750 sensor is better than the others.

Olive tree is an important portion of the human history of Mediterranean nations. On the other hand, local varieties are important for each producer regions and even countries. So, olive cultivars are important for agricultural production for these people. The traditional pomological identifiers of the olive trees based on fruits and leaves, also morphometric analysis of size, additionally shape elliptic analysis of endocarp. Because of this reason, in this study, for the ‘Picual’ olive cultivar identification, a fast and easy method was presented. For this aim, ‘Picual’ olive leaf, fruit, and stone dimension measurement values obtained from real-time video images. ‘Picual’ olive fruit, stone, leaf samples evaluated by using real-time computer vision measurements. Regression analysis was applied to the data which was obtained from real-time video and caliper measurements. According to the regression coefficient results, the regression between caliper length measurement (OLLM) and computer vision video length measurement (OLLCV) found as 98.9%, also the regression between caliper width measurement (OLWM) and computer vision video width measurement (OLWCV) found as 97.9% at ‘Picual’ leaves, additionally, the regression between caliper length measurement (OFLM) and computer vision video length measurement (OFLCV) found as 98.5% the regression between caliper width measurement (OFWM) and computer vision video width measurement (OFWCV) found as 98.1 % at ‘Picual’ fruits, at last, the regression between caliper length measurement (OSLM) and computer vision video length measurement (OSLCV) found as 86.2%, the regression between caliper width measurement (OSWM) and computer vision video width measurement (OSWCV) found as 75.3% at ‘Picual’ stones.

Background: The study was conducted at the various locations in Antalya province, where the Tavşan Yüreği olive variety is registered as the Tavşan Yüreği olive variety, which is spreading especially in Kepez and Manavgat districts. Methods: The objective of this study was to determine a homonym of Olea europaea var. Tavşan Yüreği by using molecular identification and image analysis. Based on molecular analyses and morphological measurements made on collected leaf and fruit samples collected, the morphological identification method is used based on imaging techniques from high-resolution photos. Result: The results showed that, according to the molecular definition and image analysis measurements, the source of the difference between all locations, including the BATEM sample, may be genotype or phenotypic diversity within the variety.

Colour is an essential parameter at product quality control stages, and finally, it is necessary for the consumer marketing decision. It is possible to damage the products during the process from collection to storage. Also, it is a well-known condition, cold environmental conditions protect fruits from deformations negative effects, but most of the time, most of the consumers keep the fruits at room temperature in open packs during the consumption process. Also, this condition affects the product storage time. In this study, it is aimed that to determine the behaviours of the fruits in room temperature and humidity conditions. For this aim the colour change of the damaged pears were determined, in another term, colour change value from red to green and yellow to blue at the damaged pears were determined with lightness values by using image analysis technique and analysed with data mining methods. For this purpose, 100 “Akça” pear and 100 “Deveci” local pear cultivar used for experiments. Fruits were equally damaged by using a pendulum mechanism. The damaged fruits were kept at room temperature. Colour change areas on fruits were evaluated with X-rite Ci60 spectrophotometer, and the hardness of fruits was measured by using a fruit penetrometer. The colour (L, a, b) and ΔE values were analysed for the fruit cultivars. The relationship between fruit hardness and colour change were also demonstrated. The predictions were done supervised machine learning algorithms (Decision Tree and Neural Networks with Meta-Learning Techniques; Majority Voting and Random Forest) by using KNIME Analytics software. The classifier performance (accuracy, error, F-Measure, Cohen's Kappa, recall, precision, true positive (TP), false positive (FP), true negative (TN), false negative (FN) values were given at the conclusion section of the research. The best prediction were found at the Majority Voting method (MAVL) 98.458 % success given with 70% partitioning.

Liquid chemical fertilizers are widely used in modern agriculture. The pH values of these fertilizers are important in terms of their effectiveness in the field application and their effect on the soil-water pH balance. Therefore, it is necessary to measure the pH and other properties of liquid fertilizers with fast, practical and inexpensive methods. With the advancing technology, pH value has been started to measure more accurately and efficiently with the help of low-cost devices. In this study, a low-cost pH meter was developed using a low-cost pH sensor, an Arduino UNO R3 microcontroller board, and a software written in the C/C++ programming language. The developed pH meter was used to measure the pH values of liquid chemical fertilizers. Close variations were observed between the values obtained from it and the values measured by an accredited, laboratory-type pH meter. According to the pH measurements of the two pH meters, R2 ranged 88.1% to 99.3%, average error range 0.14 to 0.28, and average error percentage ranged 1.56% to 6.81% for three different types of liquid fertilizers. In light of these results, it was shown that the developed low-cost pH meter can be useful for practical pH measurement applications.

The insecticidal effect of natural basalt powder on Tribolium castaneum was evaluated. Two tests were used to study the insecticidal action of the basalt powder on the stored durum wheat. The coating test followed by the Bioassay test. The coating test of Tribolium castaneum adults in 10g of natural basalt powder, for 17 samples at rate of 25 adults per sample and an uncoated control, showed an insecticidal effect of the said powder with mortality rate of 100% for 70 hours of exposure against 5% for the control sample with a homogeneity of the mortality rate for the 17 samples. The bioassay test was carried out on durum wheat, the natural basalt powder was applied as dust at six different doses. The results of showed an insecticidal efficacy closely related to the dose and the time of exposure. The 500ppm dose showed insecticidal potential after 12 days of exposure against Tribolium castaneum (100% mortality). However, the 300ppm dose showed significant efficacy (100% mortality) against Tribolium castaneum after 14 days of exposure. In addition, the doses over than or equal to 75ppm resulted in a significant reduction in the insect population (mortality more than 74% for 14 days of exposure) compared to the control, providing new approach of integrated pest management strategy.

Olive fly (Bactrocera oleae Rossi) is a parasite that infects olive fruit by stinging the fruit to deposit its eggs. The infection damages the fruit during its growth and affects the quality of the olive oil as a final product. Detection of olive fly stings in the virgin olive oil production process is therefore critical. This research aimed to develop automatic methodologies based on computer vision to detect fly stings in infected olive fruit samples. Different methodologies to detect defective areas on the surface of the fruit and classify them between stings and other bruises are described. The methodology to detect defective areas reached a success ratio of 93% and best classification algorithms reached a success ratio close to 80%. The proposed methodology could be applied at reception of fruit for input of the virgin olive oil production process.

Background: Agricultural product classification is an essential and widely working issue in the agriculture industry. There is a lot of work to be done in this area and the agriculture industry is looking for new applications. The reason is that the software and hardware Technologies are always developing, and the latest technologies giving better results parallel to these developments. Also, the costs of the new technologies are decreasing with the help of low-cost sensor and device technologies. New technique and technology usage also directly related to classification efficiency. The primary data on agriculture are agricultural products, so these technologies and techniques use for agricultural production. Methods: The primary data on agriculture are agricultural products, because of this reason, this research aimed to make ultrasonic sensor measurements with the help of a software which is developed in LabVIEW platform for potato classifications and showing the efficiency of the method for the potato classification, which has different sizes. Result: According to the regression coefficient results, the regression between caliper length measurement (CL) and static ultrasonic sensor length measurement (SUL) found as 95.5%, the regression between caliper length measurement (CL) and dynamic ultrasonic sensor length measurement (DUL) found as 86.9%, the regression between static ultrasonic sensor length measurement (SUL) and dynamic ultrasonic sensor length measurement (DUL) found as 87.9% for potato classification.

A one-dimensional mathematical model based on the formulation of mass and energy balance in stored grain was used to simulate grains storage conditions. The objective of such simulations was to produce grain ventilation strategies. The model was validated using data obtained from the monitoring of wheat stored in a galvanized steel cylindrical tank with corrugated conical bottom ventilated by perforated distribution pipes. A control strategy based on night time aeration from July to November followed by day time aeration for December to January was applied. Good agreement between the predicted and measured storage conditions has been observed (R2= 0.9698, S.E.= 1.479 °C in average temperature and R2= 0.99, S.E.= 0.00079 kg kg-1for moisture content). Night time grain aeration provided sufficient cooling (temperature near 10 °C in November). However, an 18% grain humidification process was induced. Day time aeration started at the end of November corrected this humidification effect for a grain temperature of 15 °C and a grain moisture content of 15% on dry basis.

The identification of olive cultivars is of utmost importance for a multitude of factors affecting both, the olive oil elaboration process and fair trade exchanges. The accurate varietal identification is a time consuming task that requires trained specialists or expensive and specific equipment. When applying the traditional method, a specialist assesses morphological features using the olive endocarp. A proposal to automate this identification method is presented in this paper. Endocarp images, acquired under three different perspectives, are processed to extract the same information that the specialist utilizes. Then, the partial least squares discriminant analysis classifier, with or without feature selection, has been tested on a set of 250 samples from 5 different varieties. Results show that the proposal is an alternative identification method which could also be used in the traditional one in order to assist the specialist in the determination of the variety.

The purpose of the survey was to determine oxidation area and skin color change at the damaged apples by using Arduino based Force Resistive Sensor (FRS) and image analysis techniques. Mondial Gala, Mitch Gala, Jonagold local apple varieties were tested with FRS supported harvest glove which was prepared for the impact measurement. FRS glove used for determination of impact force while harvesting of apples. After the impact test, oxidation areas of each sample was evaluated by using a webcam and Labview platform. The oxidation areas were precisely measured by using LabView software after all these procedures. The effects of the impact tests indicated that response to impact bruising is dependent on flesh firmness and the impact force as well as apple variety.

Bu arastirmanin amaci; bugdayin yuzey artiklariyla kapli tarla kosulunda cetvel yontemi, kesisen hat yontemi, ImageJ goruntu isleme programi ve Labview Vision Assistant Moduluyle yuzey artigi kaplama yuzdesinin belirlenmesi ve elde edilen sonuclarin karsilastirilmasidir. ImageJ goruntu isleme programi ve Labview Vision Assistant Moduluyle yuzey artigi kaplama yuzdesinin belirlenmesi icin, bugday yuzey artiklariyla kapli bir tarlanin cesitli yerlerinden akilli cep telefonunun dijital kamerasiyla fotograflar cekilmistir. Arastirma sonunda; cetvel, kesisen hat, ImageJ goruntu isleme programi ve Labview Vision Assistant Modulu kullanilarak ortalama bitki yuzey artigi kaplama yuzdeleri sirasiyla % 44.13, % 50.72, % 56.56 ve % 64.49 olarak belirlenmistir. Yapilan varyans analizi; kesisen hat ve ImageJ goruntu isleme yontemlerinden bulunan sonuclar arasindaki farkliligin istatistiksel olarak onemsiz, bu yontemlerle diger yontemlerden elde edilen sonuclar arasindaki farkliliklarin ise onemli oldugunu gostermistir.

The aim of this research was to identify some Spanish olive cultivars using image processing techniques. For this purpose, Lechin De Granada, Arbequina, Picual, Verdial De V-M, Picudo, Hojiblanca and Empeltre Olive cultivars were identified utilizing the image processing and analysis techniques. Therefore, images of olives taken as 300 dpi with the 2896 × 1944 pixels, were captured using a DSLR camera, and evaluations of pixels were used for considering the pixel distribution and dimension measurements. LabVIEW Vision Assistant v2013 (NI) and Image j (NIH) software were used for image analysis procedures. Artificial Neural Network analysis were used to assess information of the length, width and color data results obtained from the fruits and stones (olive stones). All cultivars were identified. In addition, different classification techniques were applied to the olive stone and fruit data with the help of SPSS v22. Clementine v12 was used as a data mining software package from SPSS. The cultivars were identified 90% from dimensions with Artificial Neural Networks.

AAuger drilling, which is a digging method that a large helical drilling part gets out the soil from the earth. Different types of auger drillers are available today, and they are widely used in agricultural works. In this study, an 300 mm diameter auger drill was modeled, for agricultural works, and it was analyzed efficiently in Autodesk Inventor software with the help of Nastran in computer-aided design (CAD) module. According to the analysis, Von Misses stress analysis result was found as maximum 2266 MPa and minimum 0 MPa. Also, Safety Factor analysis result was found as maximum 15 uL and minimum 0.11 uL.

WOS: 000458550500008 In this study, Good Agricultural Practices for mandarin production and their effects on the efficient energy use and environmental were examined. This paper presents the results of asurvey conducted in the Adana province between January and February 2017. Data used in this study were obtained from 87farmers and consultant engineers who practice good agriculture in mandarin production using aface-to-face interview method. In this research, the total energy requirement for the mandarin production was 4686.46 MJkg(-1). The energy use efficiency indicator, efficiency and specific energy values were 1.92, 0.52 kgMJ(-1) and 0.92 MJkg(-1) respectively. As aresult of the research, renewable energy ratio was determined as 7.79%, and non-renewable energy ratio was determined as 86.17% in the total energy input. When the effects of the survey are compared with those of the literature, it shows that good farming practices in Turkey affect energy efficiency and environmental expectations in production positively, albeit at adepressed point.

As a country in an olive production zone, olive (Olea europaea L.) production is of great economic importance for Turkey. Turkey has 88 domestic and 28 foreign cultivars of olive, all of which are located in the Kemalpaşa Production and Research Garden (Olive Gene Bank) at the Olive Research Station in İzmir (38°25'34.7628''N, 27°25'22.9872''E). The aim of this study was the identification of olive cultivars using image processing techniques. For this aim, images of olives, taken at 2896 x 1944 pixel and 300 dpi resolution, were captured using a DSLR camera, and evaluations of pixels were used for considering the pixel distribution and dimension measurements. For this aim, MATLAB v2012 and Image j software were used. In the light of the obtained data, analysis of variance and Duncan?s test were used to characterize the olive cultivars. As a result, all observed olive cultivars were identified at P < 0.05 significance level. Sarı ulak, Gemlik, Edincik su, Memecik, Eşek zeytini, Ayvalık, Kilis yağlık, Uslu, Çilli, and Domat olive cultivars were identified utilizing the validation process employing image processing and analysis techniques. Only the Erkence cultivar was not identified. Moreover, different classification techniques were applied to the olive stone color value data by the help of SPSS v22 and Clementine v12, which is a data mining software package from SPSS. In addition to the first results the Erkence cultivar was identified 69% with artificial neural networks.

AfetRiski Altındaki Alanların Dönüştürülmesi Hakkında Kanun kapsamında Bursaİli’nde riskli yapı tespiti yapılan rastgele seçilmiş 500 adet betonarme binadanelde edilen karot sonuçları bu çalışmaya konu edilmektedir. Bursa İli mevcut yapıstoğunun önemli sayıda örnekle değerlendirmenin yanında, kentsel dönüşüm mantığıaçısından dönüşüme tabi tutulan yapılara ait beton basınç dayanım değerleriirdelenmiştir. Söz konusu irdeleme sırasında ülkemizde önemli metropollerdenbiri olan Bursa için sonuçlar ilçelere göre de irdelenmektedir. Bununla beraberbinaların yapım yıllarına ve o yıllarda yürürlükteki yönetmelik standartlarına göresahip olduğu beton basınç dayanım değeri ile günümüz standartları ile sonuçlarınuyumu ve binaların projesinin olup olmaması durumları için de irdelemeleryapılmaktadır. Sonuç olarak riskli yapı tespiti yapılan binaların beton basınç dayanımdeğerleri incelenmiş olup, çalışmada Bursa İli mevcut yapı stoğunun betonkalitesinin çok düşük olduğu ve mühendislik hizmeti almış olmalarının kaliteyebelirgin şekilde katkı sağlamadığı sonuçlarına varılmıştır., The results of core obtained from the randomly selected 500 reinforced concrete buildings in Bursa Province under the law known as the “Urban Renewal Law For Risk Mitigation” are the subject of this study. In addition to the evaluation of the existing building stock of Bursa Province with a great number of examples, the concrete compressive strength values of the structures subject to renewal in terms of urban renewal or transformation logic were examined. The results for Bursa, which is one of the important metropolitans in our country, are examined a according to districts. In addition to this, the concrete compressive strength value of the buildings according to the year of construction and the regulations standards in force in those years and the harmony of the results with the current standards and the fact that the buildings were constructed without taking the project or engineering services are also being examined. As a result, the concrete compressive strength values of the buildings at risk were investigated. In this study was concluded that the concrete quality of the existing building stock in Bursa Province is very low and engineering services are not significantly contributing to quality.

It is necessary to carry out various movements to understand the functions of agricultural machines. These movements are usually taken from the tractor shaft, the hydraulic control system or the wheel. Various mechanisms are used to ensure movement and to make agricultural machinery work. With these mechanisms, the direction and the number of movements can be changed. One of these mechanisms is crank-rod mechanisms and these mechanisms turn various actions into a complex movement. Consequently, the crank-rod mechanism of the tractor motor can be analyzed with limb mechanisms. In this study, the crank-rod mechanism of a tractor motor was dimensioned in different lengths and subjected to the kinematic analysis of MSC ADAMS software. The kinematic analysis of a single crank-rod mechanism for the engine gives important information about the tractor engine. Kinematic evaluation parameters of these mechanisms can be listed as displacement, velocity, and acceleration. These values related to the crank-rod mechanism of the tractor engine are evaluated and presented in the results and discussion section of the research for a better understanding of the kinematic characteristics of the crankrod motion., Tarımsal makinalarının işlevlerini anlamak için çeşitli hareketlerin incelenmesi gerekmektedir. Bu hareketler genellikle traktör şaftından, hidrolik kontrol sisteminden veya tekerden alınır. Hareketlerin sağlanması ve tarım makinalarında çalışmalarının yapılması için çeşitli mekanizmalar kullanılmaktadır. Bu mekanizmalarla, hareketlerin yönü ve sayısı değiştirilebilir. Bu mekanizmalardan biri krank-biyel mekanizmasıdır ve bu mekanizmalar çeşitli hareketleri karmaşık bir harekete dönüştürür. Sonuç olarak, traktör motorunun krank-biyel mekanizması uzuv mekanizmaları ile analiz edilebilir. Bu çalışmada, bir traktör motorunun krank-biyel mekanizması, farklı uzunluklarda boyutlandırılmıştır ve MSC ADAMS yazılımının kinematik analizine tabi tutulmuştur. Motor için tek bir krank-biyel mekanizmasının kinematik analizi, traktör motoru hakkında önemli bilgiler verir. Bu mekanizmaların kinematik değerlendirme parametreleri yer değiştirme, hız ve ivme olarak sıralanabilir. Traktör motorunun krank-biyel mekanizmasına ilişkin bu değerler ve krank-biyel hareketinin kinematik özelliklerinin daha iyi anlaşılması için değerlendirilmiş araştırmanın tartışma ve sonuçlar bölümünde sunulmuştur.

In the sense of safety, searching solutions for the problems of farmers may face during their work in the field of agriculture is important. For this reason, in this research, developments in sensor technology and price declines are also considering, a safety tracking system with an audible warning support developed for any threshold value that selected during a posture angle measure of agricultural work. To achieve this goal the low cost, 11.25 cm long flex sensor is used with Arduino UNO R3 Development Board. In this way, human motion information for different purposes determined with flex sensors which placed on the various joints as a biometric application. Posture measurement also evaluated with image analysis technique. The system performance revealed the relationship between flex sensor and image analysis measurements, the regression coefficient between the angle change and the voltage output of the flex sensor found as 88.9 %, also it is seen that the regression relation between the angle change and the voltage output of the flex sensor fort he arm angle measurement is 80.7 % and the regression value for the leg angle measurement is 79.9 %.

In this study, biogas production efficiencies of mixtures obtained by adding corn silage (CS) to citrus industrial wastes at different ratios were determined. Orange (OJPW) and tangerine processing juice wastes (TJPW) (crusts and shells) were selected as materials in the study. 25%, 50%, 75% of CS was added to these selected wastes. Changes in the obtained mixture chemical properties (dry matter, dry organic matter, crude ash, crude protein, crude oil, Acid Detergent Fiber (ADF), Neutral Detergent Fiber (NDF)), biogas production and methane content in the biogas were investigated. The results of the study showed that the highest crude protein content was found in 100% TJPW (10%), raw fat percentage in 100% TJPW (5.14%), dry matter content in 100% CS (93.56%), ADF in 100% CS (22.74%) and the NDF in a mixture of 25% OJPW + 75% CS (45.08%). The highest methane production was determined for a mixture of 100% TJPW and 50% TJPW + 50% OJPW (0.46 m 3 kg -1 ODM). Also the highest biogas production was determined in a mixture of 50% OJPW + 50% TJPW (0.90 m 3 kg -1 ODM). The mixing of CS in TJPW and OJPW reduced significantly the production of methane and biogas in the mixture. As a result of the statistical analysis, significant differences (P?0.05) were found in both methane and biogas production of agricultural wastes. © Ankara Üniversitesi Ziraat Fakültesi. Çukurova Üniversitesi: FBA-2017-7962 The analysis and experimental results of the materials discussed in this study were taken from the project supported by Çukurova University, Scientific Research Projects Management Unit (Project No: FBA-2017-7962). We thank them for their support.

This study aims to evaluate the average droplet size and range of droplet size, which affects agricultural pesticide quality using image analysis techniques. In the study droplet diameters was measured by using 26 x 76 mm water sensitive paper produced by Ciba-Geigy with a little sprayer. A Nikon D300s camera body and a 105-mm macro lens were used for capturing images. Image J software was used for image evaluations, and Microsoft Excel software was used for evaluation of numerical data. At the end of the study, number median diameter (NMD) was calculated as 75 µm, diameter surface (ds) was calculated as 31 µm, volume median diameter (VMD) was calculated as 300 µm, Sauter diameter (dv/s) was calculated as 37 µm, and VMD/NMD was found 4.00 from evaluations. © by PSP.

This study aims the measurement of the effects of liquid fertilizers at different levels on the growth of duckweed (Lemna minor) and to investigate the relationship between the weight and surface area covered by duckweed via image analysis technique. A linear correlation was found between these values (R2=0.972). The equation is indicated as Y=5.10975+0.199898X where X is the surface area covered by duckweed (mm) and Y is the duckweed weight (mg). It can be emphasized that the results calculated by image analysis technique were at par with the results obtained by weighing.

Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s at the Jet Propulsion Laboratory, Massachusetts Institute of Technology, Bell Laboratories, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone, character recognition, and photograph enhancement. The cost of processing was fairly high, however, with the computing equipment of that era. That changed in the 1970s, when digital image processing proliferated as cheaper computers and dedicated hardware became available. Images then could be processed in real time. As general-purpose computers became faster, they started to take over the role of dedicated hardware for all but the most specialized and computer-intensive operations (Anonymous, 2011b). With the fast computers and signal processors available in the 2000s, digital image processing has become the most common form of image processing and generally, is used because it is not only the most versatile method, but also the cheapest. Digital image processing technology for medical applications was inducted into the Space Foundation Space Technology Hall of Fame in 1994.

WOS: 000409069600013 Climate and environmental conditions primarily affect the yield and quality of agricultural products. Turkey's environment shows different characteristics between regions because of the position of the Turkey in the World. In the agricultural product industry, different techniques are used to measure the physical properties (diameter) of the agricultural products to determine the effect of the climatic difference between regions on the quality of goods. Many factors affect the classificatin of agricultural products such as the physical properties of the product surface, the color and the light condition. In this study, lemon, apple and orange varieties were choosen for the tests. Their diameters were measured by using ultrasonic, infrared and image processing techniques and the sensing qualities of these sensors were presented according to measurement results. In this research, regression coefficients changeed between 92.20 - 96.00%, 72.80 - 77.00%, and 51.30 - 67.30% between three agricultural products, at ultrasonic measurement, infrared measurement and image processing methods respectively. The results showed that the image analysis method could be used more effectively than ultrasonic and infrared measurement techniques for the classififacion of products.