Use of mid infrared spectroscopy to analyze the ripening of Brazilian bananas

Luiz, Leandro da Conceição; Nascimento, Cláudia; Bell, Maria José Valenzuela; Batista, Rafaela Tavares; Seshadri, M.; Anjos, Virgílio de Carvalho dos

doi:10.1590/fst.74221

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…These images are then analysed to determine the distribution and density of crops throughout the field. This method allows farmers to efficiently monitor crop health, identify areas of overgrowth or undergrowth, and make informed decisions regarding irrigation, fertilization, and pest management [15][16][17][18].…”

Section: Drones As Alarmmentioning

confidence: 99%

Enhancing Agricultural Practices Through IoT-Based Smart Farming Technologies: A Case Study on Banana Crop Yield Optimization

Pandey,

Kumar,

Khanna

et al. 2024

Asian J. Res. Com. Sci.

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Aims: Smart farming and precision agriculture have emerged as transformative paradigms in modern agricultural practices, leveraging technological innovations to enhance productivity, sustainability, and efficiency in food production. This paper provides a comprehensive review of the concepts and technologies related to smart farming. The work proposed implements a sensor assisted IoT based model to enhance the overall yield of banana crop, by monitoring the current conditions existing at the site and predicting the alterations to achieve optimal conditions for conducive and healthy growth, further early identification and prediction of infection causing pathogens to have also been embedded in the model. Model designed has been tested on the farm field of banana crop located in the premises of Amity University Lucknow Campus equipped with moisture and humidity sensors (DHT11), NPK soil nutrient sensor, PIR motion sensor (HC-SR501), pH Sensor (pH -450), rain drop sensor along with camera installed drone for infection identification. Data from sensors and drone camera were monitored at regular intervals for future predictions about health and productivity estimate of the crop.

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Section: Drones As Alarmmentioning

confidence: 99%

Enhancing Agricultural Practices Through IoT-Based Smart Farming Technologies: A Case Study on Banana Crop Yield Optimization

Pandey,

Kumar,

Khanna

et al. 2024

Asian J. Res. Com. Sci.

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Quality Assessment of Banana Ripening Stages by Combining Analytical Methods and Image Analysis

et al. 2023

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Currently, the evaluation of fruit ripening progress in relation to physicochemical and texture-quality parameters has become an increasingly important issue, particularly when considering consumer acceptance. Therefore, the purpose of the present study was the application of rapid, nondestructive, and conventional methods to assess the quality of banana peels and flesh in terms of ripening and during storage in controlled temperatures and humidity. For this purpose, we implemented various analytical techniques, such as attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy for texture, colorimetrics, and physicochemical features, along with image-analysis methods and discriminant as well as statistical analysis. Image-analysis outcomes showed that storage provoked significant degradation of banana peels based on the increased image-texture dissimilarity and the loss of the structural order of the texture. In addition, the computed features were sufficient to discriminate four ripening stages with high accuracy. Moreover, the results revealed that storage led to significant changes in the color parameters and dramatic decreases in the texture attributes of banana flesh. The combination of image and chemical analyses pinpointed that storage caused water migration to the flesh and significant starch decomposition, which was then converted into soluble sugars. The redness and yellowness of the peel; the flesh moisture content; the texture attributes; Brix; and the storage time were all strongly interrelated. The combination of these techniques, coupled with statistical tools, to monitor the physicochemical and organoleptic quality of bananas during storage could be further applied for assessing the quality of other fruits and vegetables under similar conditions.

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Use of mid infrared spectroscopy to analyze the ripening of Brazilian bananas

Cited by 2 publications

References 24 publications

Enhancing Agricultural Practices Through IoT-Based Smart Farming Technologies: A Case Study on Banana Crop Yield Optimization

Enhancing Agricultural Practices Through IoT-Based Smart Farming Technologies: A Case Study on Banana Crop Yield Optimization

Quality Assessment of Banana Ripening Stages by Combining Analytical Methods and Image Analysis

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