AIMC Topic: Actinidia

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TTI and pH-responsive dual colorimetric sensor arrays combined with a cascaded deep learning approach for dynamic monitoring of freshness of fresh-cut fruits.

Food chemistry
Dynamic shelf-life monitoring of fresh-cut fruits faces challenges from temperature fluctuations and packaging failures in cold chains, causing discrepancies between theoretical predictions and actual spoilage. This study developed a dual colorimetri...

Calibrating the prediction model of soluble solids content and firmness in kiwifruit across years based on NIR spectroscopy using model transfer and transfer learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Near-infrared (NIR) spectroscopy has been widely used in nondestructive detection of fruit internal quality. However, the biological variability of fruit would change their texture, which may lead to the failure of fruit quality prediction models bui...

GMOPNet: A GAN-MLP two-stage network for optical properties measurement of kiwifruit and peaches with spatial frequency domain imaging.

Food chemistry
Spatial frequency domain imaging (SFDI) is an imaging technique using spatially modulated illumination for measurement of optical properties. Conventional SFDI methods require capturing at least six images, making it time-consuming. This study presen...

A dual-branch selective attention capsule network for classifying kiwifruit soft rot with hyperspectral images.

Scientific reports
Kiwifruit soft rot is highly contagious and causes serious economic loss. Therefore, early detection and elimination of soft rot are important for postharvest treatment and storage of kiwifruit. This study aims to accurately detect kiwifruit soft rot...

Using artificial neural network in determining postharvest LIFE of kiwifruit.

Journal of the science of food and agriculture
BACKGROUND: Artificial intelligence systems have been employed for the development of predictive models that estimate many agricultural processes.