Volume 9 Issue 2 ( June 2022 )


Artificial Neural Based Quality Assessment of Guava Fruit

Tejas G. Patil, Sanjay P. Shekhawat


Merchants and food services are very competitive, and food manufacturers are under considerable pressure not to increase end-product costs when production costs go up. External pressures causing physical texture changes or chemical color, smell, and taste alterations induce fruit tissue injury. To examine this, a novel technique is proposed to identify surface and subsurface flaws utilizing a thermal picture and ordinary digital image concerning the original guava. This study discovered thermal data for thermal image capturing on the guava samples stored in the atmosphere with a FLIR-C2 thermal camera. A systematic Image processing approach was employed to distinguish the injured tissues of the fruits that were unaffected. The total result of the identification of thermal blushes is 95 %, whereas the result of standard image processing is 62.5 %. Theory permitted to differentiate the sound from the defected fruit scorched by birds or insects in creating food processing safety policies, developing the passive thermographic method.

Keywords: Thermal Image; Guava, Image Processing; Thermal Camera