Apricot Production Forecast of the Leading Countries in  The Period of 2018-2025.

Uzundumlu, Ahmet Semih; KARABACAK, Tuba; Ali, A. E. M.

doi:10.9755/ejfa.2021.v33.i8.2744

Cited by 6 publications

(2 citation statements)

References 11 publications

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“…These compounds may be necessary for human health [2,3]. The leading countries in terms of the production of apricot, as estimated for 2018-2025, are Turkey, Uzbekistan, Algeria, and Italy [4]. Apricot seeds have great industrial potential.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach to the Authentication of Apricot Seed Cultivars Using Innovative Models Based on Image Texture Parameters

et al. 2022

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The different cultivars of apricot seeds may differ in their properties. To ensure economical and efficient seed processing, knowledge of the cultivars’ composition and physical properties may be necessary. Therefore, the correct identification of the cultivar of the apricot seeds may be very important. The objective of this study was to develop models based on selected textures of apricot seed images to distinguish different cultivars. The images of four cultivars of apricot seeds were acquired using a flatbed scanner. For each seed, approximately 1600 textures from the image, converted to the different color channels R, G, B, L, a, b, X, Y, and Z, were calculated. The models were built separately for the individual color channels; the color spaces Lab, RGB, XYZ; and all color channels combined based on selected texture parameters using different classifiers. The average accuracy of the classification of apricot seeds reached 99% (with an accuracy of 100% for the seeds of the cultivars ‘Early Orange’, ‘Bella’, and ‘Harcot’, and 96% for ‘Taja’) in the case of the set of textures selected from the color space Lab for the model built using the Multilayer Perceptron classifier. The same classifier produced high average accuracies for the color spaces RGB (90%) and XYZ (86%). For the set of textures selected from all color channels, i.e., R, G, B, L, a, b, X, Y, and Z, the average accuracy reached 96% (Multilayer Perceptron and Random Forest classifiers). In the case of individual color channels, the highest average accuracy was up to 91% for the models built based on a set of textures selected from color channel b (Multilayer Perceptron). The results proved the possibility of distinguishing apricot seed cultivars with a high probability using a non-destructive, inexpensive, and objective procedure involving image analysis.

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Section: Introductionmentioning

confidence: 99%

A Novel Approach to the Authentication of Apricot Seed Cultivars Using Innovative Models Based on Image Texture Parameters

et al. 2022

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“…The obtained results were compared with the 2nd and 3rd order regression models obtained using the Matlab curve fitting toolbox [11]. Previously, estimates of annual apricot production for Turkey were presented using various time series analyses in some previous studies [12], [13]. In this study, an application of the PID-based optimizer system [10] was demonstrated for the polynomial modelling of the annual apricot production data from Malatya region.…”

Section: Introductionmentioning

confidence: 99%

PID tabanlı optimize edici döngüsü için bir uygulama: Malatya kayısısının yıllık üretim regresyon modellerinin tahmini

Deniz

2022

DÜMF MD

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In this study, a data analysis application for the PID-based optimizer loop, which was previously proposed in a former study, is carried out. In this application, quadratic and cubic polynomial regression models were obtained for the estimation of annual apricot production by using the yearly total apricot production data of Malatya between 1991 and 2020. In addition, an average of these regression model estimations was calculated to increase estimation reliability. Annual apricot production amount was estimated by using the regression models obtained with the PID-based optimizer system between 2021-2025. The results were compared with the results obtained with the Matlab curve fitting toolbox.

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Insights on the bioecology of the invasive apricot seed wasp Eurytoma samsonowi (Hymenoptera: Eurytomidae) in Tunisia

et al. 2023

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Apricot Production Forecast of the Leading Countries in The Period of 2018-2025.

Cited by 6 publications

References 11 publications

A Novel Approach to the Authentication of Apricot Seed Cultivars Using Innovative Models Based on Image Texture Parameters

A Novel Approach to the Authentication of Apricot Seed Cultivars Using Innovative Models Based on Image Texture Parameters

PID tabanlı optimize edici döngüsü için bir uygulama: Malatya kayısısının yıllık üretim regresyon modellerinin tahmini

Insights on the bioecology of the invasive apricot seed wasp Eurytoma samsonowi (Hymenoptera: Eurytomidae) in Tunisia

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