A smart decision framework for the prediction of thrips incidence in organic banana crops

Campos, Jean C.; Manrique-Silupú, José; Dorneanu, Bogdan; Ipanaqué, William; Arellano‐García, Harvey

doi:10.1016/j.ecolmodel.2022.110147

Cited by 4 publications

(4 citation statements)

References 39 publications

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“…The qualitative results show the literature on the advances of industry 4.0 technology reviewing the technological trends [24] and [25] and intelligent architectures of automation by artificial vision [26], [27], [28] and [29].…”

Section: Discussionmentioning

confidence: 74%

“…Secondly, according to the qualitative approach, the researchers [24] and [25] exhaustively reviewed the relevant information according to technology as trends of industrial revolution in food. Consequently [26], [27], [28] and [29] reviewed on machine vision automation architecture and incident predictions for precision agriculture.…”

Section: ▪ In Dimensionmentioning

confidence: 99%

“…According to [24] and [25] they dealt with trends and contribution of scientific institutions in the development of the industrial revolution 4.0. [26] and [27] architecture and automation with IoT, [28] Intelligent decision framework for predicting pest occurrence and finally [29] machine vision applications ▪ In Dimension 2 Similarly [24] and [25] studied about food industry within the industrial revolution 4.0. And [26], [27], [28] and [29] precision smart agriculture by intelligence and artificial vision applying ICTs for productivity improvements.…”

Section: ▪ In Dimensionmentioning

confidence: 99%

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IoT application technologies for agriculture in Latin America during the COVID-19 pandemic

Cornejo-Olivares,

Contreras-Cossio,

Hoyos-Rivas

et al. 2023

Proceedings of the 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023): “Leaders

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IoT digitizes any plant of agricultural processes simplifying the activities; producing products of higher quality in a set period and optimizing automatic irrigation systems. Evaluate IoT application technologies for Latin American agriculture during the COVID-19 pandemic, through systematic search engine database vision; obtaining 78 publications between 2019 and 2022, considering 14 studies by inclusion criteria of methodological heterogeneity. The main IoT application technologies for smart agriculture: according to the quantitative approach in dimension 1; 3 articles contribute to architecture and 1 to irrigation control; while in dimension 2; 2 articles contribute to environmental monitoring and 4 to efficient water management; the same in qualitative approach in dimension 1; 2 articles show trends of the industrial revolution in food, 2 in automation architecture and 2 in the intelligent decision by artificial vision; also in dimension 2; 2 articles studied trends of industrial revolution 4.0 and 4 intelligent precision agriculture and computer vision. Therefore, quantitative studies were based on experimental applications of data architecture design to optimize water consumption according to environmental conditions; reviewing in qualitative approach trend documents of the Industrial Revolution 4.0 applying artificial vision.

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Section: Discussionmentioning

confidence: 74%

Section: ▪ In Dimensionmentioning

confidence: 99%

Section: ▪ In Dimensionmentioning

confidence: 99%

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IoT application technologies for agriculture in Latin America during the COVID-19 pandemic

Cornejo-Olivares,

Contreras-Cossio,

Hoyos-Rivas

et al. 2023

Proceedings of the 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023): “Leaders

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“…Peru supplies approximately 3% of world banana production and almost all bananas grown in Peru are exported (FAO, 2021;Campos et al, 2022), especially the Cavendish type; this type of banana only grows in the states of Tumbes, Piura and Lambayeque. In 2021, about 2.5 million tons of bananas were produced (MIDAGRI, 2022) at a value of 145.24 million USD.…”

Section: Introductionmentioning

confidence: 99%

Influence of convection drying with hot air on the physicochemical and phytochemical properties of green banana flour (Musa cavendish)

Espinoza-Espinoza,

Juárez-Ojeda,

Ruiz-Flores

et al. 2023

Front. Sustain. Food Syst.

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The present study focuses on the effect of different drying temperatures (DT) (40, 60 and 80°C) and the combination of banana slice thicknesses (BST) (2 and 4 mm) on the physicochemical properties and phytochemicals of green banana flour (GBF). The influence of the drying temperature and thickness of the banana pulp slice were significant (p < 0.05) on the TPC and % inhibition of the DPPH radical. As the temperature increased from 60 to 80°C and the thickness decreased from 4 to 2 mm, the TPC values (225.69 ± 5.13 GAE/100 g DW) and % inhibition of the DPPH radical (91.08 ± 2.28%) were higher, respectively. Physicochemical properties such as: soluble solids, titratable acidity, pH and ashes were not influenced by DT and BST; and the humidity values were < 10%. These findings indicate that drying with hot air from 60 to 80°C and thicknesses <4 mm favor a greater conservation of the antioxidant capacity in banana flour.

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LSTM with shallow NNs for indoor temperature long-term predictions in refrigeration systems

Machacuay,

Manrique-Silupu,

Ipanaqué

2024

Neural Comput & Applic

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A smart decision framework for the prediction of thrips incidence in organic banana crops

Cited by 4 publications

References 39 publications

IoT application technologies for agriculture in Latin America during the COVID-19 pandemic

IoT application technologies for agriculture in Latin America during the COVID-19 pandemic

Influence of convection drying with hot air on the physicochemical and phytochemical properties of green banana flour (Musa cavendish)

LSTM with shallow NNs for indoor temperature long-term predictions in refrigeration systems

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