Estimation of the storage properties of rapeseeds using an artificial neural network

Voća, Neven; Pezo, Lato; Jukić, Željko; Lončar, Biljana; Šuput, Danijela; Krička, Tajana

doi:10.1016/j.indcrop.2022.115358

Cited by 9 publications

(6 citation statements)

References 32 publications

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“…This division method adhered to a standard approach as detailed in the investigation by [34]. Following data preparation, regression models were constructed based on Equation (1) as outlined by [35]:…”

Section: Artificial Neural Network Modelingmentioning

confidence: 99%

Camelina sativa Oilseed Cake as a Potential Source of Biopolymer Films: A Chemometric Approach to Synthesis, Characterization, and Optimization

Šuput,

Pezo,

Rakita

et al. 2024

Coatings

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In this work, the possibility of obtaining biopolymer films from Camelina sativa oilseed cake (CSoC) at different parameters of the synthesis process was investigated. The pH (values 8, 10, and 12), the temperature (60, 80, and 100 °C), and the concentration of the cake in the film-forming suspension (3, 4, and 5%) were varied. The films obtained were characterized by studying the mechanical, barrier, physico-chemical, structural, and biological properties (antioxidant and antimicrobial). The results showed moderate mechanical properties, indicating the application of these biopolymer materials as coatings. Low values of water vapor permeability (5.1–12.26 g/m2h) and very low transmission in the UV range (less than 2%) indicate good barrier properties. FTIR analysis confirmed the films’ composite structures: peaks related to proteins, polysaccharides, lipids, and cellulose were detected. The biological activity of the obtained CSoC films was pronounced so that they could be used for active packaging. All films have high antioxidant activity, which is more pronounced in samples synthesized at pH 8. The films possess antibacterial properties against S. aureus, while some had an inhibitory effect on S. typhimurium. Standard score analysis showed that the film sample synthetized at pH = 10, temperature = 100 °C, and concentration = 5% had optimal investigated properties.

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Section: Artificial Neural Network Modelingmentioning

confidence: 99%

Camelina sativa Oilseed Cake as a Potential Source of Biopolymer Films: A Chemometric Approach to Synthesis, Characterization, and Optimization

Šuput,

Pezo,

Rakita

et al. 2024

Coatings

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“…These statistical parameters were calculated using equations [ 39 ]. In addition, Yoon’s method of global sensitivity (8) was used to evaluate the direct influence of the input parameters on the output variables, which correspond to the weighting coefficients (w) within the ANN model [ 40 , 41 ]:

where N represents the total number of data records, while x exp , i and x pre,i are the experimental and model-predicted values, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…These statistical parameters were calculated using equations [39]. In addition, Yoon's method of global sensitivity (8) was used to evaluate the direct influence of the input parameters on the output variables, which correspond to the weighting coefficients (w) within the ANN model [40,41]:…”

Section: The Accuracy Of the Modelsmentioning

confidence: 99%

Enhancing Cookie Formulations with Combined Dehydrated Peach: A Machine Learning Approach for Technological Quality Assessment and Optimization

Lončar,

Pezo,

Knežević

et al. 2024

Foods

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This study focuses on predicting and optimizing the quality parameters of cookies enriched with dehydrated peach through the application of Support Vector Machine (SVM) and Artificial Neural Network (ANN) models. The purpose of the study is to employ advanced machine learning techniques to understand the intricate relationships between input parameters, such as the presence of dehydrated peach and treatment methods (lyophilization and lyophilization with osmotic pretreatment), and output variables representing various quality aspects of cookies. For each of the 32 outputs, including the parameters of the basic chemical compositions of the cookie samples, selected mineral contents, moisture contents, baking characteristics, color properties, sensorial attributes, and antioxidant properties, separate models were constructed using SVMs and ANNs. Results showcase the efficiency of ANN models in predicting a diverse set of quality parameters with r2 up to 1.000, with SVM models exhibiting slightly higher coefficients of determination for specific variables with r2 reaching 0.981. The sensitivity analysis underscores the pivotal role of dehydrated peach and the positive influence of osmotic pretreatment on specific compositional attributes. Utilizing established Artificial Neural Network models, multi-objective optimization was conducted, revealing optimal formulation and factor values in cookie quality optimization. The optimal quantity of lyophilized peach with osmotic pretreatment for the cookie formulation was identified as 15%.

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“…The experimental dataset was randomly divided into two subsets: training (70%) and testing (30%), facilitating effective cANN modeling. The outcomes of the ANN, including weights and bias calculation values, are influenced by the initial parameter assumptions necessary for constructing and fitting the ANN [23]. Various network topologies were explored, with hidden neuron counts ranging from 5 to 20.…”

Section: Classification Of An Artificial Neural Network Modelmentioning

confidence: 99%

“…The obtained results of physicochemical parameters of 609 honey samples were presented by descriptive analysis of the results obtained for different botanical origins of honey samples (Table 1), different years of harvest (Table 2), and different regions of the harvested samples (Table 3). Based on Table 1, there were six types of honey identified: acacia (213 samples), honeydew (29), linden (34), monofloral (8), polyfloral (302), and sunflower honey (23). In Table 2, the data show that 209 samples were collected in 2018, followed by 80 samples in 2019, 78 samples in 2020, 108 samples in 2021, and 113 samples in 2022, with an additional 21 collected in 2023.…”

Section: Physicochemical Characterizationmentioning

confidence: 99%

Assessing the Impact of Botanical Origins, Harvest Years, and Geographical Variability on the Physicochemical Quality of Serbian Honey

Tasić,

Pezo,

Lončar

et al. 2024

Foods

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This study summarized the physicochemical analysis of 609 honey samples originating from the Republic of Serbia. Variations among honey samples from different botanical origins, regions of collections, and harvest years were exposed to descriptive statistics and correlation analysis that differentiated honey samples. Furthermore, most of the observed physicochemical parameters (glucose, fructose, sucrose content, 5-hydroxymethylfurfural (5-HMF) levels, acidity, and electrical conductivity) varied significantly among different types of honey, years, and regions. At the same time, no noticeable difference was found in diastase activity, moisture content, and insoluble matter. Based on the obtained results, 22 honey samples could be considered adulterated, due to the irregular content of sucrose, 5-HMF, acidity, and diastase activity. In addition, 64 honey samples were suspected to be adulterated. Adulterated and non-compliant samples present a relatively low percentage (14.1%) of the total number of investigated samples. Consequently, a considerable number of honey samples met the required standards for honey quality. Overall, these findings provide insights into compositional and quality differences among various types of honey, aiding in understanding their characteristics and potential applications.

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Estimation of the storage properties of rapeseeds using an artificial neural network

Cited by 9 publications

References 32 publications

Camelina sativa Oilseed Cake as a Potential Source of Biopolymer Films: A Chemometric Approach to Synthesis, Characterization, and Optimization

Camelina sativa Oilseed Cake as a Potential Source of Biopolymer Films: A Chemometric Approach to Synthesis, Characterization, and Optimization

Enhancing Cookie Formulations with Combined Dehydrated Peach: A Machine Learning Approach for Technological Quality Assessment and Optimization

Assessing the Impact of Botanical Origins, Harvest Years, and Geographical Variability on the Physicochemical Quality of Serbian Honey

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