An MLP artificial neural network for detection of the degree of saccharification of Arabic gum used as a carrier agent of raspberry powders

Przybył, Krzysztof; Masewicz, Łukasz; Koszela, Krzysztof; Duda, Adamina; Szychta, Marek; Gierz, Łukasz

doi:10.1117/12.2602011

Cited by 10 publications

(7 citation statements)

References 23 publications

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“…Observation of changes in plants using vision systems [11][12][13] , a photogrammetric method 14 and luminescence spectrometry are becoming more and more important in assessing the condition of plants and crops. Using appropriate image analysis methods, it is possible to obtain a lot of important information about the observed objects, such as quality parameters [15][16][17][18] , physical data 19,20 , selection data 21,22 or classification data 23,[26][27][28] . The test showed that the excitation-emission spectra can also be useful for the detection of the application of a plant protection product on leafs, which is important from the point of view of spray drift and environmental protection.…”

Section: Discussionmentioning

confidence: 99%

Detecting of plant protection spraying by excited luminescence

Szychta

Szulc²,

Gierz³

et al. 2022

Fourteenth International Conference on Digital Image Processing (ICDIP 2022)

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The research was carried out to detect plant protection products on plant leaves using excited luminescence. The tests were carried out for the leaves of two random plant species and four typical plant protection products. The study of excitation and emission spectra (EX-EM) was carried out on the Edinburgh Instruments FS900 luminescence spectrometer equipped with an attachment for measurements from the surface. The collected EX-EM characteristics of clean leaves were compared with the EX-EM characteristics of leaves coated with plant protection products and the EX-EM characteristics of the agents themselves. The obtained results allowed for the assessment of the suitability of the excited luminescence method for the plant protection spraying measuring, including the detection or identification of inappropriate use of plant protection products by a farmer.

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Section: Discussionmentioning

confidence: 99%

Detecting of plant protection spraying by excited luminescence

Szychta

Szulc²,

Gierz³

et al. 2022

Fourteenth International Conference on Digital Image Processing (ICDIP 2022)

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“…9 research samples were obtained, which were different from each other in terms of the amount and types of carriers (Arabic gum, maltodextrin and inulin). A detailed description of the origin of carrier, type of carrier and its proportion was provided by Przybył et al 7,11 .…”

Section: Sample Preparationmentioning

confidence: 99%

Application of artificial neural networks in recognizing carrier based on the color of raspberry powders obtained in the spray-drying process

Przybył

Wawrzyniak²,

Samborska³

et al. 2022

Fourteenth International Conference on Digital Image Processing (ICDIP 2022)

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Fruit juices and vegetable and fruit juices are the products, which provide our bodies with a lot of valuable and nutritional ingredients and play a major role in prevention of numerous illnesses. Raspberries are the valuable source of bioactive compounds. As part of preserving food, whose main aim is to extend stability of products obtained only in season, the researchers took advantage of spray drying technique. In the research part of the study, research samples were prepared in the form of raspberry powders obtained from the process of dehumidified spray drying. Because of the research, a neural model was made, which supported the evaluation of the quality of detecting powder samples based on their color. The devised neural network reached classification accuracy at 0.924.

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“…Growing consumer awareness puts pressure on food producers to supply products that meet certain standards (norms) [15], forcing them to search for methods allowing for effective control and assessment of the quality of manufactured food products. In connection with continuous development and actions taken to modernize and automate food production processes, methods used to assess the quality of raw materials and food products have also been evolving, and now also encompass analysis of sensory characteristics, including color [16][17][18], shape, and texture, using instrumental methods [19,20]. The adequate analysis of sensory characteristics of food products based on digital photos may be a key factor in the development of these methods.…”

Section: Introductionmentioning

confidence: 99%

Machine and Deep Learning in the Evaluation of Selected Qualitative Characteristics of Sweet Potatoes Obtained under Different Convective Drying Conditions

et al. 2022

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This paper discusses the use of various methods to distinguish between slices of sweet potato dried in different conditions. The drying conditions varied in terms of temperature, the values were: 60 °C, 70 °C, 80 °C, and 90 °C. Examination methods included instrumental texture analysis using a texturometer and digital texture analysis based on macroscopic images. Classification of acquired data involved the use of machine learning techniques using various types of artificial neural networks, such as convolutional neural networks (CNNs) and multi-layer perceptron (MLP). As a result, in the convective drying, changes in color darkening were found in products with the following temperature values: 60 °C (L = 83.41), 70 °C (L = 81.11), 80 °C (L = 79.02), and 90 °C (L = 75.53). The best-generated model achieved an overall classification efficiency of 77%. Sweet potato dried at 90 °C proved to be completely distinguishable from other classes, among which classification efficiency varied between 61–83% depending on the class. This means that image analysis using deep convolutional artificial neural networks is a valuable tool in the context of assessing the quality of convective-dried sweet potato slices.

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An MLP artificial neural network for detection of the degree of saccharification of Arabic gum used as a carrier agent of raspberry powders

Cited by 10 publications

References 23 publications

Detecting of plant protection spraying by excited luminescence

Detecting of plant protection spraying by excited luminescence

Application of artificial neural networks in recognizing carrier based on the color of raspberry powders obtained in the spray-drying process

Machine and Deep Learning in the Evaluation of Selected Qualitative Characteristics of Sweet Potatoes Obtained under Different Convective Drying Conditions

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