AIMC Topic: Solanum melongena

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Hyperspectral discrimination of vegetable crops grown under organic and conventional cultivation practices: a machine learning approach.

Scientific reports
A verifiable and regional level method for mapping crops cultivated under organic practices holds significant promise for certifying and ensuring the quality of farm products marketed as organic. The prevailing method for the identification of organi...

Deep learning-based prediction of plant height and crown area of vegetable crops using LiDAR point cloud.

Scientific reports
Remote sensing has been increasingly used in precision agriculture. Buoyed by the developments in the miniaturization of sensors and platforms, contemporary remote sensing offers data at resolutions finer enough to respond to within-farm variations. ...

Disease Classification in Eggplant Using Pre-trained VGG16 and MSVM.

Scientific reports
Currently, the application of deep learning in crop disease classification is one of the active areas of research for which an image dataset is required. Eggplant (Solanum melongena) is one of the important crops, but it is susceptible to serious dis...

Antigenic and pathogenicity activities of Ralstonia solanacearum race 3 biovar 2 molecularly identified and detected by indirect ELISA using polyclonal antibodies generated in rabbits.

Microbial pathogenesis
Eight molecular-characterized isolates of Ralstonia solanacearum from potato belonging to race 3 biovar 2, their virulence were evaluated on potato cv. Lady Rosette, tomato cv. Strain B, eggplant cv. Balady and pepper cv. Balady and showed high virul...

Regression study on fruit-setting days of purple eggplant fruit based on in situ VIS-NIRS and attention cycle neural network.

Journal of food science
In the intelligent harvesting of eggplant, the lack of in situ identification technology makes it challenging to determine the maturity of purple eggplant fruit. The length of the fruit-setting date can determine when the eggplant is ready to be harv...