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Fruit

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Application of a multilayer perceptron artificial neural network for identification of peach cultivars based on physical characteristics.

PeerJ
In the fresh fruit industry, identification of fruit cultivars and fruit quality is of vital importance. In the current study, nine peach cultivars (Dixon, Early Grande, Flordaprince, Flordastar, Flordaglo, Florda 834, TropicSnow, Desertred, and Swel...

Evaluation and process monitoring of jujube hot air drying using hyperspectral imaging technology and deep learning for quality parameters.

Food chemistry
Timely and effective detection of quality attributes during drying control is essential for enhancing the quality of fruit processing. Consequently, this study aims to employ hyperspectral imaging technology for the non-destructive monitoring of solu...

Development of a visuo-tactile sensor for non-destructive peach firmness and contact force measurement suitable for robotic arm applications.

Food chemistry
Precise measurement of firmness was crucial for determining optimal harvesting times, implementing rational storage strategies and minimizing avoidable waste. Current technologies for assessing peach firmness struggled to balance high precision and n...

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...

Predicting physicochemical properties of papayas (Carica papaya L.) using a convolutional neural networks model approach.

Journal of food science
The current state of quality assessment methods for agricultural produce, particularly fruits, heavily relies on manual inspection techniques, which could be subjective, time-consuming, and prone to human errors. Consequently, there have been emergin...

MOF-Based Biomimetic Enzyme Microrobots for Efficient Detection of Total Antioxidant Capacity of Fruits and Vegetables.

Small (Weinheim an der Bergstrasse, Germany)
Green and efficient total antioxidant capacity (TAC) detection is significant for healthy diet and disease prevention. This work first proposed the concept of TAC colorimetric detection based on microrobots. A novel metal-organic framework (MOF)-base...

A rapid, non-destructive, and accurate method for identifying citrus granulation using Raman spectroscopy and machine learning.

Journal of food science
Citrus fruits are widely consumed for their nutritional value and taste; however, juice sac granulation during fruit storage poses a significant challenge to the citrus industry. This study used Raman spectroscopy coupled with machine learning algori...

Artificial intelligence-driven quantification of antibiotic-resistant Bacteria in food by color-encoded multiplex hydrogel digital LAMP.

Food chemistry
Antibiotic-resistant bacteria pose considerable risks to global health, particularly through transmission in the food chain. Herein, we developed the artificial intelligence-driven quantification of antibiotic-resistant bacteria in food using a color...

Machine learning techniques for non-destructive estimation of plum fruit weight.

Scientific reports
Plum fruit fresh weight (FW) estimation is crucial for various agricultural practices, including yield prediction, quality control, and market pricing. Traditional methods for estimating fruit weight are often destructive, time-consuming, and labor-i...

Rheological modelling of apple puree based on machine learning combined Monte Carlo simulation: Insight into the fundamental light- particle structure interaction processes.

Food chemistry
In this work, apple purees from different particle concentration and verifying in size were reconstituted to investigate their impacts on rheological behaviors, optical properties and light interaction at 900-1650 nm. The optical scattering of differ...